Tag: the buzz

Podcast: Managing payments pressure | Bank Automation News

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Payments fintechs are leaning on technology as consumers look to them to alleviate payments pressure in today’s high interest rate environment.

“The payments space today is in a stress test,” payments fintech Sunbit’s Chief Executive Arad Levertov, tells Bank Automation News on this episode of “The Buzz” podcast, noting that consumers are struggling to make payments and payments fintechs are struggling to scale.

Sunbit uses machine learning, AI and software to offer payment options to customers through retailers, according to Sunbit. The tech provider connects to retail APIs to collect data on performance of their technology and simultaneously offers buy-now-pay-later capabilities, a credit card and point-of-sale lending.

Sunbit customers include dental office Dossett Dental, automotive retailer Highline Parts and Service Center and vision eyewear retailer Henry Ford OptimEyes, according to the Sunbit website.

As payments providers help consumers, they also want to ensure they can scale. To be sure payment companies can accomplish both, Levertov says they should ask themselves:

Listen as Sunbit’s Levertov discusses with “The Buzz” how to navigate a high-rate environment with consumers and technology at the forefront.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:03
Hello and welcome to The Buzz a bank automation news podcast. My name is Whitney McDonald and I’m the editor of bank automation News. Today is November 2 2023. Joining me is Chief Executive of FinTech Sunit Arad Levertov. He is here to discuss payments disruptors, leveraging AI and Gen AI today and the future of the payments landscape. he co founded Sunday in 2016, and has been in FinTech since 2009. Thanks for joining us.

Arad Levertov 0:30
Thank you for having me. Happy to be here. I’m Arad Levertov. I’m the co founder and CEO of Sunbit. Sunbit is a financial technology for Real Life. We are based in Los Angeles, and we have about 500 employees across the nation. Many people are familiar with the pay overtime functionality, or the Buy Now pay later. And usually the this happens in the online sun beat we have two main products. The first product is a pair of real time functionality that is used for where people needed the most. So when you go to fix your car, or when you go to the dentist or to to get an eyeglass, we help the customer to get the service they need and pay overtime. We are right now operate in about 7500 locations of car repair services, which is about 40% of the market of authorized car dealerships. So if you go to fix a car in the authorized car dealership, there is four out of 10 chances that you will see us. In addition, we are in dental, as I mentioned that eyeglasses places overall over 20,000 locations, and we are adding five to 700 a month. Our second product is the sun beat card. And the Sunday card is a product that we announced in 2022. And basically brings the best of credit, debit and buy now pay later into the hands of each customers. And the customer can use it in with a physical card, or with a virtual card. In over there, we’ve processed over 300 million transaction and customer uses 60% of the time in everyday purchases like gas, food, and groceries. And basically we allow the customer to choose each transaction, how they want to pay where it’s like a debit, which means paying full credit, paid only the minimum or split into 236 or 12 months like buy now pay later. Our products are focused on the customers, we are inclusive, which means we have to have more customers, and we never charge any fees.

Whitney McDonald 2:43
Great. Well, thank you again for joining us and for talking us through some bit. I’d love to get started with just setting the scene for today’s payments industry. What are you seeing today kind of where to where do we stand within payments today?

Arad Levertov 2:58
That’s a good question. Because when you think about where we are today, you you cannot ignore the macro economics condition. Right. So you know, the Fed increased rates starting last year. And the current interest rate is super, super high, which impacts the entire economy, but mostly the payments and the FinTech companies. So today, when the interest is I customers are struggling more to make payments and customer struggling more to make purchases. And that actually it’s an opportunity and also I call it a stress test for every company, especially companies that are in the payment spreads, which also got impacted by the by the increase in interest rate. And when it when I look at this stress test, each company needs to ask itself like three basic questions. One, do I really add value to consumer? Two? Can I make profit out of it? And three? Can I do it? With the same core values and promises? I promised the consumers the employee like you know, three, four years ago when things were easier. So what does it mean? It means that especially in the payment space, when interest is high in customer struggling, our customers still willing to take my product and pay money for it? In our case, it’s like you know, the customers and the merchant Do they really value needs? Second, can I do it while I my cost is lower than the revenue which is super important these days? And three Can I do it with the same core values and promises? As I promised to my employees, we promise to customers we promise to invest up to three years ago when the market was different. So I think that the payment space today is in in a stress test and in the good news that eventually it will differentiate the I call it the real value companies from the free riders companies that were riding on the payment Space. Two, three years ago when interest was low, and everybody was, you know, money was easy.

Whitney McDonald 5:06
Now you talk through the stress that’s in the macroeconomic environment today, maybe you could talk us through where technology comes in to address these pain points within payments.

Arad Levertov 5:20
So this is exactly where technology technology, but only if it’s kind of in the fundamental of the business is coming into play. Because at the end of the day, in order to both serve customers, and make profit, when you’re you know, basic costs increasing, you need to think about scale, and scale comes with technology. So, when you are able to operate with, you know, with more technology, better underwriting, smarter decisions, better go to market or you know, something that is pretty famous right now, what we call the CAC, to LTV, the customer acquisition costs, and the lifetime value of the to get from the from the from the customer, the CAC to LTV ratio. This is where technology comes into play. So you can actually operate in scale without the additional cost of you know, manual costs or travel costs or stuff like this. And this is happens in the entire world. In many, many industries. I mean, right now we’re sitting in a recording of podcasts, which was never like 2030 years ago, there was no podcast, people actually listen only to what comes to the news. Now people listen to us because they want to focus on something personalized. In the payment space. Specifically, it’s a little bit delayed because of regulations because of other stuff. But now when you get to the technology around regulation, this is where you will be able to win for the long term.

Whitney McDonald 6:56
Now, when it comes to payments, companies like Sunday, it’s not a traditional means means for payments, how do companies like sun bet, disrupt the financial services industry, if you could kind of talk us through that that would be great. Course.

Arad Levertov 7:18
So there are many people talking about FinTech over the last literally 10 years, which is great. However, still, the biggest, biggest player in the markets are the credit cards, right. And consumer credit, people use credit cards, everybody has credit card in their hand, and credit card are easy to use many people you know it is to pay, but it’s horrible experience to apply. approval rate is really low there, you know, sometimes only 50%, actually of the people get approved, people get declined. By the way, I personally got declined for credit card after moving to the US when applying at point of sale at one of the retail places. And the most important there are many, many unnecessary and hidden fees. And when you think about this, in general financial market, they focus on making a lot of money, and they less focus on the consumer. fun bit. Try to innovate for good and put the customer in the center. So for example, one of our our main mission was from day one, eliminate financial waste and pass the value to the consumers. And one of our values innovate for good. So what does it mean? We try to be better to be more personalized for the customer. So your rate should be different in my rate, right? And end it up. But both rates should be transparent. No hidden fees, no fees at all. Actually, exactly. You know how much you’re gonna pay. We want to be more inclusive than the competition because we use more under more sophisticated data, more machine learning, and we use it across the across the business to get more customer into the door. And if we do it well and these customer pay back, we can get lower rates for everybody. So use technology across the entire spectrum. How do we get to the merchant? As I said, we are adding five to 700 new merchants amongst we choose them to make sure that we do it with the right operating costs. So we add them right the sales calls, of course, how do we handle customers? How do we treat customers? And how do we run the operation in general, we use technology. However, I would say that this is not enough. Technology is amazing in the most sophisticated under artificial intelligence, and machine learning is being used across the nation across the business. However, in addition, one we put the customer in the center, which is super important, we remember that it’s all for the customer and to we never get blinded by the numbers. You know at some beat we sell have millions of customers and posts of billions of dollars of loans. But we remember that behind these numbers, there are people that at the end of the day, wanted to fix the car and go back to work, wanted to get the root canal. And you know, and get out with the pain and go back to the life. And when I’m able to, to help these customers, split the purchase, over three months over sometimes 12 months without paying any interest and still make money because they make from the merchant, I see that I’m doing the right thing. And using technology to help people, that’s the basic of what we do we never forget about it.

Whitney McDonald 10:42
Now I know they said it’s not the most important part. But technology is is a key player here for some but can we talk through the application of data and machine learning and AI to accomplish all of this?

Arad Levertov 10:56
Of course, yes, technology is the basically enabler that helps us actually get what we do, right. So when you think about some between when we think about machine learning, you know, all the big world machine learning AI data science, we from day one, and we started in in 2016, decided to put it really across their operations. So because we work with mostly physical locations, we have retail operations, which means we need to get to the stores, we need to sell to them, we need to implement our solution into their systems into their API’s into the system. And we all need to do it in a smart way because it costs money. So we build technology and data that basics, give us feedback on how does the how the how much time it takes to get the store how much data you’d like these stories better than the other stories, these vertical versus that better than the other vertical. And we get this data and get better and better and better. And then we need the stars to keep using us and working with us and working with the customer. So again, here, use underwriting use technology to get the feedback about these customers and how they do versus the store to get better and better and continue when you serve the customer, you want the end user customer to have seamless experience when they take the loan when they pay for the loan. And if they want to, you know to change some time and they have some challenges not paying the loan, give them the best experience. And we use technology look at the entire system, from A to Z with technology with underwriting with AI, and then go back with the focus on the customer.

Whitney McDonald 12:41
Now, of course, you’re in the business of innovation in payments, wondering if you could give us kind of a look ahead as to where the payments market is heading in the next year as we look into 2024.

Arad Levertov 12:56
So I think that the first thing I will try to look is look even farther, like even, you know, 20 to 2030. Because, again, I mentioned that you and I are doing right now podcast, which 20 years ago was nowhere, right. I mean, when I was a kid, we used to read newspaper like literally newspaper. When you think about the payment and you know, financial financial industry, it’s still closer to the newspaper and to the podcast that we are doing right now, which means it stuck many years ago, because customer gets the same, the same many customer get the same, the same products, and it’s all personnel is not focused on the customer. So I think that you know, 10 years from now or whatever, in the long term, it will have to change because customers deserve more, they deserve better product more personalized, and actually cheaper, right? So the companies that will be able to do it are the companies as we mentioned that, you know, focus on technology, put the customer in the in the center, and of course, make profit because if not, you’re not going to survive. So this is the long term, the next year is still going to be challenging, because the interest is high. And this is the new reality whether it’s ends or stuck, you know, easing in end of 2024 and 2025. I don’t know I treat right now this the current situation is the new normal. So it will actually, as I mentioned, be a stress test for all the companies in the space to see if you can get through this and keep growing and you know, doing it while while building profitable, profitable business. You will definitely be the winning for the long term. And you will do it if you focus on technology customers and in Detroit and this is what we try to do they have today.

Whitney McDonald 14:51
You’ve been listening to the buzz, a bank automation news podcast, please follow us on LinkedIn. And as a reminder, you can rate this podcast on your platform Choice thank you for your time and be sure to visit us at Bank automation news.com For more automation news

Transcribed by https://otter.ai

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November 2, 2023
Podcast: Neobanks fight fraud | Bank Automation News

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Neobanks can lean on data and rich client information to protect themselves from fraud attacks.

Almost all neobank activity is accomplished through mobile devices, which makes digital institutions targets for fraudsters, Matt DeLauro, chief revenue officer at fraud prevention and anti-money laundering platform Seon, tells Bank Automation News on this episode of “The Buzz” podcast.

However, neobanks can work proactively when it comes to fraud prevention if they collect the proper client data.

“Gathering the richest amount of information on users and meeting them where they’re at in the customer journey is probably the most important thing to do,” DeLauro said. “If you don’t have the data to be able to take action, then you’re not going to be able to react [to fraud attacks].”

For example, neobanks can check the IP range of devices, monitor cookie hashes and device hashes that are available through Android and Apple and make sure that they have the correct email addresses for clients, DeLauro said.

Listen as Seon’s DeLauro discusses how neobanks can prepare their operations to proactively fight fraud.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:01
Hello and welcome to The Buzz a bank automation news podcast. My name is Whitney McDonald and I’m the editor of bank automation News. Today is October 26 2023. Joining me is Chief Revenue Officer of fraud fighting FinTech Seon Matt DeLauro. He’s here to discuss how Neo banks can fortify their operations to combat fraud. Thanks for joining us.

Matt DeLauro 0:22
My name is Matt DeLauro. I’m the Chief Revenue Officer at cion. I’ve spent about the last 18 years of my career, both building as an engineer but also delivering and selling solutions from a software vendor perspective into retail and fintech and InsurTech. And at cion, where we get the mission of transforming how fraud and risk teams manage their customer journey, right? We provide fraud prevention and anti money laundering and counterterrorism financing platform for businesses that are really is focused on detecting and preventing potential threats before they happen. Rather than investigating and doing the sort of autopsy after it’s already taken place. The big shift in the industry has been towards API for solutions, which is the sort of solution that we’re anchored in so that these things can happen in a frictionless way for customers, when they onboard. And, you know, creating the kind of digital profiling and unique social footprints that are available when we look at onboarding customers through that experience. So that fraud teams can efficiently scale without having to rely on black box machine solutions that are known for things like false positives and bad correlations.

Whitney McDonald 1:33
Great. Well, thank you, again, for being here. Before we get into all the fraud talk and how CNN works, I’d like if we could first set the scene here with neobank adoption, we’re going to be talking about digital banks and Neo banks and how as the adoption grows, the fraud concern grows as well. But may we kind of talk first through what you’re seeing as neobank adoption grows?

Matt DeLauro 1:57
Sure. Yeah. I mean, it’s very strong in the European market. It’s a much more diverse ecosystem, just like it is with, you know, traditional banks, the US and the EU look a little bit different. So there’s more players and more diversity within the marketplace and EMEA. But there’s far more adoption in the aggregate in terms of the number of users in the US by far. So it’s sort of the tale of two stories related to neobank adoption is there’s fewer players with much larger sort of customer pools in the United States and abroad. There’s a lot more selection and a lot more focus, but not nearly the installed base of neobank users.

Whitney McDonald 2:37
Now, maybe we could talk through what you’re seeing, from the Seon perspective, when it comes to fraud. What are some of those examples? What are some common types of fraud that you’re seeing that neobanks need to be monitoring for watching for and fighting against?

Matt DeLauro 2:53
Sure, a lot of a lot of the neobanks, you know, worked very closely with either brokerages or Kryptos, or exchanges, particularly across the pond. And we’re seeing sort of a Back to the Future moment, which is like one of the one of the worst things that’s happening. And so the most prevalent is a lot of confidence scams, we’re seeing a lot of people that are you know, getting access to phone numbers and calling up users and instructing them on how to use the app, that sort of real time ability to transfer funds very quickly, anywhere, anytime, has sort of brought to the forefront this confidence, scam fraud, where people are calling up users and convincing them to make certain investments or to make deposits, or representing the bank themselves. And, you know, trying to do credential stuffing. And so a lot of that just happens so much more quickly. Now when I can talk to you on the phone and give you instructions on what to do while you’re typing in the app at the same time. So like that vector of attack is just something that fraudsters have gravitated towards with neobanks.

Whitney McDonald 3:53
Now, when it comes to prepping your operations, let’s talk through the bank side of things. What can what can you be doing to prep for this prep your systems prep your operations to combat these fraudsters?

Matt DeLauro 4:08
I think the gathering the richest amount of information on users and meeting them where they’re at in the customer journey is probably the most important thing to do. You know, historically, we would probably look at things like you know, in, you know, an email address when we’re onboarding and see if it’s deliverable. And the attacks are a lot more sophisticated today. And so, you know, we need to make sure that that email address is deliverable will maybe check the IP range also look at things like device information. That’s the real big paradigm shift is that in neobank, in almost all the activity is done on mobile. So like, if you’re not collecting very rich device information, Cookie hashes, device houses, all these kinds of things that are available on Android and iOS, then you probably don’t have the data points and the variables you need to be able to identify these fraud patterns and shut them off vulnerabilities will be found, right? But it’s really important to be able to react If you don’t have the data to be able to take action, then you’re not going to be able to react.

Whitney McDonald 5:05
Now, speaking of that data, the technology component, having those pieces in place to be monitoring what you need to be monitoring, maybe we can talk through the technology of see where that comes in, what your clients are looking to you for?

Matt DeLauro 5:22
Sure, I think it starts right away where most of the places we touch customers is when we onboard them. So if a neobank is onboarding a customer, we’re number one, trying to make the determination whether that’s a legitimate human being, right, and in many cases, Neo banks are not doing things like ID verification, so they need much more subtle cues that are far less expensive. The customer lifetime value associated with a user of a neobank is far less than a traditional bank, right? They don’t have all the loan products and the car financing and all these things to get to them. So most neobanks have trouble justifying doing like a hard ID verification check for everybody that comes on board the platform. So they have to look at like more subtle cues to be able to validate identity. So really starts right up front with the customer onboarding.

Whitney McDonald 6:06
Now, when it comes to what your clients are asking for, maybe you could give us an example or to some of your clients that do this, well work with you well, and and some of the successes that they’ve had with having some of this fraud monitoring in place, where it stood before, what they’re looking at now with having some of this technology in their back pocket to monitor fraud.

Matt DeLauro 6:33
Yeah, I mean, the people that are the best at that we work with some of the names you’d recognize, like revolute, or new bank, they number one, they have very good data science teams, right. And their data science teams aren’t just looking for like upsell opportunities and transactional like value out of the customer. But there they have components of their data science model that are focused on fraud and risk, right, and where they use us as they feed us into their model. And so we’re one of the layers that they use, with respect to doing login monitoring and event monitoring and transaction monitoring, and, you know, customer onboarding. And they’re looking to us for things that are very hard to get, you know, we provide a social relevancy score that’s associated with onboarding a new customer. So if you see an email address, we can tell you the longevity of it, we can tell you, you know, leading social media profiles where there may be an account associated with that email address, which is something that’s very difficult for a fraudster to replicate.

Whitney McDonald 7:30
Now, with using Seon, I know that you mentioned being API based, maybe you can give us a little bit of insight as to how long it would take to be up and running. What does that entail? How do your clients actually leverage this technology? And how quickly could you be up and running fighting fraud?

Matt DeLauro 7:48
Yeah, you know, with neobanks, it’s relatively straightforward. I think the fight with you know, traditional banks has always been access to the resources were times fraud and risk lives within the product and engineering like in the r&d team at a neobank. So, you know, there are oftentimes resources available. So we like to say we can move as fast as they can. But when you’re when you’re doing like very simple REST API calls and accepting like decisioning, from Seon, we find customers go live in as little as a week and incorporate us into their model or decisioning. So that’s just the value of being API. First is the integration is simple. It’s using standard protocols. Any web developer at any bank can sort of pick up see on and play around with it. We even offer a free trial of our application. And oftentimes, we get customers that implement it without us even being aware of it, and then come to us to cement a contract.

Whitney McDonald 8:40
Okay, great. Thank you. Now, being in in the fraud fight in the fraud game, of course, this year, we’ve seen technology evolve, vastly use of AI, fraud seems to be one of those major components, one of those major use cases where AI is fitting in, maybe you can kind of talk us through how the evolution of fraud fighting has progressed. And then we can kind of get into a more future look, but maybe first, you could just kind of set the scene of what you’ve seen, even in the past year, but maybe even beyond that, how fraudsters have evolved, but also how the Tech has evolved.

Matt DeLauro 9:16
Yeah, I think it’s with so much of our information being available on the internet. You know, we used to rely on things like network data to fight fraud, like, Oh, this is a fraudulent user. I’ve seen them some other place. And the relevancy of that network data is vastly like rapidly approaching zero, right? These are sophisticated attacks, mostly scripted, a lot of them are velocity based. So they’ll identify a security hole, either at a traditional bank or at a neobank. And then they’ll develop an attack that can take advantage of that, you know, 100 times 1000 times 5000 times within 30 seconds. And so having an understanding of the sort of velocity basis of an attack, sometimes using you know credential rules that are legitimate, you know, you can develop a lot of synthetic identities and have those consumed by a bot, and really take advantage of a financial institution for very serious losses within a very rapid amount of time. So this, this concept of being able to catch fraud later on, or identify it later is like, really, you need to be preventing fraud, not identifying it. And that’s, that’s really the trend is, you know, can you get assurance in a Manila, you know, sub second, you know, 500 millisecond or so response time when you’re about to proceed with a transaction for a customer?

Whitney McDonald 10:31
Yeah, absolutely. We hear all the time the the proactive approach rather than the reactive, of course, you you still have to have those those things in place when you are reacting. But getting ahead of that is something that’s key that we’ve definitely heard about. Forward, look here, where where’s this fraud tech, anti fraud tech going, I should say, What do you want to see? Or what are you working on at CNN that you’re excited about? Within the fraud landscape?

Matt DeLauro 11:01
Yeah, I think continuing to look at things that are real time and available, that’s publicly available information on the on the internet to validate identity, being able to provide neobanks with, you know, the confidence to be able to validate identity without like a lot of friction in the customer experience. So looking at, like always making big investments and performance and scalability on our side, and reducing response times. Because we know that we’re like a really intricate part of the customer journey. But, you know, add on the back end of it, when it comes to the fraud examination, and the things that do get flagged to like, you know, we’ve put it implemented a lot of really common sense machine learning. So the things that might have taken a fraud exam or a long time to do and then weren’t as scalable to implement when a Fraud Examiner identified it, you know, we’re looking to support that Fraud Examiner with a lot of machine learning capabilities, so that those patterns can get learned by the model. And then they can be more effective, and they can really stop those vulnerabilities. Because it’s yeah, it’s a never ending battle against the fraudster, they’re gonna find a security hole. And our job is to plug it as fast as we can, and then implement a series of gates, or defensive measures to make sure that that’s covered.

Whitney McDonald 12:11
Right, the technology gets stronger, and the fraudsters get more creative. It’s

Matt DeLauro 12:17
gone are the days where you’re gonna get like a poorly worded email with grammar mistakes in it from a Nigerian prince. Now it’s going to look exactly like an email from your bank. And it’s going to, you know, be very hard to identify some of these spear phishing attacks and things like that. The fraudsters just have tools at their disposal that are really highly scalable, and in some cases, more scalable than the financial institution. And really, you know, the message that we have that we’ve learned from a lot of our neobank customers is it’s really all about fraud prevention, right? It’s about instrumenting things at the very front end when you first onboard a customer and having things done in real time, because the velocity of the fraudster is just getting faster and faster every year.

Whitney McDonald 12:58
You’ve been listening to the buzz, a bank automation news podcast, please follow us on LinkedIn. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time, and be sure to visit us at Bank automation news.com For more automation news,

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October 26, 2023
Podcast: Broadridge Financial Services | Bank Automation News

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Financial institutions are implementing technology throughout the customer experience, including account opening, servicing and even transactions, but banks also need to know if clients are having problems navigating digital offerings.

That’s where engagement results, client monitoring and customer surveys come in, Debbie Miglaw, head of digital business development at Broadridge Financial Services, tells Bank Automation News on this episode of “The Buzz” podcast.

Banks can access client feedback by using technology to listen, she said, and they can use data to determine how clients are interacting with digital options.

Are clients dropping off at any point of digital account opening? Or is there friction in digital check depositing? Banks are already collecting metrics on their technology use, and they can use that data to measure whether the technology they have releases is successful, Miglaw said.

Listen as Broadridge’s Miglaw discusses how banks can improve the customer experience by leaning on data and insights.

Subscribe to The Buzz Podcast on  iTunes, Spotify, Google podcasts, or download the episode.

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October 10, 2023
Grasshopper adds to startup offerings | Bank Automation News

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Grasshopper Bank is looking to expand its support of the innovation economy with the launch of a new operating account intended for venture-backed startups.

Accelerator Checking, launched today, is “really focused on the small business or venture startups’ needs of a really useful product for managing their day-to-day cash flow,” Grasshopper Bank Chief Digital Officer Chris Tremont told Bank Automation News on “The Buzz” podcast.

Accelerator Checking can be opened in less than 10 minutes, offers free domestic ACH and wire transfers, bill-pay and check-deposit services, and digital invoicing tools, according to a Grasshopper release.

The $700 million bank will continue to build out the operating account to include access to venture debt, corporate credit cards and startup insurance, Tremont said.

In addition to the digital banking product, the bank is offering startups access to its network of venture capitalists, he said. “We have a lot of connections in the VC community that are always looking to meet new startups from an investment standpoint, so we’re going to start to cultivate our network and make referrals.”

Since the banking crisis earlier this year, New York City-based Grasshopper has shifted its priorities to recognize that “every startup needs a good depository solution and a place for managing their money and their payment infrastructure,” Tremont said.

The bank was originally founded “to be working in the venture community and to be working with startups, so it’s not a brand-new segment for us,” he said. However, “the narrative has changed over the last six months since the banking crisis happened.”

Over the last 12 months, the bank has rebuilt its technology infrastructure to better support this [startup] client base, he said.

Listen as Grasshopper’s Tremont discusses the digital bank’s latest solution and its continued effort to support startup banking.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:06
Hello and welcome to The Buzz a bank automation news podcast. My name is Whitney McDonald and I’m the editor of bank automation News. Today is October 3 2023. Joining me to discuss grasshoppers latest innovation to launch accelerator checking is Chief Digital Officer at the bank, Chris Tremont. Throughout his career, he spent time at radius bank and Key Bank before joining grasshopper in 2021. He’s also been a speaker at past bank automation summits about his efforts at grasshopper. Chris, thanks for being here.Chris Tremont 0:38
Hi, I’m Chris Tremont, Chief Digital Officer for grasshopper bank. I joined the company about two years ago. Prior to that I served in a similar capacity for 12 or 13 years at radius bank based out in Boston, a little bit about grasshopper bank. We’re a digital only bank headquartered in New York that’s focused on serving the business and innovation economy. And we do that 100% digitally across the United States. And we do it through a combination of really solid product, digital resources and really passionate people toWhitney McDonald 1:17
Great, well, thanks so much for joining us for the buzz. I’d like to get right into your latest innovation that you’ve been working on at grasshopper called the accelerator checking, can you talk me through what you guys are solving for and what you’re announcing?

Chris Tremont 1:32
Sure, we’re really excited about this. And I think as as maybe a segue talk a little bit about where we’ve come over the last couple of years. So grasshopper itself was founded in 2019. So still young, by Banking Terms, only about four years old. A number of new folks joined the company about two years ago. And we kept the mission intact. And the mission of the company is to serve the was the business and innovation economy. And the way that started with me was really working with venture capital firms, private equity firms and the companies that they invest in. And so we’ve kept that mission intact. But we’ve kind of broaden the vision of who we’re serving. So we’re still working with that line of business with within the venture fund world. But we’ve layered in a couple of other areas that includes some new lending products like working in the SBA and commercial real estate space, as well as on the deposit gathering side working with fintechs through banking as a service, and a little bit more directly with small and medium sized businesses. So SMBs. And so we’ve spent really like the last 18 months or so layering in those new components. And as you can imagine, part of that was building out a new team, as well as new technology, infrastructure. And so where we started on the deposit gathering side was really working with within the small business community, and launching a digital checking account product for them. We’ve seen a lot of good success over the last 14 or 15 months since that’s been launched. And now today, we’re really excited for sort of the next iteration or the next segment that we’re going deeper into serving, leveraging our digital technology. And that’s working more with venture backed startups. And so the product itself, we’re calling the accelerator checking, but from a macro view, it’s much broader than that than just an operating account. But starting there, it’s really focused on the small business or the venture startups needs of a really useful product for managing their day to day cash flow, money in money out. So it starts with the product on the deposit side and making it really useful for the startup to manage their day to day business. I think taking another step back, what we did was we said, We got to make it really easy to get the account open. So you can apply for the account digitally from any device and get an account approved and funded and under 10 minutes. So we think that’s a really nice feature of the product. The product itself, like I mentioned, has a lot of useful features and integrations from a money movement standpoint, as you would imagine, wires and ACH things like that source and table stakes products. But then we also have integrations with companies like auto books for digital payables and receivables, which we think is a really powerful tool. We work with a company called MX to allow for some better budgeting and cash flow management tools. So just to give a flavor of Like what’s inside that digital banking product, coupled with this kind of what we call a marketplace or an ecosystem. So what we believe is grasshopper is really great at providing a solid digital banking experience and a really good operating and payment accounts. But there’s more to startups financial needs than just that. And so we’ve layered in some best of breed called financial technology players to help surround our offering and make it stronger. And so some of the things that we’ll roll out over time starting this week, include access to things like venture debt, corporate credit cards, we have a partnership with ramp doing that startup insurance is important. So that’s going to be in there. And then just through our work with with our various teams in the venture in the FinTech space, we have a lot of connections into the VC community that are always looking to meet new startups from an investment standpoint. So we’re going to start to kind of cultivate our network and make referrals on either end right with the startup that might be looking for funding. We’re going to make those intros to some friends of ours on on the VC side,

Whitney McDonald 6:22
setting up getting into that network and gaining those deposits. Can you maybe talk through the gap that you’re able to fill here? Of course, we know that everything happened in the spring, and startups are looking to kind of change where they’re where they’re banking?

Chris Tremont 6:40
Yeah, it certainly has been an interesting, six or seven months, I suppose in in the banking industry, for sure. And so for us, the timing is is unique in that it’s twofold. One is, yes, we’ve seen some of the financial services providers that have worked with the startup community for many years, some of them are now gone, right, or they’ve been absorbed into larger organizations. And we’ll see where, where that strategy goes for those companies down the road. So there is a bit of a gap. Certainly that’s opened up for, for the startup community. At the same time, I would say as to a previous comment, grasshopper was was founded this way to be working in the venture community and to be working with startups. So it’s not a brand new segment for us. I would say, though, that maybe the narrative has changed over the last six months since the banking crisis happened, where maybe the way we went at it, at the beginning was, it was more about leading with the loan, or the the lending or the debt solution. And venture debt can be hard. Like we’ve, we’ve learned that we knew it, but like we’ve seen seeing this play out over the last few months and, and so not every bank is able to do it. And there just aren’t that many places for a startup to go to find it. And so that’s kind of maybe where we started. And now the narrative has changed a little bit more around every startup needs a good depository solution and a place for managing their money and their their payment infrastructure and things like that. And so I think like the macro level, you know, the industry changes have caused a gap. And at the same time internally for us, we’ve kind of repositioned our offering to be leading with the Depository relationship versus the loan, and have taken the time over the last 12 plus months to rebuild our technology infrastructure to better support this client base. And so that’s why we’re coming out now. To say we’re sort of, you know, with a new product, and serving this market, though, it’s not brand new to us, but there’s certainly a need for it and an opportunity, and something that we’ve been working on for many months, kind of behind the scenes anyways. And so it’s coming together, we believe at a nice time to be serving this market.

Whitney McDonald 9:13
Now, as you’ve kind of shifted that approach to gaining deposits and worked through this project, is this something that you something you guys have built in house or partnered on building the technology itself? Or is this something that was all a grasshopper initiative?

Chris Tremont 9:30
Yeah, we’re inside the company. We’re huge believers. If you think about a lot of times companies look at the buy build or partnership models, and we are strong believers in the partnership model. And so helping to build out our technology infrastructure, we consider a lot of the financial technology firms that we work with as partners of ours. And so we have a really, a really smart Are and dedicated and innovative product and data and engineering team inside the company that are kind of leading the strategy and helping to execute the vision. And then we partnered with some best of breed partners or companies out there to make this happen. And so to elaborate on that a little bit, like I mentioned earlier, we can open a startup depository account in 10 Minutes or Less without any paper, fully digital, well to be able to do that it takes our team, but we also partner with a company called mantle for the account opening. Behind the scenes, we work with a company called alloy for the decisioning on the consumer and the business itself and some other players that funnel into the aloe ecosystem to help make that approval decision. Once the accounts opened, we use a company called Narumi. For the online and mobile banking, user interface, they helped power that. And so that’s just a few examples of sort of this partnership model that we’ve used to build the technology to provide a really great digital banking experience for startups.

Whitney McDonald 11:16
Great. Yeah, I mean, a lot of those names that you just mentioned are something that that we’ve definitely covered in the past, ramp and mantle standout for sure. As you kind of launched this accelerator checking, you talk through kind of taking this different approach and to gaining deposits, kind of from a broader, bigger picture point of view, maybe we could just talk through the importance of financial institutions, gaining new deposits, looking for those new avenues to gain deposits and gain strength, getting those sticky deposits, maybe we could just talk through the importance of that that our audience can take away?

Chris Tremont 11:55
Yeah, that’s a great question. And a great, maybe issue or topic that was highlighted back in March as as we went through some of those issues. I think one topic it highlights is the importance of diversification. And in sort of how you’re building out your balance sheet, whether it’s loans, we’re talking about deposits today, so we can focus on that. But being diverse in or not single threaded or monoline in terms of who you serve, I believe is important. You know, every bank has a different strategy. But having some diversification there is something we as a company have always believed strongly in. So I think serving a wider audience is, is important. The second is you think about how rates have changed over the last 12 to 18 months. And certainly we could talk about maybe where we think they’re going over the next 1218 months as well, but

Speaker 2 12:59
at a much more elevated level now in September of 23, than where we were in February of 22. And I said this to folks along the way is, you know, for a while it was like deposit gathering wasn’t always this easy, you know, we had this time period where rates were low and deposits were flowing into banks, and they were sticking around and and we knew it wasn’t going to be that way all the time. And so I think outside of the diversification of the client base, having a strategy that’s probably a little bit less reliant on rate, though rate is important and is a larger part of the conversation, but really driven by relationship. And I That’s easy to say. But what I mean by that is sort of the you know, when you get into serving different clients segments, and what they’re looking for, some are less, you know, rate dependent, or rate demanding, and will move less, you know, when when rates change, or they’re chasing, chasing rate. And so I do think having a strategy, that is where you step back and say I’m gonna skate to where the puck is going in terms of serving growing client bases. In our case, we’ve said how do they want to interact with us? And we’ve said, digitally is the place we want to be. So like, how are you acquiring these customers? The products that you’re putting out there where rate is a component, but more about the relationship and helping in our case, let’s say it’s a business owner or a startup founder, really managing their cash and thinking through how am I getting paid? How am I paying my vendors? Do I have a banker I can call if I need to? Only if I need to, let’s say you know the self service model here

Chris Tremont 14:59
and Some other connections to within the industry, whether it be those VC referrals or access to other products, I think the point would be is providing more value than just talking about an interest rate is really important.

Whitney McDonald 15:16
On that know, kind of some self service options, how it works and what it presents? Could you maybe walk me through how a client or a startup would actually leverage accelerator checking?

Speaker 2 15:30
Sure. I mean, I think it starts with if you’re thinking about making a move, the ease of getting started with us, is unparalleled in the industry to say that you could open an account and be funded in less than 10 minutes, you know, I think is is fairly industry leading, we’re not the only ones that can do it, but like to get up and running fast. And to not have to walk into a bank branch with a lot of paperwork and spend the afternoon trying to get your account open, whether it’s a day or weeks, I don’t know. So I think getting up and running is important. And then from there, some of the tools that we’ve set up, like I mentioned, the ability to

Chris Tremont 16:15
set up invoices to get send out invoices to get paid, or using our bill payment services, like wire transfers, ACH bill pay, to pay vendors to pay employees, if you’ve got payroll, I mean, you could be up and running doing that in the first day with us. We are layering in some other technology to think about the financing side of things and the debt side of things through some partners as well. So if you’re actively seeking venture debt, or maybe you’re a company, a startup in the E commerce space, we’ve got some partnerships in the works, that will help maybe with some financing of receivables to improve cash flow in the short term.

Speaker 2 17:03
So there’s a couple of the ways connections into like we mentioned ramp, if you’re looking for a corporate credit card, the connection can be made there quite seamlessly. And actually the ramp transactions up here in the grasshopper experience. So it’s kind of this holistic approach. So I think like, broadly speaking, is like you can be up and running quickly. And you can leverage tools that

Chris Tremont 17:29
help you operate your business out of the gate right away.

Whitney McDonald 17:34
Now I know that you kind of gave a little bit of insight into something that you guys are working on. Anything else grasshopper has in the pipeline right now, either related to accelerator checking, or is this tool going to be something that you monitor and update often just kind of wondering for a little look ahead as to what grasshopper is working on?

Chris Tremont 17:54
Yeah, that’s a great question. And so we’re really excited to be focused here on this segment of working with with startups. And we’re going to continue to go deeper with the accelerator checking product, and the marketplace offerings that we have. So we hope to expand that out into services that startups need. This could be, you know, tax prep and accounting, things like that. So we’re gonna continue to improve on that experience. But I’d say more broadly, is, we’re a company that serves the business and innovation economy. So startups are one segment of it. Small and medium sized businesses are another large segment that we love, and we’ve been serving for a while. And there might be a couple other niches that we layer in down the road. But thinking about those two, and probably a third would be financial technology, or FinTech companies are three of the areas that we’re working on closely and continue to develop for. So I would call out. One is we’re working on our lending solutions in the small and medium sized business space. So that can be on and off balance sheet opportunities. So some referral opportunities or small medium sized businesses looking for a lending solution for us. We’re working on digitizing that process, more to come there probably in the next couple of months. And then we continue to be a big proponent of the FinTech banking as a service, embedded finance space. And so we’ve been a player in that for the last 12 or 18 months. We continue to work with our partner, Treasury prime and San Francisco to bring on quality fintechs that are looking to use our API’s and some really creative and innovative ways in the depository and payment space. So we’re going deeper, they’re getting pushed probably more around on real time payments and fed now, functionality, as you would imagine, in the FinTech world, so I think like that’s going to be our focus in that for that group over the next six to 12 months as well.

Whitney McDonald 20:16
You’ve been listening to the buzz, a bank automation news podcast, please follow us on LinkedIn. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time and be sure to visit us at Bank automation news.com For more automation news,

Transcribed by https://otter.ai

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Whitney McDonald

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October 3, 2023
Podcast: Data analytics, automation | Bank Automation News

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Financial institutions can look to data analytics technology to better understand customer sentiment so they can drive organizational change.

Financial institutions are looking to utilize all available unstructured data from calls, emails and chat capabilities to understand customer needs, Global Head of Financial Services at Qualtrics Dmitry Binkevich tells Bank Automation News on this episode of “The Buzz” podcast.

The data integration platform gives financial institutions that insight into what clients need, he said.

For example, $5.3 billion Connexus Credit Union started using Qualtrics’ platform roughly five years ago to make decisions based on specific customer feedback, Craig Stancher, director of member experience at the Wausau, Wisc.-based credit union, told BAN.

“We needed a solution in place that would help us better understand what’s working and what’s maybe not working as well,” he added. Through Qualtrics, the credit union was able to implement automated customer surveys to provide immediate feedback from clients based on member experience.

Prior to Qualtrics, customer surveys were a manual process, with the platform in place the credit union is able to run six automated surveys each day saving the bank eight hours per day of work — equivalent to that of a full-time employee, Stancher said.

Qualtrics also worked with M&T Bank during its $7.6 billion acquisition of People’s United Financial to help M&T better understand client needs during the integration, Binkevich said. Additionally, the tech company helped insurance company Nationwide analyze contact center interactions to improve call quality.

Listen as Qualtric’s Binkevich discusses how FIs can use technology to drive change within their organizations based on applicable customer data.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:03
Hello and welcome to The Buzz, a bank automation news podcast. My name is Whitney McDonald and I’m the editor of bank automation News. Today is September 26 2023. Joining me to discuss data collection to make performance driven decisions is Dmitry Binkevich of Qualtrics. Throughout his career, Dimitri spent time at banks, including Citi, and Barclays focused on business development and strategy. Please join me in welcoming Dimitri.Dmitry Binkevich 0:29
Very nice to be here Dmitry Binkevich, I lead the financial services industry practice here at Qualtrics. Globally, have been with the company for coming up on two years. Prior to that, I spent my entire career close to 20 years in financial services in a variety of roles both within financial services players, like Barclays and city and insurance companies, as well as as an advisor, as a consultant as an investment banker, serving the industry. So my approach to the industry as well as to experience management overall, generally begins with the business problems, right? What business problems can we help our customers solve? And at the end of the day, how can we make them either make more money, or spend less money. So generally, our objective is help our customers move their financial and operational outcomes, using experience and everything around it as a lever. Right, which is, which is a nice segue into into Qualtrics. And in general, the Qualtrics position in the financial services industry, our goal at Qualtrics is to make experience a little bit more human to make business a little bit more human. And so that’s what we help companies do. We help companies solicit feedback, which is, you know, your typical survey, right? When you think experience management, probably surveys, the first thing that comes to mind. But then we also help companies ensure that they’re listening into the conversations that are happening with and about the company, right? So whether it’s a phone call, or an email, or a chat or social media, right, there’s a variety of sources that customers can try to can can use to try to connect with a company or just opine about the company something like 85 to 90% of all customer feedback, data is what we call in, in the lingo unstructured, right. So it is not a survey data set, it is just a customer talking or posting or whatnot. And if the if our clients, the financial services, businesses are not listening to that, then they’re missing kind of, you know, nine tenths of all of the possible information. So Qualtrics serves the financial services industry top to bottom right, we cover all of the verticals, we serve over 1300 financial services clients, with, you know, probably 90 out of the top 100 financial institutions globally, right. So very, very rich data set, very rich client list, and they partner with us, because at the end of the day, we help them deliver business results, right? It definitely begins with customer satisfaction, right? But then we can help them deliver better business results, right customer satisfaction tends to result for example, in lower churn, higher cross sell higher revenue, other parts of our platform can help our customers lower cost, right lower cost of serve, whether it’s you know, increasing the amount of interactions that take place via, for example, an automated chatbot or reducing the number of calls into the contact center where a customer is actually doing things by themselves on digital. And finally, we help our customers manage their regulatory risk visa vie sort of complaints, obligations that are prevalent for banks in virtually every jurisdiction that we serve. In the US, you’ve got the CFPB as an example, in other countries, you’ve got the central banks, or security regulators. So we help our customers understand manage, and action, all of that. But our engagement and we’ll talk about you know, sort of the technology and the software later on in this conversation. We kind of it is our thesis that in order for our software to bring value, you don’t just need just sort of listen and under listen, understand, you need to act. And so when we work with customers, we partner with them to make sure that the entire organization is aligned on the value of what they’re doing that it is not just, you know, a CX team, out there in the corner, kind of doing their thing, you really do need the buy in of the entire organization in order to get somebody to do something differently. Our goal is to use the information and the insight that our platform brings to get our customers to do something differently to positively impact their business. So that’s a little bit about, you know, what we do and how we think about working with clients in the financial services industry. You

Whitney McDonald 5:44
know, I know you talked a little bit, you started getting into a little bit about the quantity of data that financial institutions have you talked through the ability to have that insight into that unstructured data in order to make those business decisions. Maybe you can set the scene here a little bit further about really the need for automating that approach to data to both increase the operation or enhance the operation side, improve the customer satisfaction ratings. Can you maybe talk us through a little bit about how Qualtrics plays a role in automating that data and the importance of having that type of solution to get into all of this robust information that fit is half?

Dmitry Binkevich 6:27
Yeah, absolutely. I mean, I think in order to do that, though, let’s think a little bit about how financial services experience and let’s begin on the consumer side, because that’s the easiest way to sort of frame it, how the Financial Services experience has changed. Right? If you go back, I mean, at this point, like 30, you know, even 30 years ago, right? Most of the Financial Services experiences that you had were in person, right? You went to a bank branch? Yes, you interacted with an ATM, but that’s a pretty, you know, inanimate object. But you talk to a teller, you talk to an insurance agent, right? If you needed something, you fax things, and you called right, so they were very big, they were person to person experiences, for the most part. If we fast forward to now, a lot of the experiences that we’ve got our, you know, person to person still exists. But I would venture to say that the majority of experiences in retail financial services are what I would call person to machine. Right. And so the person goes on the website, the majority of the transaction happens on the website. And so these journeys have fundamentally evolved and changed. And so has the expectations. So have the expectations of the consumers, right? consumer expectations are framed, but what by what they experienced in other sections of their lives, right. It’s the Google’s the Facebook’s, the Amazons, the Twitter’s, which is very personalized experiences, right? experiences that are not just I mean, it’s not even just personally, it’s almost like no me experience their predictive experiences, they know what I want, before I sort of realized that I want it, right. The gratification is instant, right? Because you know, you get the news, you click a button, et cetera. And it’s sort of very, very precise. And so for the financial institutions, to be able to deliver an experience like that, you really need a deep, deep understanding of your consumer desires, preferences, you know, thoughts and opinions. And in order to do that, you actually need a platform that listens in appropriate ways in every single interaction, where there’s person to person, person to machine and any kind of way, and not only listens, but sort of ties it all together, because the consumer thinks they’re interacting with the bank, while they might be interacting in reality, with a bank onboarding department, with the application department, with the service department, and then with the fulfillment department. But in order to succeed, and I would venture that every one of our clients is in the experience business, even though they think they are in banking, insurance and wealth management businesses. Right, in order to deliver those experiences, they need to understand consumer journeys, they may need to line up the listening posts in an appropriate way. For some it might be a survey, right? There’s always a place for solicited feedback. But if I just spent an hour on the phone, as an example, explaining in painful detail to my insurance company, what exactly happened in my accident? If somebody sends me a survey and says, Hey, how did that go? I’d be just like, well, I just spent an hour telling you exactly how that went. So please go ahead and listen to that. Right? Or if I’m on the website, and I’m frustrated, right. I sort of expect the company to be able to say, hey, looks like you’re frustrated. Maybe we didn’t do a great job, you know, building this page, how can we help do. And so what the Qualtrics platform does, it allows our clients to position listening posts along key journey nodes in the mode that is most appropriate for that journey for that node. And for that customer, structured, unstructured, Inferred behavioral, right. So everything from survey to call analytics to click analytics, right to session recording. And so, and on the back end, we ended up pulling all of that together and helping customers, our customers make sense of it. Because the important thing and experience management is not just the what, which is what I just described, it’s also the so what, right, as a, as a manager, as a leader in a financial services organization, if I’m just looking at like information or data, it’s overwhelming, right? What I really need is a needle in the haystack, so that I can figure out where to spend my limited resources to make sure that the results that I care about are moved. And that’s where the sort of the omni channel platform with a single back end, like Qualtrics, irrespective of sources really comes into its own.

Whitney McDonald 11:18
Now getting into the how I know that you said you’re linking into these different areas of the bank and making sure that you’re you have that tech in place, what does that look like? How do you really get into the the nitty gritty of the data on a tech on the tech side?

Dmitry Binkevich 11:37
Well, I mean, if you think about Reg, in any, if we take a typical bank, right, there’s a marketing tech stack, and like a marketing team, there’s an onboarding system and an onboarding team service system and a service team. And very often, these systems actually don’t Doctor each other, right? Banks are, and I’m going to use bank so as the most obvious example, but this applies to insurance and wealth managers and other customers that we serve. But companies typically don’t have these talking to each other very effectively. And so when we get into journey design, like you said, we really needed to figure out a way how do we plug into every single text, I can actually bring these things together. So Qualtrics is a SASS platform, right, from a technology perspective. And so the way we link into every single tech stack is via API’s in general, right, so the integration is generally quite easy. And we’ve got a series of over 150 pre built integrations with the most commonly used systems, you know, like a sales force or a dynamics on the CRM side, you know, Pegasystems, for example, you know, for actioning, you know, workday, for example, for ServiceNow, right for human resources, and ticketing. So, we’ve thought long and hard about how to make it as seamless as possible for Qualtrics, to be able to link into each individual ecosystem, not just to pull the data out right to be able to synthesize it, because we actually need the operational datasets to be able to contextualize the experiences, but also in order to help actioning. Right, if you think about it, not everybody at the enterprise needs Qualtrics on their desktop, right? The managers do, the leaders do. But if somebody’s working, for example, in Salesforce, and sort of, or in ServiceNow, in sort of processing tickets, we can ping our, we can trigger an alert or a ticket, for example, into ServiceNow, or Salesforce. So there’s no swivel chair for the frontline employees, right? They sit in the system that they’re in, they sort of are told what to do they go do it, they close out the ticket that goes back into the Qualtrics ecosystem for analysis. For management for leaders, we’ve got role based dashboards, right with the views that are specific to those roles and focused on the sowhat. Right, that, that those people need. But in general, we integrate via API’s. We have a deep, deep pre built set of integrations. And we’re always building more because we know that the ease of integration is one of the key hoops that we have to jump through if we’re gonna get our platform, you know, into our clients. tech stack.

Whitney McDonald 14:36
Yeah, thanks for talking through that integration. That’s really helpful. Another piece of the puzzle that you mentioned was the ability to predict right so you talked through Of course I’m I’m frustrated Didn’t you see throughout that transaction that I was frustrated? So talking through those predictive and analytics and I mean when you’re talking through anything, but especially bank to technology right now, you can’t really ignore AI. Where does artificial intelligence come in? Maybe you could talk to me through or talk through your use of AI here to benefit those financial institutions really get those predictive analytics into play?

Dmitry Binkevich 15:15
Sure, absolutely. The great thing is, is that Qualtrics has been on the AI or the machine learning bandwagon, you know, for the better part of the last decade and a half. Right? So many of our analytic capabilities have been enabled by AI, one of the, you know, specific ones, when we analyze unstructured data, for example, it’s a combination of sort of language models, but also AI, especially when it comes to what we call enrichments. Right? So if you think of the way that if we analyze a phone conversation, for example, or a phone conversation transcript, there’s a couple of layers of this analysis. First of all, what is that person actually saying in English? Right? So we have a natural language model that helps us or not an English actually, we’ve got, I think, over 20 languages that we sort of natively, natively ingest, but let’s say the conversation is in English. What is that person saying? in English? Right? What is the meaning of the words, including all of the nuances, right, when somebody says that, you know, the word sick, for example, like something is sick means very different, something very different from you know, I’m feeling sick, right, and you kind of need to catch those nuances. If you’re going to accurately understand what the person is saying, then you need to conceptualize it in context of the business, right. So if the person is going through banking, onboarding, there’s actually a very specific set of terms and banking, onboarding, right, that you need to understand in order to be able to deeply sort of get in order to get deep insight into why they’re having an issue. And finally, and this is really where the a lot of the AI investment comes in. We do emotion, intent and effort enrichments. So from the text, our AI platform is able to understand, how is this person feeling? Right? Are they angry? Are they confused? Right? Are they very happy? Are they very unhappy? Right? There’s a series of there’s a series of emotions that we’re able to ascribe using our AI engine, based on sort of the relative positioning of the words next to each other, and you know, et cetera. How hard was this to a person? Right? Like, as an example, if they say that your website is ugly? It’s definitely not a great statement. But it doesn’t indicate that they’re having a hard time. It just, you know, they find your website, aesthetically unpleasing. Right. And so, and then intent, what is this person trying to do? And when our clients see the output, it’s not just the understanding, right? Just the what, but also the overlay of how is this client feeling? What are they trying to do. And that is enormously helpful in creating the, what I call Nomi experiences. Because if I had an experience where I was really angry, in the contact center on one of the calls, or I typed in a very angry comment into a web survey, the next interaction that I have with this company, especially given the the single back end, what we call the customer ID, or customer directory, where every single experience gets written on to your customer record. So on my record, there would be, you know, what I said, how I felt, and a suggestion about what the person should do what the CSR should do about it, if I call next. So the next time I call, you know, the conversation doesn’t begin with, hey, please tell me your problem. It begins with, I see that you already spoke to us. And we’re very sorry, that we were not able to deliver the experience that you’ve expected, you know, I you know, haven’t evolved my management to be able to help you now, et cetera, et cetera. So which is as you can appreciate, is a world of difference in terms of how I feel about the brand, how likely I am to recommend the brand, how likely I am to buy from them again. Right? So that is just one small example of how we use AI inside of our platform, the other the other thing and I might be jumping ahead. There’s a lot of talk about AI and generative AI specifically to just sort of understand right understand and respond. Which to my earlier comment is really the what Leia, right, like, what is this person saying? How should I respond? The other way that we’re using AI is actually to try to get to the so what? Because in response to sort of this overwhelm of data, right, because every single conversation, every single thought is now sort of being analyzed, we’re investing in a couple of areas that will help the teams do their job better. And that is actually one big theme that we see in our application of AI, we’re not looking to replace teams, right? We’re looking to augment what these teams can do, right? Make them far more productive. So we’re looking to invest in summarization, right. So really be able to whether it’s video feedback, audio feedback, type, feedback, etc. Quick summary of what’s been said, Read the TLDR, so to speak, and tech speak. The second one is interactive analysis. And that is really cool. A lot of our dashboards right now are just like any dashboards, their data and they’re thoughtfully laid out, they will lead one to the conclusion of what’s important, what to do about it, etc. But we’re building capabilities that, and these are going to be released soon, that will enable you to basically type, Hey, what is the key theme in this data, right and have the AI on the background, do the analysis and give you sort of a thought of what you should pay attention to, right? If I care about customer churn, which parts of this data set, should I pay attention to right and have it. So it’s almost like having a very, very, very able assistant, that can help you with a lot of the drudgery. And then finally, semantic search, which is, and this is true for a lot of our research customers, people run project research projects, through the years and over multiple business lines. And often the left hand does not know what the right hand is doing. And so all of a sudden, you’re able to type in like, Hey, have we ever researched the propensity of, I don’t know, auto insurance customers to churn during price rises? And if the answer is yes, you will actually have that. Right. So imagine, like this, like having a magic library? It’s like, it’s almost like Hogwarts, right? Like you type in a query and sort of a magical answer comes out. So those are some of the forward looking AI applications that we’re working through.

Whitney McDonald 22:35
Yeah, that’s really exciting. And thanks so much for sharing what you guys are kind of looking through and having the works there. One thing I wanted to be sure to touch on was Qualtrics. In action, and example of a financial institution that you work with. That’s that’s benefiting from the technology and kind of talk me through where and how that’s all that’s all progressing?

Dmitry Binkevich 23:00
Yeah, no, absolutely. I would love to, I’ll talk you through with your permission. I’ll talk you through a couple one example. And there was a really interesting example of what we call cross exam, which is, you know, Qualtrics, obviously, does the customer experience employee experience, you know, brand experience experience across the entire 360 of the work. And for one of our customers for, for m&t Bank, we deployed both the CX, which is customer experience in E ex employee experience, and as they were going through the integration, so they bought people’s United Bank not that long ago. And bank integrations are fraught, in general, right, because they tend to lead to branch closures, they tend to lead to customer attrition, because it’s very difficult for customers to, you know, change, branches, interface, people, etc. And so what what m&t was able to do is, they were actually able to pull out drivers, I can speak to exactly what the drivers are, because that’s proprietary, but they were able to, to analyze e x and CX information jointly, right, and make sure that and what they found on some level intuitive, but that the satisfaction of the employees and the branches on how the employees felt about their job, their training, their environment, was very much related to how customers felt right about their experience with their new sort of owner with MMT. And so using that insight MMT was able to deliver, you know, targeted training targeted resources on both sides of that equation, right, both the employee side to make sure that they’re trained, enabled, rested, appreciated, etc. And on the customer side of that equation to make sure Have they had the information to make sure they have the extra help to make sure they had sort of an extra reach out to make them feel welcome when they were peoples United customers. So that was an amazing story of helping the bank really go through, I believe it may have been their biggest acquisition up to this point. And then another one we worked with, we worked with nationwide, a Nationwide Insurance Company to, to do sort of analytics of all of their data, including calls and what they were doing, it was super interesting. They were analyzing each call that came into the contact center using the platform that I just described. But not only that, they were actually scoring it on their bespoke rubric, right, they had a quality threshold that they sort of decided that every single interaction with nationwide should be of a certain quality. And so every call was analyzed and scored. Right, and based on the proprietary rubric, and what they did when the calls were not sort of up to par is fascinating. They call it proactive service recovery, they actually call the person back. And they say, Hey, we’re very sorry that you did not get the level of experience that you expect from nationwide, we’re committed to making it better. Let us work with you to make sure that your nationwide experience is outstanding. Right. So really, both from a from an experience perspective, right, you could think of an impact of that on something like an NPS on something like a renewal on something like churn. So those are two two really cool examples. I think that you know of how we work with customers and how we drive value.

Whitney McDonald 27:00
You’ve been listening to the buzz, a bank automation news podcast, please follow us on LinkedIn. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time, and be sure to visit us at Bank automation news.com For more automation news,

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September 26, 2023
Podcast: Archway Software | Bank Automation News

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Financial institutions must determine where they can apply AI within their operations to stay competitive with other players using AI for predictive analytics and call centers.

If one bank is using AI to serve clients and another is waiting for a crisis to occur to implement AI, clients will naturally gravitate toward the more proactive institution, Dustin Hubbard, president at Archway Software, tells Bank Automation News on this episode of “The Buzz” podcast.

“Banks that don’t apply AI are going to start having their margins squeezed a lot more than banks that are actually effectively using [AI],” he said.

For example, WaFd Bank replaced its entire call center stack and inserted conversational AI at the start of every call, Hubbard said. This investment in technology is translating to higher customer satisfaction levels, according to the bank’s August Investor Presentation.

Listen as Hubbard discusses AI use cases, maintaining competitiveness in the space and the future of AI in finance.

Join Bank Automation News for the upcoming webinar, Global Ideas for Better Banking AI, on Thursday, Sept. 14, at 11 a.m. ET.  For more information on this free webinar and to register, click here.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:05
Hello and welcome to The Buzz a bank automation news podcast. My name is Whitney McDonald and I’m the editor of bank automation News. Today is September 5 2023. Joining me to discuss AI use cases implementing the technology with safety and compliance in place. And a forward look to Predictive analytics is Dustin Hubbard, president of digital innovation provider archway software. Dustin has spent his career in tech and most recently served as the Chief Technology Officer at Washington federal bank before moving into FinTech join me in welcoming Dustin,Dustin Hubbard 0:35
Hi Whitney great to be on the podcast today. Thank you so much. I’m Dustin, the President and CTO of Archway Software. Simply put our choice of SaaS company. And we serve financial institutions looking to increase their revenue, their reach, and their relationships through digital transformation. We do this by providing world class products deployed on our enterprise grade architecture that may Nabal these banks and credit unions to succeed and what’s really become a highly competitive industry. I spent my entire career in tech spending 15 years at Microsoft, where I ran a lot of software teams and and products. Maybe the one most notable is the Snipping Tool, which is in every Windows SKU ship, that was actually a product I worked on when I was young in my career. I went on to help found an insurer tech company that was eventually sold to a fortune 300 insurance carrier. And then I was a CTO at Seattle regional bank, before I became the president of archway software. So that’s a little bit about my background.Whitney McDonald 1:46
Great. Well, thank you for being here. Of course, we’re here to talk about all things AI. Let’s kick things off by setting the scene here with AI today, of course, we want to get into the future look and where it’s headed. But let’s take a step back and talk through AI today, I was hoping you could talk through some real world examples of how AI is being used within finance today.

Dustin Hubbard 2:08
Sure, I’m so glad we’re talking about AI because not only is it on everyone’s mind, but it’s greatly misunderstood. And like any new technology, it’s disruptions can have positive and negative implications. So it’s important to think of use cases that aren’t going to give your compliance team a total heart attack. So as it relates to AI and finance, it mostly tends to fall into three buckets. Today, you have fraud detection, you’ve got virtual assistants, or chatbots. And more and more, you’re starting to see things around marketing and cross selling. So far to look in maybe a little bit deeper on, let’s say, chatbots, because that’s the one that I think is most visible to people in something that’s relatable. The virtual assistants our program to answer common questions, is designed to obviously improved self help, but also reduces the burden on the contact centers. That’s why businesses are interested in them. But as we all know, these are not all created equally, and how a customer feels about chatbots. And virtual assistants vary a lot. And the reason is, because a lot of these actually aren’t using AI at all. So a lot of the early chat bots are effectively decision trees, right? You’re answering a question that you know, the person is going to ask with a canned response. And those examples, typically, we don’t answer the question correctly, or you haven’t predicted what the question is going to be the bots like, I have no idea what you’re talking about. Please rephrase. And then the customer gets frustrated. But the chatbots using actual AI models underneath of them are becoming much more human like in their experience, which makes a dialogue between the bot and the human feel much more natural, and also is far less likely to get stumped with questions. So I think that’s a different kind of a differentiating component of how Chatbot is evolving. Now, the one use case I didn’t mentioned underwriting, and that’s largely because of concerns and bias modeling. So regulations around adverse lending is a really serious thing for financial institutions. And that’s a serious issue if they’re humans making underwriting decisions and a serious issue, if a bot or an AI system is making those decisions. So typically, I think even though underwriting is a use case, in AI for financial institutions, you’re not seeing it applied very much because of the concern that the the model could be biased in that actually probably complained to the heaviest regulatory scrutiny.

Whitney McDonald 4:44
Now, you mentioned chatbots, you mentioned decisioning. Of course, AI, even just in the past couple of months has come a really long way. And it seems like it’s changing almost daily. Now. How can a financial institution approach implementing this new tool technology like they’ve implemented tech in the past?

Dustin Hubbard 5:03
Yeah, sure. FIS know that AI is going to become a more and more critical part of their underlying bank operations. I think that’s a certainty. But similar to cloud transformation, there’s a lot of concerns with risk, there’s a lot of concerns with in house expertise and knowledge on how to do it, how to deploy it. In fact, it’s hard to believe that AWS has been around for nearly 20 years already. Yet, banks are still relatively early in their overall cloud transformation, compared to a lot of the other industries. But the one difference also between cloud and AI transformation is speed is a necessity with AI for banks. So they need to have a sense of urgency. And the reason is cloud transformation was really about modernizing the hardware, making it more scalable, improve resiliency, better, maybe security, but it wasn’t customer pressing, your clients weren’t more impressed with the bank, because they’re on the cloud versus in the data center. So banks, I think, have a little bit more time to work through the rest of the mechanics of doing the deployment. With the AI, it’s going to be detrimental to their business if they don’t start adapting quicker. And so when they think about how to start applying it, I think they need to think a little bit more around who are the right partners and providers that are going to help them do the implementation, AI has become more of an appliance, meaning you buy the AI off the shelf, and a plug it into your business model, as opposed to like designing your own AI models from scratch, right? Banks probably shouldn’t be in that business. It’s too complicated. And so I think that that’s the biggest difference. They need to find who they’re going to work with, they need to find the use cases that they want to start with. And it’s a classic crawl, walk run approach.

Whitney McDonald 6:49
Wondering if you can expand on one thing there, which is you mentioned it could be detrimental to your business. If you don’t implement AI, what could that look like if a financial institution does kind of take too much of a hands off approach or keeps it too much at an arm’s length?

Dustin Hubbard 7:05
Well, I think there’s a couple of issues. One is AI is going to be a game changer in terms of banks, operational scalability. So as AI starts to change the economics of banks, which is how many people they need, how much operations can be automated banks that don’t apply AI are going to start having their margin squeezed, I think a lot more than banks are actually effectively using it. The second part is banks are using AI are going to be able to more proactively serve their clients. And so as a customer, if I start looking at Bank, a, who waits for a crisis to occur, and I walk in, because I tell them, I’ve got a problem, and Baby B who tells me, you’re gonna have a problem, let’s do something proactive about it, people are gonna naturally think gravitate towards those banks. So those are customer retention component there as well.

Whitney McDonald 7:56
Now, we mentioned a little bit about compliance and how to implement this. If we could spend a little bit of time here on how financial institutions can keep up with AI implement in a safe and compliant way. How would you? How would you say that if I should approach that, and then maybe an example of a bank that might be doing this? Well.

Dustin Hubbard 8:18
For starters, FIS can’t let the perceived risk of AI causing action at that’s the big takeaway. If they do their input, the longevity of their business, I think in serious jeopardy. So one of my favorite use cases is around Lafayette bank, and how they transformed their contact center through the use of conversational AI last year, through COVID, in particular, staffing shortages really magnified the call center experience with long wait times customer frustration, people that really don’t know how to serve you. And this is really across all industries and banking was no exception. So one solution wasn’t to hire more agents, which I call the kind of brute force method just hire more people to handle the calls. It was really to improve self service and call deflection through the use of conversational AI. So in six months, they replaced their entire call center stack, inserted conversational AI at the very top of the call, and included voice biometrics, which meant the customer would not only reduce their fraud, meaning the bank knew that it was the person on the other end of the phone by meant that customers could start doing self servicing. Like how much is you know what, please read me my most recent transactions, and the data speaks for itself. WAPA just posted their highest net promoter score in their history 57 the industry average for banking is 35 years ago, wall fence was 17. And when people are voice enrolled when they have the voice biometrics enrollment, they’re seeing only 5% of the time are those clients asking the bar Up to talk to an agent 55% of the time, if they’re not voice biometrics enrolled, they’re asking to talk to an agent. So clearly, when they’re enrolling in voice biometrics, they’re able to do self servicing through conversational AI, it’s actually improving the client experience, but also reducing cost and burden. The point is, AI can be safe and compliant, really, by picking use cases that are well understood, and also already proven by RFIs. They don’t all have to be riddled with like massive risk.

Whitney McDonald 10:32
Now, thanks for sharing that example. I think it’s important what you just mentioned that you don’t necessarily have to pick the riskiest ones in order to implement AI. I think that brings us into the question that we’ve been excited to get into, which is, where is AI headed? What are those future use cases, whether it be short term or long term, wondering if you can talk us through how you’ve been exploring AI and what you see for it in the future?

Dustin Hubbard 10:58
Definitely. And if people follow me on LinkedIn, they’ll know I’m certain AI is can become the most disruptive innovation of the century. For banking, that’s because it has the capacity to dramatically impact every banking function, from origination, to fraud, to lending, to servicing, and eventually to actually predicting. So let’s imagine for a minute what banking might look like in 2030. That’s one of my favorite things to do as kind of a technologist and how AI would actually pull that change. Today, nobody’s paying attention to your finances, but you there’s, you’re the only one who logs in your loved one knows where your money is. And if there’s a problem, you’re the one who’s got to sort it out. But in 2030, actually think AI is going to be doing that automatically with you. So it will know when you’re going to be short on cash between pay periods. Maybe before you do, it will know if you’re going to default fall on a mortgage before you realize that you have a financial crisis, three months on the horizon. So maybe an analogy I could use is to think about how we dealt with weather before the use of satellites. Basically, before we have satellites, we knew if storm occurred when it landed on our front doorstep. And there was no forewarning whatsoever. But satellites completely changed that because it gave us the ability to see weather before it hit us, thus allowing us to prepare to evacuate, to do the things we needed to do to protect ourselves. And that helps minimize the loss. So for banking, I see AI solving that problem for finances. The way satellites help solve that problem for whether it’s predictive, it’s preparedness. It’s not just reactive. So the point is, many technical innovations over the years have disrupted banking from debit cards, mobile apps, peer to peer payment systems. Banking hasn’t gone away, but it has changed and AIS can change it again. But I think vastly more profound ways than probably all those other ones combined. So Fy is really need to have a five year proactive AI plan. They need to work to implement it and refine it and basically make sure they don’t become the next blockbuster. To me that’s the biggest thing that can change the next five to 10 years.

Whitney McDonald 13:26
You’ve been listening to the buzz, a bank automation news podcast, please follow us on LinkedIn. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time and be sure to visit us at Bank automation news.com For more automation news

Transcribed by https://otter.ai

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September 5, 2023
Podcast: FIs should view AI as a team member | Bank Automation News

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Financial institutions can treat AI as a team member in need of training rather than a tool that needs monitoring.

“The banks and credit unions who really get [AI] right are the ones who are treating AI more like they would treat onboarding a new team member,” Lindsay Soergel, chief product and experience officer at fintech Kasisto, said on this episode of “The Buzz” podcast.

Think of AI as one person who has a lot of knowledge, who needs to be trained, developed and understood to become a brand ambassador, she said.

Once trained and trusted, financial institutions can look to AI to build client relationships, answer client questions and represent a bank’s brand with personality that has been embedded into the technology, Soergel said.

Listen as Kasisto’s Soergel discusses intelligent digital assistants, treating AI as a team member and how FIs can bring personality into the technology.

Join Bank Automation News for the upcoming webinar, Global Ideas for Better Banking AI, on Thursday, Sept. 14, at 11 a.m. ET.  For more information on this free webinar and to register, click here.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:01
Hello and welcome to The Buzz a bank automation news podcast. Today is August 31 2023. Joining me today to discuss how FIS can change their mindset when approaching AI and intelligent digital assistants is Lindsay Soergel, Chief Product Officer at Kasisto. She has background in both FinTech and banking, having worked as a technology leader at both PNC and SunTrust Banks.Lindsay Soergel 0:25
Thank you, Whitney. It’s, it’s great to join you today on The Buzz. I’m Lindsay Soergel. I’m the chief experience officer at Kasisto and I focus on connecting our products and services with our financial institution clients, and with their customers and members. And we do that all over the world. We’re fortunate enough to have customers in 16 different countries. I’ve worked in web technology for more than 30 years, and I’ve worked in the digital banking industry since the late 1990s. So it’s been a while managed digital banking and cross channel experience teams at PNC and SunTrust banks and an NCR. And I’ve built FinTech businesses at Equifax, and Deluxe. So I guess, all of my roles have kind of focused on the goal of connecting people with their finances through data and technology. So when I found consistent I thought it was a dream world, you know, the, it’s a very next logical step in my career. And we focus at Cisco on making sure that people are armed with information that helps them to make smarter financial decisions. And, and that’s what their purpose of this organization has always been. It’s a conversational and generative artificial intelligence provider. We focus exclusively on financial services. We build intelligent digital assistants, and other types of AI products come because Cisco has been around for a while, we got our start back in 2013, at the Stanford Research Institute, where Siri was was born, and our tech stack is rooted in the same tech stack as Siri, we’re headquartered in New York, we have about 50 banking clients all over the world. And our customers range from the largest institutions like JPMC and Westpac and Standard Chartered to some of the smallest community banks and credit unions out there. We’ve got about 35, community banks and credit unions now. And that number is growing every week.Whitney McDonald 2:35
So thank you so much for being here and explaining your background. As you had mentioned, we’re going to talk through AI intelligent digital assistance. But before we get into all of that, I’d like if you could just set the scene here by talking through the notion of combining artificial intelligence and human teams and what financial institutions can learn from that approach from Francisco?

Lindsay Soergel 2:57
Sure. Well, I guess, by definition, pretty much every FinTech provider, focuses on building tools, that you’ll either help bankers do their jobs better or help consumers do banking better, or both, right. So ecosystem, we do that. And I guess in that sense, we’re like other fintechs. But the technology that we produce is very different from other software tools. In fact, I would argue, and I often do argue that it’s not a tool at all, it is much more like a teammate. And I actually had to learn that for myself. When I joined Cisco, I thought, you know, I’m coming in with a lot of banking experience, a lot of digital banking experience, I know pretty much what you need to know about digital banking systems. This is a really cool, neat, new thing. But I quickly realized that there is a very clear distinction between financial institutions who are finding success with conversational AI, and those that are still kind of struggling to make it work for them. And the difference was that the ones who are maybe struggling a little bit having some challenges are treating the AI just like they would treat any other digital or mobile banking, app deployment, right, any other sort of automation project. And right, these are smart people, they’ve got 20 plus years successfully deploying all kinds of self service software, just like I had, and they are often imagining that with AI, we’re building just another new self service channel. You know, we’re our goal is to perfectly automate a transaction or multiple transactions, so that you never have to interact with a human. So if If I’m a self service oriented consumer, I can transact completely by myself independent of an assistant of any kind. But that knowledge is actually what gets in the way of success with AI. The banks and credit unions who really sort of get this right, are the ones who are treating AI, more like they would treat onboarding a new team member. And that was a huge epiphany for me. You know, I realized that it was the non digital banking experts, who were playing a huge role in the success of AI. We have a client at Cisco, one of our faves, Jean Fichte, and holds from Mary West Credit Union out on the West Coast, in I thought he put it really well. He says, I think of AI, as this one amazing person with this really huge brain and with access to all the knowledge. And that, I think, is exactly what we mean when we talk about ai plus human teams. So when you’re introducing AI to your business, I think it really would be wise to lean on the people at your financial institution who understand the people interactions, understand the assistant channels, and more so than even the self service channels. You lean on your marketing team, especially the brand folks and the experienced designers, the people who think about the ways that your frontline staff, with their words and with their interaction and with their personalities can create a really welcoming experience for folks who need answers. Oftentimes, the best customer care and member care managers, or the best branch managers play a key role in creating a successful AI deployment. These are the folks right, because they’re, they’re great at onboarding, and training, and developing successful customer facing teammates, who then turn into great ambassadors for the brand. And so that’s the mindset that you’ve got to have. I think that that not that AI is a tool for your team, but that AI is really working with your team, you know, kind of hand in hand, I guess. I guess AI doesn’t have hands. But if you know if aI had hands will be working hand in hand with your team. And so that mindset is what really helps the most successful teams to get up and, and working faster, you’re hiring a new teammate just happens to be AI, you’re introducing them to their colleagues on the team, you want to create seamless relationships between the two good, collegial working relationships. You want those existing folks, whether they’re in the contact center, or in the marketing team, or wherever they are, you want them training the new kid, assign a good mentor to the new employee, right? Make sure they understand what are your expectations for how you’ll be communicating with consumers? What are your practices? What are your brand standards, you train them, and then you let them go to work, just the way you would let an employee go to work, right? You don’t QA them for three months, you know, you know, you don’t necessarily spend all the time in the weeds with with making sure the codes perfect. You watch them, and you give them tips, but but then you let them go to work.

Whitney McDonald 8:47
Now you talk through changing that mindset, not necessarily having AI as this new tech tool, but treating it like part of your team you just talked through working hand in hand. Maybe we can talk through how Christo has put this into practice, more specifically within its intelligent digital assistant, how do you achieve this? This approach?

Lindsay Soergel 9:12
Yeah, I think there are a couple of ways that we really work hard to make sure that we’re helping our financial institution clients to create an appreciation for ai plus human is generally people consider chatbots traditionally, to be the domain of the contact center, and the customer service teams. And there is absolutely no question that the contact center is a very key connection point for the digital assistant. You know, if you think about even the most digitally savvy, very self service oriented customers, they’re going to want to chat with a human from time to time. So one thing we’ve done is to make certain that our digital assistants are integrated out of the box with live chat experiences. So we come pre integrated with financial chat systems like Link live or glia, and other ones out there. And so when a consumer does need to shift from that digital realm, over into the human assisted realm, or vice versa, the entire chat conversations can be passed between the digital assistant and the live chat, the human agent. And that can be done without any Miss missing a BT at all for the from the consumers perspective. But we’re also I think, even more concerned, because Cisco about the less digitally savvy customers, the folks who maybe wanted to speak with a human, but they weren’t able to, because they were directed to the digital assistant as a first stop, or they weren’t able to wait in a call queue. And that’s where I think our technology, and our onboarding process is really focused on how can we address that particular need? So we spent a lot of time working with bankers, who are in the process of thinking through what will be success? what will success look like, in their final implementation in their final introduction of their new digital teammate? And we asked them to consider how how can the digital assistant be used to help that group of traditionally maybe digitally averse consumers be more at ease when they’re interacting? Maybe it’s the first time with a digital assistant or Chatbot. Maybe they have a preconceived bad experience with other solutions that weren’t great. So, you know, what’s that first greeting? Like? Is the user interface in any way intimidating? Or is it inviting, helpful, pleasant? Is it personable? Is it conversational? And, you know, I think one of the best ways that that the bankers can kind of think through this process is to think about what’s the right personality? For our digital assistant? What are the characteristics that would really appeal to our community audience? Or to if it’s a larger financial institution, or one that serves multiple audiences, to the various audiences that we serve? What What should that unique personality be?

Whitney McDonald 12:38
Now to expand on that idea, a little bit of bringing personality into the IDA? How do you achieve achieve that? What is the technology look like to to bring human like interaction into something that is a digital tool?

Lindsay Soergel 12:57
Yeah, I mean, so I think the first thing, when when you’re looking to create a relationship, is to not necessarily start with the technology, I when I will, I will talk about how we all the technology works and enables this, but it’s important that the FYI, just sort of start with the consumer first. Think about the process of banking, and how it can sometimes be intimidating to certain sorts of audiences. And, and not necessarily audiences that are not tech savvy, or already tech savvy, where you might have young people who are just starting out in the world and are not intimidated by tech, but are intimidated by banking. Or you might have you know, folks who are particularly astute and savvy in retail banking, but they’re just about to open a new business, and they’ve got some questions, and they feel a little bit like a Rube all of a sudden, you might have a person who’s changing financial products and needs advice, right? Or folks who’ve moved to maybe maybe just moved to the states are learning our financial system, etc. Right? So there’s, there’s all different sorts of reasons for folks to need a digital assistant. And so I think we would encourage our banking clients to stop and think about their community of users, and to think about what are all the sorts of issues and challenges that they are that their digital assistant and its personality needs to solve? So first of all, just basic good old fashion outside in consumer centric design, right, that we’ve all been thinking of so those techniques around, you know, sort of usability and, and user focused design really pay off Um, our customers tell us that increasingly, a lot of consumers in those some of those segments that I kind of ran through there, they’re using the digital assistant as a starting point. So it’s a way of gathering some facts and information before they’re ready to walk into a branch and sit down across from a banker who can help them with more complex transactions, or maybe they’re going to call up somebody in the call center to initiate a transaction, but the IDA becomes a place for them to start. And, and when that’s the case, those customers definitely are not looking for a flat, kind of traditional chatbot robotic interaction. So it would be wrong to sit there and think, you know, here are the here’s the question, here is the answer. We want to think about what kind of tone do we want to imbue into that interaction? And our tool, our content management tool, allows our banking clients to figure out exactly what it would be what are the kinds of ways that would put their customer base at ease? How can I help them to feel more comfortable? You know, so, if a customer is looking for a very financially literate conversation, and a helpful, intelligent assistant, the digital assistant can can deliver that. So that right what’s involved in that there’s, there’s an AI piece of it, and a natural language, understanding piece of it on the technology side, that allows us to recognize all the various ways that a customer consumer may be asking a certain sort of question. And then there is the part that’s up to the banker to think about, how do we want to respond? Are we a very professional type of brand, are we more lighthearted type of brand, right? And so that’s how a little bit of digital personality gets imbued into the the idea, I would say, the most successful financial institutions to embrace the capabilities of Chi Chi’s our platform. And our and our tools, our content management tools? are the ones who are thinking about that first greeting? And what are the characteristics of the personality that they want to highlight for their members and customers? And I’m always fascinated by the fact that there’s really no one right way to apply the technology. Digital Assistant for a private wealth oriented bank in southeastern US, is going to be very different from the persona that you know, a digital only FY in the Pacific West, that maybe only tailors to a younger clientele is going to deploy.

Whitney McDonald 18:07
Now, as we talk through AI driven technology daily, you see updates to what AI can do, how does the system make sure that that’s all being updated? Within its platform as well? How do you stay up to date with something that is changing so quickly?

Lindsay Soergel 18:26
Yeah, it’s a good question. I mean, we are, I suppose we do it in a couple of different ways. And it requires keeping pace both technically. And right, from a regulatory standpoint, and just from the standpoint of what are bankers looking to do? What are what ideas are they having? What are they struggling with? And so the most important thing that we’re doing is we’re talking to as many bankers every single day as we can we literally, I can’t think of a day in the past six months, that we have not been on the line with customers, prospects of financial institutions, large and small, just to understand, what are you trying to do? Where do you see the opportunity? Across your segments? Across your use cases? Are there different sorts of things that you’re looking to do? And it’s just because the tech is so new, it is evolving every single day. And so we we want to keep pulse on what our very creative, innovative clients are thinking about. And as they’re developing new concerns or new questions, it’s very likely that we have spoken with some other client who may have worked with us to already solve that particular challenge.

Whitney McDonald 19:55
You’ve been listening to the buzz, a bank automation news podcast, please follow us on LinkedIn. As a reminder you can rate this podcast on your platform of choice thank you for your time and be sure to visit us at Bank automation news.com For more automation news

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August 31, 2023
Podcast: Embedded finance | Bank Automation News

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Small businesses are embedding payments options beyond credit card transactions into their platforms as consumers desire pay-over-time capabilities.

“Now that technology has allowed installment payment options to be present everywhere, especially online, consumers are choosing that,” Bobby Tzekin, co-founder and chief executive at embedded finance platform Wisetack, tells Bank Automation News on this episode of “The Buzz” podcast.

While software-as-a-service providers allow companies to embed payments options into their platforms with credit card transactions, the more affordable approach actually is to spread out payments over time, Tzekin said.

Wisetack’s API-based technology embeds into a company’s platform to allow for these pay-over-time transactions, he said.

Listen as Wisetack’s Tzekin discusses embedded finance with BAN Editor Whitney McDonald.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:01
Hello and welcome to The Buzz a bank automation news podcast. Today is August 22 2023. Joining me today to discuss embedded finance is co founder and CEO of wisetack. Bobby Tzekin.Bobby Tzekin 0:14
Hi, I’m Bobby Tzekin, I am co founder and CEO wisetack. And my background is over 20 years in FinTech at this point, a started in the early 2000s. at PayPal before FinTech was a term. So I spent seven years at PayPal as the company grew quite a bit. And after that, was head of product at three other FinTech companies, both in the payment processing space, as well as online lending. And all of that experience actually has led to co founded why stack because we sit at that intersection of payments and lending.Whitney McDonald 0:55
Great. Well, thank you so much for joining us for the buzz would love to kick things off with you kind of setting the scene here for embedded finance, what is the need for for this type of solution, the ability to pay over time? What does this bring to clients and express a little bit about what the need is for this market?

Bobby Tzekin 1:13
Yeah, we believe there’s two important trends that are driving consumers to adopt something other than a credit card to pay for purchases these days, which then is setting the stage for the embedded piece. So first, in terms of financial products, credit cards have been the most common and frequent way consumers will borrow in the US. And the reason why that’s changing is twofold. One, after the Great Recession, there was a regulation that prevents card issuers from marketing on campus and universities. And so now we have a much larger population of young people graduating without credit cards and going without a credit card for a long time. So that is requiring a new way for them to afford larger purchases before they really started getting the income that they’ll get later on in their career. So that’s one trend. The other really important one is everyone understands these days that a credit card is not a great way to borrow great way to pay if you pay it off at the end of the month. But it’s expensive to borrow. And everyone understands that. And so now that technology has allowed installment payment options to be present, everywhere, especially online, consumers are choosing that because they know it’s more affordable to spread your payments over time via these installment payments. And that I think sets the stage for Well, why is embedding these financial products important. And the other trend that contributes here is the adoption of SAS or software as a service by businesses pretty much every business, no matter the size these days, is thinking about or has already adopted some type of software to run their business. And those software providers themselves are embedding payment options. And the most common one usually the first one is credit card payments. If if the businesses are serving consumers, the software they use typically will offer credit card processing. And the next step beyond that, obviously, we just talked about the limitations of credit cards is Well how else can a consumer pay, especially for larger purchases? And that’s what wisetech does, we embed the seamless installment payment options. So the consumer can pay over time if it is a large purchase, and they don’t have to put it on a credit card.

Whitney McDonald 3:32
Now taking that a step further, I know you started talking through how wisetech accomplishes this, but maybe we can get into a little bit about the technology behind wise tech and how it’s how it works.

Bobby Tzekin 3:43
Yeah, absolutely. So as I mentioned, its most fundamental voi stack technology consumer can pay over time for a large purchase and how we’re different from others who may say the same thing is that we’re an API platform. So we do a few things differently. One is we’re incredibly easy for a developer to integrate into any software experience. So it’s a deeply embedded option. And that does a couple of other things. One is it makes it really easy for the business to get started. So the business, just the way everyone expects these days that if they’re running a business, they can very easily enable credit card processing for their customers. They can do the same thing with installment payments via wisetech. It is very easy it is embedded in the software that the business is already using. So it makes the startup cost go away for the business. We’re also because we’re embedded we’re very seamless as part of the purchase for the consumer, very customer friendly. So we from the very beginning focused on simplicity and customer friendliness, and that encompasses both the consumer as well as the business. And another way we differentiated is we in the past they focused on businesses that sell in the real world so not online purchases, not a website. They sell through but they are usually doing something involves an in person service. So we work with a lot of home services, businesses, like plumbing, electrical, H back, and so on just things around the home. And we also work with dental practices, we work with car repair shops and some other similar type of businesses that that again, serve their customers in the real world, not on the website.

Whitney McDonald 5:25
Now a little bit further into what you were just explaining, could you talk through, I don’t want to use the word embedded. But could you talk through integrating wisetech onto some of these claims that you were just explaining what does that entail?

Bobby Tzekin 5:38
Yeah, we, we have focused on having a really simple API that I do think the best parallel is, these days, everyone expects it to be really easy to integrate card processing. So So there are a few components. One is for businesses, how do they get going and offer the payment option. So it should be really easy to provide some basic information and turn it on for for my customer experience. So we do that. Also, we embed reporting, so in the software that a business is already using, all their transactions that have been paid via wisetech will show up seamlessly in the reporting. So they don’t have to change anything around how they reconcile what their business did. And then the final part is, again, for their customers for the consumer, how easy is it for the consumer to pay. And so all of that we’ve made it really easy to put into a piece of software. So think if if I’m running a plumbing business, I’m using this piece of software to manage my entire business. It means dispatching my technicians to jobs in the field, it means managing my inventory of supplies, it means my orders my payments. And so why stacks embedded in there as a payment option. And anytime there’s a large, unexpected job, let’s say your pipes burst at home, and it’s an unfortunate thing is going to cost many 1000s of dollars to repair Well, you don’t have to panic about how you would pay for that because you can pay over time. And that option is available as the business comes out to do the work.

Whitney McDonald 7:15
I’d love to get into another use case here. I know that you just shared that great example. Maybe we can talk about another way that wisetech is in action. I know that you recently announced that you’re working with citizens, maybe you could talk through through that and what that entails a more specific type of use case. Yeah, I

Bobby Tzekin 7:35
can talk about both of those. So another very common example we have is imagine it’s it’s the winter and it is very cold and your water heater goes out or your your heater for your home. And it is obviously an emergency. When that happens, you didn’t plan for it, you call It’s a call a plumber, if it’s the water heater, they show up. And they look at your 15 year old water heater and they say, well, it’s on its last legs, I can repair it. And I’ll probably be back here next year. Or I can replace it with something better. Or you have another option, I can replace it with a really modern top of the line version that’s much more energy efficient is actually going to save you substantial costs in terms of the energy that it’s going to consume. And at that point, the merchant usually will will present a proposal that says here’s your options. And for the options of replacement or the top of the line replacement. There’ll be something that presents, okay, maybe it’s $2,000 for this option, or as low as let’s say, for example, $150 a month. And that allows the consumer to afford something better that over the lifetime will save them money, whether it’s through lower costs of repair or lower costs of energy, if they could just afford to make the better purchase in the moment. So it’s a win win. Because the business is able to do the right work and serve the consumer, the consumer is able to afford something better. They don’t have to revolve on a credit card and incur additional costs. And so then the consumer makes the choice. Let’s say they do elect to pay overtime so they can afford the better the better purchase. They can either proceed with that through the proposal that they received from the business, which often is digital, it can be emailed or texted to the consumer, or the merchant and the technician in the home via the mobile app that they use to manage their work and push a button and the consumer can attack text message to complete their payment. So all of that is part of the consumer experience. And then once the consumer starts the process, it takes just a minute to see what their options are to pay over time. And they can complete everything on their own device really quickly. So that’s the that’s the customer Ernie, that’s an example of how it works. And I’m happy to go into that more if it’s interesting.

Whitney McDonald 10:06
No, that’s great. And I kind of wanted to shift a little bit here into what I was talking about with the relationship with citizens, what what it means to be working with a financial institution, I know that there was also discussions that there was opportunity to further those types of relationships, maybe specifically talking about citizens here, and what that does, with with wisetech, and then other opportunities for other FIS to to work with other advice.

Bobby Tzekin 10:34
Yeah, from the very beginning, when we started the business, in our business plan, we said that we’re building a platform for financial institutions. And the reason for that is multifold. One is, as I mentioned, these are big shifts in terms of what’s available to consumers, we know that financial institutions need to play in that space of installment payments. So we knew that they’d be interested. On the other hand, these are large banks committed to serving consumers, and they have a really low cost of capital. So we knew it would be a win win to provide a technology that we’re great at making and running to financial institutions that are already committed to that business and have a low cost of capital. And so that benefits customers, and it benefits the financial institutions. And in terms of, if you think about citizens, they already have some big brand names, they’ve had a partnership with Apple for a long time, they’re partnered with Microsoft for purchases at the point of sale. So they really know the space, the reason why they partner with us, is because they reach a channel and a type of business that they can’t reach otherwise. And that is those developer integrations that bring them smaller businesses and real world businesses. And we’re really good at serving those merchants, we have a big merchant base that they want to have access to. And again, for us, we get a lot of benefit from being partnered with a large bank that is committed to this space. And we do, as you mentioned, we do have others in in process that we’ll be announcing, in the coming quarters. And again, it furthers the the example I started with that if if you think of us as a network of technology integrations and merchants, we always planned to bring the banks to this platform. And another parallel again, if you go back to the card processing world is on a smaller scale, think Visa and MasterCard that is a network of consumers and merchants that allows payments and financial institutions to be on that network. And that’s very much the vision for us. But we are not beholden to the card rails and have a lot more flexibility when it comes to the terms on which everyone can participate.

Whitney McDonald 12:54
Yeah, that’s really helpful. And I know you kind of gave us a little bit of a sneak peek of your you’re working with others. But it’s all just about kind of growing that network is what I’m getting from what you’re what you’re saying citizens being one, but like you said, there’s there’s others in place to again, grow that grow that network that’s speaking of what you’re working on, for the remainder of 23. I know you said a couple of other partnerships, announcements coming in the coming quarters on the tech side, or even just on the embedded payment side things that you’re working on for the rest of the year or excited about for the rest of the year. Yeah,

Bobby Tzekin 13:33
there are quite a few things. That’s a big category, onboarding the financial institutions and ensuring that that important pillar of the business is really serving the the large banks. That’s an important part. And as we talked, we’ll have more specifics to share soon. The other part is we are growing the network part, we are growing our integrations we are growing our network, our Merchant network and merchant base. And so all of that comes with plenty of work where we’re constantly looking to make the product simpler and better so that it can reach more customers. We’re growing quite fast. And that comes with its own set of things we have to do. Overall, I’m very excited that our net promoter score has stayed really high. And we do we do organize what we do around customer happiness. And from early days, our net promoter score has been just just around 80. And so that that’s how we prioritize what we do. And it’s focused on what are the little things we can do in the product that makes it that make it ever easier for the consumer to pay and then for the merchant, to use us. So we have a long list of those. And so just supporting the growth of the customer base generates a decent amount of work. And currently I would, I would say those are the main two areas, the financial institutions and the growth of the customer base that we are focused on.

Whitney McDonald 14:58
You’ve been listening to the As a bank automation news podcast please follow us on LinkedIn and as a reminder you can rate this podcast on your platform of choice thank you for your time and be sure to visit us at Bank automation news.com For more automation news

Transcribed by https://otter.ai

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August 22, 2023
Podcast: Using AI to Identify Fraud | Bank Automation News

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AI has joined the fight against bank fraud, and further enhancements to the technology are helping financial institutions monitor risk.

AI technology is advancing quickly and is “approaching the ability to emulate the more advanced features of human cognition,” Phil McLaughlin, chief technology officer for fintech AML RightSource, tells Bank Automation News on this episode of “The Buzz” podcast.

Founded in 2004, Cleveland, Ohio-based AML RightSource is a provider of technology-enabled managed services and software solutions, McLaughlin said. The anti-money laundering fintech combines AI-led technology with its team of 1,000 investigators working in the field.

The fintech’s bank clients, including Puerto Rico-based Stern International Bank, are leveraging AML RightSource’s AI to monitor onboarding and transaction activity, McLaughlin said. The fintech’s technology is able to identify whether a potential bank customer is politically exposed, or if there is negative media about them, or if other risks could surface.

“We have tools and techniques that allow us to monitor changes in [customer] activities, identify that a change has occurred, evaluate the parties involved, to see if there’s a risk event that we need to surface,” he said.

As AI evolves, its ability to screen potential clients in the onboarding process and monitor transactions will become faster and more automated, allowing “human beings to focus on the things that are really salient,” McLaughlin said.

Listen as AML RightSource CTO discusses best practices in anti-money laundering and how AI advancements can improve fraud fighting techniques.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:02
Hello, and welcome to The Buzz, a bank automation news podcast. My name is Whitney McDonald and I’m the editor of bank automation news. Joining me today is AML, right source Chief Technology Officer Phil McLaughlin. He’s here to discuss the need for anti money laundering practices, and advancements in AML. Technology.Phil McLaughlin 0:22
My name is Phil McLaughlin, I’m the Chief Technology Officer at AML. Right source. Amo, right source is a provider of managed services, which is people, financial crime advisory services, and then also technology platforms, and sort of the blending of those three offerings together in technology enabled managed services, and we support banks, other non bank, financial institutions, fintechs, all over the world, we have around 4000 investigators that work with our customers to help them stay compliant in the AML KYC space. And we’re bringing technology solutions to those customers, to help them be more efficient and more effective. And, you know, that’s really the the problem that we’re we’re all about, you know, trying to make the efforts that our customers and that that our, you know, internal teams are trying to accomplish as efficient as effective as possible.

Whitney McDonald 1:20
Great. Well, thanks so much for joining us on The buys, let’s take a step back here first and set the scene with financial or fighting financial crime today, you could talk us through really the need for this advanced technology, especially when identifying money laundering.

Phil McLaughlin 1:39
Definitely. So the the estimates that are out there today are that basically the current methods that we’re using for any money laundering, our lack, you know, are lacking, right, they fall short of what we really need to accomplish here. If you look at a number of estimates from the UN and others, it’s something like two to 5% of global GDP are, you know, between 800 billion and $2 trillion that are involved in, in money laundering, and we’re probably only catching maybe 5% of that. So despite the significant amount of effort that banks, regulatory agencies, folks likes us that are in the services and technology business, you know, there, there’s still a lot of room for improvement to make this stuff better. And then when you sort of look at the technology side of this, that the technology systems themselves that are helping are really not all that effective, they look at relatively relatively small amount of data, when trying to make assessments, they are really pretty simplistic in terms of the things that they’re looking at, like simple patterns, that sort of stuff, simple name matching. And we know that the the reality of the of the financial crime space is a lot more complicated than that. And so really, technology needs to come in and help improve this. You know, again, the way to think about this is, this is largely today a very human intensive effort, the tools alert or highlight certain characteristics, but it’s really left to the investigator really left to the human being to do the vast majority of the legwork, do all of the data synthesis, do the evaluation, make a conclusion, draw a recommendation, document all of that. And it’s a very, very time consuming process. So the degree to which technology can be employed to help make those human beings more efficient and effective. That is, is where we’re going.

Whitney McDonald 3:35
Now, before we get into where we’re going with, with new technology and advances in technology in this space, maybe we can talk through what exists today. What are some best practices in tackling, identifying and in identifying money laundering today?

Phil McLaughlin 3:52
Sure. So I think we’re, we think about this, kind of from a current state future state sort of thing, right? So really, the goal is gonna be to improve the level of automation and to include or improve the level of efficiency with the investigators. Like I said, a lot of the processes today are very limited in terms of what they look at. So you know, as you’re thinking about as people are thinking about, you know, how would they improve their process, looking at more data, automating anything that they can the robotic process automation capabilities are out there are a good place to start in terms of, you know, thinking about how to make things better. Expanding the frequency of monitoring again today, because it’s a very human intensive process. Things get looked at maybe on a once a year basis, once every six months basis, if there’s things that we can do to make that an ongoing, continuous monitoring type of a solution that lets us find things faster, and allows human beings to flow focus on the things that are really salient as opposed to separating the wheat from the chaff so to speak. Again, a lot of the tools that are out there right now, or are very limited in terms of their technology or their their detection capabilities, a lot of them are rule based. So, you know, the simple rules that are capable of being implemented in these kinds of solutions are, are very limited. And that’s really why, you know, the broadening of the of the technology platforms and the algorithmic content and moving towards AI, and some of these other things are so important to help us, you know, begin to tackle these problems in a more efficient way.

Whitney McDonald 5:41
You can’t talk about anything in technology right now without talking through AI. Right. So maybe you could expand on that a little bit. Why is AI well suited for this type of technology? And how can AI fit into this puzzle?

Phil McLaughlin 5:55
Thing, AI is exceptionally well suited to the AML challenge. The thing that’s great about it is, is that, you know, as people now are starting to have a pretty broad awareness, some of these AI tools and techniques are really approaching the ability to emulate, you know, the more advanced features of human cognition, right, so they are really able to, not only, you know, do what we consider to be really relatively simple things, but but much more complex levels of thinking much more complex levels of inference of summarization, those kinds of things. And, you know, being able to figure out even with traditional AI techniques, you know, be able to, to do anomaly detection, figure out what’s notable, and, you know, separate the needle, find the needle in the haystack, so to speak. There’s a bunch of different flavors of AI that are sort of relevant here, you know, two good examples are natural language processing. So if you think about what an investigator has to do, to go read news articles, read various documents and artifacts, and try to infer and connect and synthesize all the connections there. It’s a huge amount of work and the degree to which you can get knowledge from text and understand it and present it to a person in a way that is easy for them to then internalize and take action on. That’s just a super, super big force multiplier. And then, you know, the more traditional, you know, machine learning models, whether they’re classifiers, or whether they’re other types of, of neural networks are really good at at, you know, training to be able to figure out things like entity name, or entity type from an entity name, that’s one of the problems in money laundering is that the, the banks and financial institutions know a lot about their customers, because they vetted them in the onboarding process, but they don’t know much about the counterparties or other related parties. And so the amount of work that can be done to to, in an automated sense to try to collect information on those related parties and counterparties is going to make the total understanding that the investigator has that much more clear and allow them to, you know, more, resolve those issues or solve the cases in a more timely manner.

Whitney McDonald 8:18
Now, we’ve talked through the technology, the opportunity for advancements here the need for solutions like this. Can we talk through where AML right source fits into this and how the technology works?

Phil McLaughlin 8:31
Yeah, sure. So as I mentioned earlier, email is a provider of technology enabled managed services, as well as software solutions to banks, fintechs, and other institutions that have regulatory requirements to help oversee the safety of the global banking systems. We have 1000s of investigators working in the field on KYC, suspicious activity monitoring, you know, those around the globe, really, across the all the different global geographies, in addition to you know, providing sort of these AI LED technology solutions. So we’re really all about trying to bring this great technology along with great people to our customers. You know, one of the things that I would say to somebody who’s looking into trying to embark on, you know, putting their toe in the AI for AML waters is, make sure you work with somebody who knows AML because if you’re just going to work with somebody who knows AI, you’re going to end up paying for their learning curve. And there’s so much nuance in terms of the data and the risk bearing characteristics that are that are relevant and important in the AML space, that you really want to have a partner that understands that stuff. And so, you know, we think we are, you know, the best of the best in that regard, really having, you know, strong practitioners, coupled with that AI technology, you said bringing that AML AI, sort of blend to the our customers.

Whitney McDonald 10:07
Now speaking of a customer, maybe you can talk through or identify some use cases who would use this? How would you get in? How would you integrate maybe talking through what that entails?

Phil McLaughlin 10:20
For sure. So our customers and our solutions tend to follow the customer lifecycle. So think about your relationship with your bank, you open your account with a bank, they onboard you, they make sure you’re not a bad guy, they make sure you’re who you say you are. Once you’re on boarded, then you can start transacting. So there’s some, you know, transaction monitoring that’s going on the so called suspicious activity monitoring. So we’re helping in that regard. There’s also sort of know your customer monitoring that goes on through the course of the lifecycle. So let’s say you’re a bank, let’s say you’re a corporation, and you’ve just had a change over in your board of directors, and you want to understand, you know, you’re the bank wants to understand, is this new person on your board? Are they a good guy? Are they a politically exposed person? Do they have? Is there negative media about them? Is there some other risk that should be surfaced related to, to this district board member. And so we have tools and techniques that allow us to monitor changes in those activities, identify that a change has occurred, evaluate the parties involved, to see if there’s a risk event that we need to surface, and then we’ll surface that, then then, you know, we also help with more broader just workflow across that whole client lifecycle, helping customers to manage that full trajectory from onboarding through monitoring through suspicious activity detection, periodic monitoring, and then to offboarding. So it’s, it’s all the stuff that you’d think about in terms of, you know, that full lifecycle.

Whitney McDonald 11:59
Now, quantifying here some savings that that someone that a bank might benefit from, from this client might benefit from this catching fraud examples of successes here.

Phil McLaughlin 12:14
Yeah, definitely. So like I mentioned, the big banks do a pretty good job of understanding who their customers are, but it’s this community of related parties where there’s often a lot of insights that can be gained. And also just like, understanding sort of the specific nature of the activity and trying to identify if something is anomalous. So for example, we have, you know, a tremendous number of our customers who’ve seen, you know, instances where they’ve identified risk in in Counterparty. So for example, some buddy might be have negative media associated with them, they might be a bad guy, they might be a politically exposed person, that kind of stuff. Some of the more interesting ones, when you start looking at the AI techniques, the more advanced AI techniques is looking at things like inconsistent line of businesses. So if you’ve got a banana, or steel company, and they’re buying iron ore, that makes perfect sense, right. And if you’ve got an iron, steel company, they’re paying for bananas, that doesn’t make sense. So the tools and techniques are able to learn by looking at a massive amount of data, what kinds of relationships are appropriate, what kinds of relationships are inappropriate or consistent with what one would expect. And they can highlight that to the investigator that this, this company seems to be doing something that is counter to what one would expect given, given what we know about them. We’ve seen a number of instances of that with our customers, we’ve also seen the issue of money going the wrong way. So let’s say you’ve got a we’ve seen an instance where there was a casino, and they were getting transacted with a company that makes computers and so you would expect to see the money flowing from the casino to the computer company, because they’re purchasing computers to use in their Casino. That would be a perfectly reasonable use case. But what we saw is the money going the other way. It turns out that after further investigation, the the gentleman who was the head of the computer company had a bunch of different activity that he was involved in. And you know, we were able to help surface that particular instance, we’ve seen other instances where companies are related to risky parties or risky jurisdictions. So let’s say that people are concerned about doing business with any buddy who’s not only in Cuba, but doing anything related to Cuba. And so we’re able to detect, for example, that there are companies in Venezuela, who are arranging travel to Cuba, which is not illegal in the context of what they are doing as a company but But, but the US banking folks would want to know that that party is has a relationship with Cuba and is doing something there. So there’s, there’s a lot of those kinds of instances where, you know, we’re able to surface relationships or surface characteristics about the related parties that help make sure that the, the, our customers understand what that full picture of risk is. And it just wouldn’t be practical for humans to do all the legwork to hunt each and every one of those things down. So, you know, at the end of the day, it’s really coming back to automating whatever we can, for the investigator, making the investigator giving the investigator, you know, the, the best point of departure to resolve the investigation as they can. So I the analogy that I like is, um, let’s say, doing an investigation is a 100 meter dash, you know, if we can start a client at the 50 meter line, or the 70 meter line, and all they’ve got to do is get to the end, then that’s, that’s, that’s the goal. And that’s, that’s really what we’re seeing with our customers, they’re seeing a significant amount of savings, in terms of the amount of time that it takes. And it also puts the investigator in a lot better position because they’re able to then instead of doing all the legwork, all this grunt work of doing Google searches and searching for names and structured databases and searching, you know, downloading transactions and building pivot tables, and totaling in sub totaling all this stuff to see what’s going on. We can give them all of that prevented, we can give them all of that, in a human readable narrative, supported with all the documentary evidence, and it really lets them the investigator focus on using their training their experience, their their education and, and an expertise in actually understanding if there’s financial crime there, as opposed to being an Excel expert or a Google search expert.

Whitney McDonald 16:59
Now with with these use cases, and working with clients and and all of that what you just discussed, what are you working on when it comes to innovating in this space and forward looking maybe just to the end of this year? What am all right sources is working on I know, we talked through AI opportunity and machine learning and of course generative AI as a as a buzzword as well, maybe you can share a little bit about what you’re looking into?

Phil McLaughlin 17:26
Yeah, for sure. So, the good news for us is that we’ve been really bringing AI to the financial crime flight now since 2015. So we are well versed in how to use and employ these different techniques to to solve the problems. We’re looking right now, working in a couple of different areas, one major area that we’re looking at is we’re rolling out the next generation adverse media solution that we have. So really helping, you know, our customers very effectively and efficiently get surfaced articles, news articles content from around the world, that might indicate that they’re a customer or a related parties involved in something that would be risk bearing, we have a tremendous amount of natural language processing and other artificial intelligence techniques that are baked into that, and we’re gonna see, you know, a two fold improvement, at least in terms of the efficiency with with with which the investigators can adjudicate the articles as well as a significant drop in false positives. All of these adverse Media Solutions, try to do their best to give relevant content, but it’s a hard problem to solve the next generation of our stuff that we’re bringing out is going to do a fantastic job of that. We’re also we are working in a number of different areas with with LLM with the generative AI techniques. You know, the way we think about this is, this is just another tool in the ever evolving AI toolbox. So, you know, when when we talk about AI, it really spans the gamut of all the different things that can fit in there, right, from natural language processing to more traditional, supervised and unsupervised machine learning to the new LM and a whole bunch of other, you know, techniques that are in this toolbox. And so, you know, our view that L is that LM is is just another tool that we can utilize to help solve problems. The work that we’ve done with LM M’s and we expect to have some of these use cases in production in the next few months, has largely to do with with inference and reasoning and summarization, like those are the things that the algorithms are really very good at. So asking the LLM, read this article and tell me if this entity is a good guy or a bad guy. They’re pretty good at that. Looking to do knowledge extraction, taking the LLM and saying, you know, tell me how old the subjects in this article are or tell me what jurisdiction in there that are in, those are very easy things for humans to do. Not very easy things for some of the traditional AI techniques that we’ve had out there, and, but are something that LLM ‘s are very good at. So, again, we’re looking at a number of different areas having to do with data inference, summarization, those sorts of things. And we’re going to be peppering them essentially, throughout the solutions, we’ll be sort of using them to augment the existing capabilities. A lot of the techniques that are there could have AI techniques are often layered. So you may start off with one technique, and that may get you 50% of the answers, then you may need to go to a second technique with that is different or better to get to another 25%. And then you need to go to a third technique to get you in another, you know, 10, or 15%. And so the way we think about these MLMs, in the short term is, is them just being another layer another tool to help fit into that tapestry of, of solutions that we’re using, you know, in the big picture, our view is that, you know, these, the MLMs are here to stay, they are going to become more and more important tool in the toolbox. Like I said, they’re not going to replace everything. They don’t do everything, as well as some of the other techniques. But I think that over time, we’ll see them becoming more and more prevalent. I also don’t think that in this space, at least LLM ‘s are ever going to just entirely take over the the process, right. There’s always going to be the need for human judgment, human intuition, human training and experience to be able to adjudicate the final outcome. And while the LMS can definitely help with efficiency and effectiveness, they’re they’re never going to be maybe never too strong. But in the near term, they’re not going to be sort of the standalone, you know, Uber AI solution that that answers the questions for us.

Whitney McDonald 22:12
You been listening to the buzz of bank automation news podcast, please follow us on LinkedIn. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time and be sure to visit us at Bank automation news.com For more automation news,

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August 15, 2023
Podcast: Future of mobile payments | Bank Automation News

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Financial institutions look to omnichannel offerings to meet clients where they want to be met, and most consumers now prefer a mobile experience — even to pay their bills.

“Eighty-seven percent of Americans prefer to be met over their mobile device than any other channel,” payments provider Solutions by Text Chief Executive Dave Baxter tells Bank Automation News on this episode of “The Buzz” podcast.

Mobile technology allows customers to be reached by billers on demand and in real time.

For billers, reaching clients about payment is effective via text messaging since 97% of text messages are opened and read in less than five minutes, Baxter notes. Meanwhile, emails can end up unread or languishing in spam folders.

Bills sent through text are likely to reach a consumer at the right time. Baxter’s Solutions by Text has a 99% deliverability rate where its messages reach consumers, Baxter said.

Listen as Baxter discusses how to integrate text messaging with payments.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:04
Hello and welcome to The Buzz a bank automation news podcast. Today is August 8 2023. My name is Whitney McDonald and I’m the editor of bank automation news. Joining me today is Dave Baxter, Chief Executive of solutions by text. He is here to discuss the idea of turning messaging into payments.Dave Baxter 0:24
My name is David Baxter. I’m the president and CEO of solutions by text. We’re a messaging company that was founded in 2008. Based in Dallas, Texas, with remote offices throughout North America, as well as Bangalore, India, we were one of the first messaging companies that really pioneered text messaging. And we lead a most compliant messaging platform in the industries that we service, specifically, consumer finance in some verticals of consumer buy, we service roughly 1500 customers throughout auto mortgage community banks, credit unions, card issuers, and marketplace lending.

Whitney McDonald 1:08
Great. Well, thanks for joining us on the podcast. I would love to start off by setting the scene here on how you have determined how clients want to be communicated with what works, what doesn’t work. Tell us about your strategy.

Dave Baxter 1:22
Yeah. So when we were thinking about the messaging platform really started with thinking through, we’re an extension of our customers brand, to the extent that we believe that the consumer is always going to win, and you have to meet consumers where they’re at from acquisition of an account all the way through delinquency and everything in between. And there’s no denying the fact that everybody is mobile first, right. And as far as messaging goes, in Gen Z, they’re on their phone greater than, you know, 10 hours per day, on average, people look at their phones, roughly 20 times a minute, there are billions of messages sent every single day. And so we felt that a logical play for us is really thinking through bill pay, and meeting consumers like just give them a very seamless, quick on demand way to view and subsequently pay a bill on the device that they carry with them throughout the day.

Whitney McDonald 2:29
Now, if you could talk us through this idea of turning messages into payments, you discussed that everyone’s on their phone all the time you gave those data points, I think that you said you look at your phone 20 times per minute, can you talk about really meeting the customer, where they are and how you turn this into a way of payments?

Dave Baxter 2:49
Yep, so 87% of Americans and this is through the the last at how Americans pay their bills, the latest one is coming out. So the there will be refreshed data, we can discuss that you know, at another time, but 87% of Americans prefer to be met over their mobile device than any other channel. So it’s don’t phone me don’t write me a letter, don’t send me an email. So it’s clearly the most preferred channel I mean, look at your your daily life, right? And everything that you do, you’re likely, you know, in an in and around your phone using different applications, you’d like to communicate with your friends and colleagues and family through their phones. So why not communicate with a biller through through text messaging? Interesting stats, and so far as 65% of payments are made on demand as a result of an alert, or reminder. So what not they better way to get an alert or reminder than through a text message or for that matter, you know, there’s a myriad of different sorts of messages, right, you’ve got rich communication you got you got Apple business chat, you have iMessage, you have SMS, you’d have text and WhatsApp and so on and so forth. So the technology is really lending itself to this place to meet consumers on demand in real time. And so no wonder that 97% of messages are opened and read in under five minutes. Whereas I look at my phone right now, I probably have 3000 unread emails, because most of my emails are probably either I don’t know who it is, so I delete it or it gets wound up in my spam folder. And I think that that’s part and parcel to why we have such high success deliverability rates so 99% of the messages that we attempt to send actually hit the consumer at the right time in a compliant way to keep our customers on the right path. We operate and really to two very difficult Markets, consumer fi highly regulated market, as well as telecommunications. And one of the reasons that we have very low opt out rates and very high deliverability rates is we maintain the integrity of the rules of the carriers and the carriers are trying to protect against spam. And that’s where email just failed. Only 21% of emails are actually ever written threads he’s been.

Whitney McDonald 5:28
Now if we could talk through how you actually achieve this.

Dave Baxter 5:32
Yep. So proprietary platform that, you know, we built, we just came out with our two Dotto platform that we call fintechs. Because we operate in the center of financial services, as well as tax, we coined the phrase, Fin fintechs. So how do our customers leverage the platform? There’s outbound messages, there’s inbound messages, inbound and outbound MMS. So imagine if, for example, when I said that acquisition piece, I could open up a credit card, through taps with a call center agent, we create some efficiencies for agents, right? How do we make a payment, there’s an alert or reminder. And that first payment, all we need to do is capture the funding information. And we do that in a very seamless way. So in real time, we’re extracting customer account information. So your account number, your address, the amount due the due date, and then we just capture that funding information, whether that’s your bank account information, or your card information, and then you subsequently, you know, make that make that bill pay for all other transactions. So now we’ve tokenized the funding information. We’ve stored and vaulted that funding information. So for the next transaction, it’s all driven by key keywords. Whitney, your American Express bill is due tomorrow. For $500, would you like to make a payment? Reply? Yes, and it’s just it’s really just as simple as that. So that’s how, you know we convert messages to payments, but there’s a lot more that goes into the messaging platform. We were working on text AI, where we can empower the end user of these see themselves in the status of delinquency, we can enable somebody to self cure their debt online, imagine if you know, I have a delinquent credit card, I might be able to negotiate with my bank or card issuer songs, any you know, human interaction, I can make a promise to pay, I can make a series of payments, maybe I could make a payment, make a payment right now just to, you know, satisfy satisfy the debt. We started in consumer fine, because it’s highly regulated. Obviously, that’s not to say that we couldn’t, you know, go after other verticals. But, you know, that’s kind of where we’re playing right now. And then of course, there’s leveraging our platform for marketing services, remarketing, cross sell and upsell opportunities. And what we have found is that the customer satisfaction goes up, call center times go down.

Whitney McDonald 8:22
Now I know you just gave a great an example of an added efficiency any other efficiencies that financial institutions might be able to benefit from?

Dave Baxter 8:31
Yeah, so I think, you know, going back to that whole delinquency piece, you know, we would, we believe that we could reduce charge offs by 10 to 15%, just by enabling somebody to self cure their debt. It’s not like people are, you know, think about tax, there’s a level of anonymity and a texting conversation. Whereas when you’re speaking to a bill collector, one, it’s next to impossible to capture somebody on a phone to the regulatory bodies that make it really difficult to establish right party contact, which you can do over tax. So why not meet the consumer in a way that’s non invasive, make it a little bit easier on them? So I think, you know, reducing charge offs, I think, you know, customer satisfaction goes up, I think this notion of real time. And, you know, capturing a payment right before it’s due, as I said, most payments are made on demand as a result of, you know, an alert or a reminder. And I think that, you know, you know, we obviously live in this world, it’s mobile first, but text messaging is the most widely used app on your phone.

Whitney McDonald 9:42
Now and a question about adoption for this because everyone has a phone in their pocket or is using these types of capabilities and getting text messages in adoption pretty easy to to get folks to opt in to this type of tool.

Dave Baxter 10:00
Yeah, it is. And, you know, we look at it in terms of like, adoption, but also opt out. And, you know, opt out, we opt out less than 1% of all of our transactions. And, you know, and think about, like I have, for the most part part gone paperless. So that’s another material benefit to a financial institution, think about the documents that I could send letters of consent of Bill, just not like isolated to the payment, there are many things that we could be doing to help these financial institutions, you know, reach their consumers and in ways that they hadn’t been able to and often in in real time, right. You know, think about just the, not that long ago, the the amount of clutter that you had with all of the bills that were coming into your house, and I think that there’s a much more a efficient way to be able to, you know, achieve the same outcome and do it where were the consumers at right.

Whitney McDonald 11:01
With that in mind, and Bill Pay in mind and reaching folks by text and allowing this this payment to, to happen. Where’s this all headed? What’s next in the future of payments? Or even in bill pay?

Dave Baxter 11:18
Yeah, you know, um, well, I think that we’re onto something. But, you know, the like, here’s the thing, bills are not going away. You know, there’s, I think there’s a double moat around our business. You know, there’s roughly 16 billion bills per annum 4 billion of which are related to consumer consumer finance vertical, but it’s 40% of the total spender about a trillion dollars is in and around consumer finance. And then I think a few things one, I think that the the notion of like, so we’re more of a push strategy, not a pull strategy, I think people have app fatigue. I know myself, I’m constantly forgetting my username and, and passwords for all the, you know, the different sites that I have to have a username or password password, there’s obviously two factor of that. So it’s like, it’s very complex, I think that what, you know, payments has got to be easy, fast, real time, also, and that it like, has to be great customer experience. And I think that’s where real time payments are, you know, we’re bill pay is going, you know, we live in this world of real time. Nobody has cracked the code in real time as it relates to, to build back, which is strange meat, because everywhere else in the world, real time payments is taken off. So I think you’re gonna see Bill Pay, coupled with real time. I do believe it’s mobile. First, I think it’s tax. And I think that the technology is empowering us to get there with us being able to render a bill over a text message. So there were like two other things that I think are really interesting that afford us to do. So we’re building a text wallet with network tokenization. So imagine if like, I contend that your mobile phone number is your new social security number. When was the last time you changed your mobile number and it’s very secure. Think about I know it’s Whitney, you biometric into your phone, your phone has a phone ID, you can geo located so I know it’s you, I know you made the billpay. And imagine if I could, you know you have wallets that are in your phone, imagine if a wallet was attached to your mobile number that you could use over a text message. So we’re working on that, that you can take to different billers. Hence that that network tokenization of the funding information so I can recognize Whitney, for all of your different bills without you having to continue to reenter your funding information. So I think that, you know, that is another area and no other channel can really do that in such a way that gives you ease of mind that, you know, it’s a secure transaction and the other beauty of gopay there’s very, very limited fraud, right? The likelihood that Whitney is going to pay David’s you know mortgage is zero, right? So that’s another benefit of you know, kind of proving this out and and built that

Whitney McDonald 14:34
you been listening to the buzz, a bank automation news podcast, please follow us on LinkedIn. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time and be sure to visit us at Bank automation news.com For more automation news,

Transcribed by https://otter.ai

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August 8, 2023
Global Startup Podcast: Toronto | Bank Automation News

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When considering credit underwriting for small- and medium-sized businesses, satellite heat mapping and detailed traffic patterns may not be the first data points that come to mind.

Yet these are precisely the sources of information Toronto-based startup Uplinq draws on to help extend credit to SMBs not served by traditional scoring models, co-founder Ron Benegbi tells Bank Automation News during today’s edition of the Global Startup Cities Podcast from “The Buzz.”

Uplinq, founded in 2021, allows [lenders] to evaluate the entire ecosystem of the business itself, and look at all that information in context,” Benegbi said, explaining that the company uses environmental, community and market information data in conjunction with a borrower’s credit score and financials.

The Canadian fintech has already partnered with some of the world’s largest financial institutions, including JPMorgan Chase and Citigroup, according to its website, and is active in Latin America and Africa and planning an expansion in Asia soon, Benegbi said.

Listen as Benegbi discusses how his experience as an immigrant in Toronto inspired his business, what alternative data can do for SMBs and the collaborative ethos shared by Canadian founders.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Victor Swezey 0:02
Hello, and welcome to a special edition of the buzz, a bank automation news podcast. Today is August 2 2023. My name is Victor Swezey. And I’m the editorial intern at Bank Automation News. Today is the last episode of our global startup cities series, where we have taken you to some of the most innovative tech hubs around the world to give you a look at these startup cultures and the markets they serve. Along the way, we’ve talked to FinTech founders, from the cities about the products they’re bringing to market. On this final episode, we’re bringing you back to Toronto to get a look inside Canada’s startup capital just over the border. We’ll be talking about the immigrant experience in Toronto, the collaborative ethos shared by Canadian founders, and some of the resources that have grown in the city to support them. Joining me today is the co founder of uplinq a startup using AI and alternative datasets to help financial institutions lend to small and medium sized businesses. Please welcome Ron Benegbi.Ron Benegbi 1:12
Yeah, sure, a so first of all, Victor, thanks so much for having me excited to be here. Like you said, I’m founder and CEO of uplinq in a sentence, we are a credit decisioning support technology for small business lenders. So in English, what that means is we provide institutions that lend money to small business, a lot of data and a lot of insight to help support their evaluation process and their credit adjudication process. And ultimately, though, the decision is still stays with the, with the lender, but we we support them. So a little bit about me. I’m Cyril founder, fifth startup, by the way, I’ve been told it’s my last startup, so very excited about that. But really, more importantly, as I’m an immigrant, and my family migrated to Canada in the early 70s, we were poor. We had no money. My dad was baking bread at night, to put food on the table for our family. And he went to a bank in 1973. And I know I’m dating myself a little bit, because I look exceptionally young. I was around in 73. And he asked the banker for a small business loan. And the banker told them Look, Mr. Bernanke, you really don’t qualify for how the bank lends to small business. However, I believe in people. And here’s $5,000. And my dad was able to take $5,000.19 73 start a small business, which turned into a medium sized business over time. And that really became the springboard the backbone for our family’s lives and in a new country. And I, I share that because that that really correlates directly to your question. I’ve grown up in a small business family, my successes, and my failures have come as a small business owner. So it uplink, our mission is to work with lenders and through the use of data to the use of science. And some pretty sophisticated techniques, provide them the information they need to help them extend additional working capital into the hands of small business. So in other words, say yes, when they were initially going to say no. So it is a very personal and meaningful story for me, Victor, I mean, small businesses always been underserved in financial services, no one would argue that, but if you look at the impact that COVID had on small business owners all over the world. And now if you look at the impact that, you know, the economy’s having, and we’re in this sort of uncertain times, whether some days we’re in a recession, other days, we’re not access to fair and ethical credit, has never been more difficult for a small business owner to obtain. So if we can just help turn a few nose into yeses, we would really be serving our purposes.Victor Swezey 4:19
Let’s dive in maybe on a on a technical level, a little more into how uplinks credit decisioning process actually works, we’d love to hear more about what kind of alternative data sources you use, maybe some of your most unique types of categories of data that you pull from, and you know, any use cases and ways that AI and machine learning might be involved in your credit decisioning process. I think our listeners would be really interested in that as well.Ron Benegbi 4:43
In terms of alternative data. Here’s how I would I would I would talk about this, you know for years and going back to when my dad was applying for a loan lenders would evaluate a small business the same way. Give me your For financial records, let me pull some type of credit score on you. And then from that I’ll make a credit decision. Well, that’s a very antiquated way of thinking about credit, especially in today’s day and age where the profile or the DNA of the small business owner has changed significantly over the last few years. So, you know, a lot of new small businesses have cropped up, a lot of these small businesses are sort of, you know, sort of in the gig economy, so to speak, they don’t have established financials or credit reports, and ultimately, they’re gonna, they’re set up for failure. So when we talk about alternative data, what we present to a lender is, we allow them to evaluate the entire ecosystem of the business itself. And look at all that information in context, meaning environmental data, community data, market information, data, all of these different types of data sources, in combination with traditional financials and credit scores. I’m not, you know, I’m not trying to downgrade or poopoo credit scores. But if you look at them in concert with all of these other macro and micro economic types of data sources, then you as a lender have a much better perspective on the true health of the business. So, you know, you ask the question, well, like so what are you talking about? Well, it can be things like cell phone data, it can be traffic information, it could be information from governmental sources, like, you know, the US Bureau of Labor, or the Census Bureau or Department of Housing or Department of Commerce and an on and on and on. I mean, in some cases, we actually use data that we acquire from a NASA feed of looking at satellite imageries sure, because there are all kinds of small business operators out there, it’s not just tech. So it’s, what we do is we tap into all of these sources, but we don’t just dump it on a lender, because at the end of the day lender won’t know what to do with it. We crystallize it for them, we leverage the years of experience and insights that we’ve garnered from the programs our customers have utilized over that time. And ultimately, we make a recommendation and we provide it the recommendation in a very, very detailed manner as to why we think this is a good or a bad loan. And ultimately, though that decision does stay stay with the lender. So that’s a little bit about what we’re doing and how we do it. I hope I answered your few questions. But if I missed one, just fired over? No,

Victor Swezey 8:05
absolutely. I really appreciate that. And, you know, you really piqued my interest with some with the traffic data and the NASA Data. Can you tell me a little bit more specific use case for how that might be relevant in?

Ron Benegbi 8:19
Yeah, I mean, if you if you Well, if you look at traffic data, so let’s say you’re a restaurant. Well, that’s really, really important. If we can get information about traffic flow and patterns in your specific neighborhood. That’s a really important piece of information to determine what, you know, potential future performance could look like beyond just again, traditional financials and Bureau scores. If you look at like things like I use satellite imagery, people love that. So I’ll give you a use case. So let’s say you’re a manufacturer, and you’re applying for a loan with a bank. And you’re telling the bank, listen, we run seven days a week, we’re running night shifts, because this is where we’re manufacturing this widget, whatever the widget is, well, if we have access to satellite imagery, that can then capture sort of heat patterns and heat signals over your location. And we noticed that on the weekend, it’s like there’s nothing there. But during the week, at during these hours, we’re getting different types of readings. Well, we know that they’re fibbing or they’re stretching the truth a little bit. So those are the kinds of things that the system can look at and intelligently and this is where, you know, leveraging different AI techniques helps us develop models that ultimately attenuate directly to the lender, but also specifically to the applicant itself. And that’s something that is a true point of differentiation for us against others.

Victor Swezey 9:58
And tell me about Some of the banks that you that you partner with who are some of the lenders that you use your data to advise,

Ron Benegbi 10:06
right now where we are with our business is we are in heavy proof of concept mode, with a number of banks all over the world. And we typically take that approach first, because it’s a pretty big deal when you’re going to a lender, and even though we’re not making the decision for them, you’re talking about potentially transforming their loan book, in which case, you’ve got risk, you’ve got compliance, you’ve got it security, you’ve got the business itself, all have to kind of look at this. So you know, the, the proof of concept or POC approach, like try before you buy, has resonated very well. So right now we’re working with two of the large to the top five banks in Canada, we’re working with to top 20 small business lenders in the US, we’re working with one in Mexico, we’re working with a couple in Africa, and I’m hoping to be able to share that, you know, by as early as you know, next month, we can add Hong Kong and India to that list as well. So, you know, it’s it’s, it’s a global approach in terms of we can help anyone who’s lending the small business, and anyone who wants to make some type of meaningful impact on their loan book,

Victor Swezey 11:30
in the spirit of comparing Canada and the US. Maybe if we could zoom out a little bit and compare the startup cultures in Toronto to to, you know, some of the other startup hubs around the world, maybe take Silicon Valley in the US and London? What makes Toronto unique?

Ron Benegbi 11:49
Yeah, well, you know, it’s hard for me to answer that just because I’m, I don’t know what the startup culture in Silicon Valley is like, or it isn’t Israel, or it is in London, but, you know, as far as Toronto goes, you know, I can I can talk to that it’s, it’s certainly what I feel, is a tight knit community where anyone kind of in this community is open to helping one another, there’s sort of a pay it forward mentality here that I’d like to think exists within Toronto. Yeah, I mean, the community itself has grown substantially over the years, especially in FinTech and especially with the organizations that support technology here, in Toronto. So I would tell you that, you know, you can, if you want to, you could probably attend some sort of tech event, whether virtually or in person, just about every night of the week, here in Toronto, there’s always something going on, and being a pretty large Metropolis onto its own, you’ve got some, you’ve got some great entrepreneurs in here. And, and, and a big reason for that is because, you know, Toronto has always been known as fairly diverse, and multicultural, and you have a lot of different ethnicities and immigrants like myself, and my family, who have come at one point from a different country. And you know, many of them have decided to, you know, go into the startup world. So it’s great, because we get to meet different different people from different cultures, different perspectives, and they certainly bring that added element to the entrepreneurial world. And I can tell you, it’s exciting. Like I’ve, I’ve made a lot of friends just being in the community. Not necessarily by working with these companies, but just like I said, bumping into them in advance, whether it be in person, or you know, you’re at as sort of a zoom seminar and you see them in you know, people start talking and then you, you reach out. So overall, I would tell you that look, it’s a it’s a great place to be. It’s a big city, but it feels like it in many ways it feels like a small town and that that’s how I would describe Toronto in my in my from my view.

Victor Swezey 14:20
Can you tell us a little bit about maybe how Toronto became the startup hub that it is now?

Ron Benegbi 14:26
Yeah, I mean, I would tell you that I think Toronto really started to take shape as a tech hub in the kind of early to mid 2000s. I will tell you that. A big a big jumping stone is an organization called Mars. And no, it’s not the planet and it’s not the chocolate bar company. Mars is an innovation ecosystem. I like to think of it as almost as a platform to which it It has four different tracks, like different types of startups, like clean tech, digital health, enterprise software, and fintech. And it supports these ventures through different programs that originally were government funded both federally and provincially. But over time, as you know, government funded funding naturally declined or has gotten more difficult to obtain corporate sponsorship really stepped in. So I think Mars has played a critical role in the in the ecosystem, and has grown has helped grow and develop that ecosystem over time. There are other organizations that have also played a big role. The one, the one that really resonates with me is an organization called Tech to start by an individual named Alex Norman, probably sort of Mr. Tech Canada, if I would describe Alex but it started off as a kind of a small community gathering, trying to help a few startups and all of a sudden tech to has grown into Montreal, you know, Montreal tech, and Vancouver tech. And really, it’s a, it’s a community for all startups in Canada, it’s a it’s a Canadian community, and they host a bunch of different events, both in person and online. Newsletters go out a couple times a week, you know, a lot of a lot of a lot of information has garnered from them. And then accordingly, you know, there’s a lot of, there’s some really good media focus specifically in Toronto, probably the most prominent one is organization called beta kit, which everyone kind of defers to as the sort of the go to go to source for information on all things tech in Canada. And then there are a few technology writers as well that are very well known. So, you know, over time, it has really, really grown. And as more venture capital dollars, started to enter the ecosystem, both from Canadian firms as well as US firms. And I can tell you, there are a lot of US firms who invest in Canadian companies and Toronto based companies. And I’m proud to say that most of our investors that are actually American, really helped the community grow and flourish and become what I believe is a top 20 tech community globally, as ranked by different startup reports out there. So I hope that answers your questions. I’m sure there are a lot of other great communities out there as well.

Victor Swezey 17:56
Definitely, definitely. And that’s really exciting to see. And, you know, looking forward, I guess, with with, with all that momentum, what are some fintechs that you think we should be watching coming out of Toronto?

Ron Benegbi 18:08
Yeah, I mean, there’s a lot of I think there’s just a lot of great companies, there’s, there’s one that you know, pops into my head, called lat Li, they’re, they’re sort of a hybrid FinTech kind of Prop tech. But they’re doing some really exciting things with respect to real estate, and trying to help you, you as a potential homeowner, get access to your first home. And I think that is a really, really big problem. It’s certainly a huge problem in Toronto. And I can tell you, as a father of like, she’s not a millennial, she’s a Gen Zed. It’s just really, really hard to like, buy your first home. And, and I’m pretty sure that other markets here in Canada, they’re experiencing the same thing. So they’re doing some really exciting and creative things around how they use financing to help these individuals get access to real estate that they can own. There’s also a really interesting company, sort of in the FinTech InsurTech space called walnut, which is doing some really cool things around embedded insurance and insurance again, is another problematic area where you know, rates are kind of like rates and access to fair and market market value policies are, are tough to get especially for startups and especially for fintechs. So, you know, so that companies wall not so those are the two that kind of dropped off by head but certainly there’s there’s quite a few and, you know, we’re all kind of trying to take it one day at a time. I’m in grind it out. So, you know, hopefully many, many will succeed.

Victor Swezey 20:08
You’ve been listening to the bones, a bank automation news podcast. Please follow us on LinkedIn and Twitter. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time. And be sure to visit us at Bank automation news.com For more automation news,

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August 3, 2023
Global Startup Cities Podcast: Paris | Bank Automation News

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Keeping up with expenses can be difficult for small- and medium-sized businesses, which may not always have cash on hand or ready access to capital.

Paris-based fintech Defacto is seeking to solve this by offering cash advances to SMBs through embedded lending, co-founder Jordane Giuly tells Bank Automation News during today’s edition of the Global Startup Cities Podcast from “The Buzz.”

“We believe that there’s a huge opportunity to distribute credit and distribute financing differently,” Giuly said. SMB customers can access financial services through fintech platforms they use on a daily basis.

For example, Defacto, founded in 2021, has partnered with major European fintechs and financial institutions including neobank Qonto, French bank Banque Populaire and accounting platform Libeo, which provide products to SMBs.

Listen as Giuly discusses the benefits of open banking in Europe, the rise of startup culture in Paris and how French President Emmanuel Macron has made entrepreneurship “cool.”

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Victor Swezey 0:01
Hello and welcome to a special edition of the buzz, a bank automation news podcast. Today is August 1 2023. My name is Victor Swezey, and I’m the editorial intern at Bank automation News. Today is the fourth episode of our global startup cities series, where we take you to some of the most innovative tech hubs around the world to give you a look at these startup cultures and the markets they serve. Along the way, we’ll be talking to FinTech founders from these cities about the products they’re bringing to market. This episode, we’re stopping for an aperitif in Paris, to see how the City of Lights became one of Europe’s prime entrepreneurship destinations. We’ll be talking about open banking, securing VC funding in the current economy, and how President Emmanuel Macron made startups cool in France. Joining me today is the founder of defacto. A startup using open API’s to offer embedded lending to small and medium sized businesses. Please welcome Jordane Giuly.Jordane Giuly 1:00
First of all, thank you very much for having me today. So my name is Jolene, Judy. I’m co founder and CEO a de facto. As you can tell, I’m French, I’m a Paris based French engineer. I’ve been working in startups for the past 10 years. And prior to defaqto, I was co founder and head of product at spendesk, which is a span management solution for SMBs based in Paris. So I’ve been I’ve been evolving in this, FinTech that startups, Paris seen for the past eight years now. Maybe about a word about de facto. So we launched defecto, a bit more than two years ago, with my two co founders, and we are now 18 people in the team. Basically, the problem that we’re solving is the following. So SMEs in Europe are kind of stuck in the middle between their large customers who are going to pay them in 3060 90 day terms. And the large suppliers who are asked to be to be paid very quickly. And this creates huge working capital issues for these SMEs in Europe. And we are basically, basically want to solve this. So we are offering short term financing to SMEs via our embedded lending, I would say, approach. So so first of all, what why are we doing an embedded lending to start with. So we believe that there’s a huge opportunity to distribute credit and distribute financing differently. And we are huge believer of these of the embedded finance trend, where you as as an SMB as as a customer, you can access financial services, financial products, not on your bank, I would say web interface, but from products that you’re using on the on a daily basis. And in that context, we are offering lending through different types of platforms, different types of SMEs platforms, for example, we’re working with b2b marketplaces, neobanks accounting software, financial software for SMEs and SMEs can access those financing solutions directly from their preferred solutions.Victor Swezey 3:19
And who are some of these fintechs that you partner with? Maybe say a little bit about how you embed de facto into these platforms from a technical side, and then what benefit it can provide to customers, existing customers for these fintechs?

Jordane Giuly 3:34
Yeah, so so so for the end SMBs, the the end cost customers as well as worldwide to the borders, basically, the value proposition, it’s instant eligibility results. So instead of having to go to your bank, upload your your past financial statements, which are documents that that can be like one or two years old, and wait for a few weeks. For manual reviews from your bank, with defaqto embedded in your favorite solution, you can have basically lending in seconds. And so this instant response for SME, it’s a huge differentiation because they can pilot their business and their treasury on a real time basis for the platforms that we are working with. For example, we’re working with malt with the leading freelance marketplace in Europe, they put in relationship freelancers on the sell side, and cooperates on the buy side. So we’re working with them. We are working with contoh with the biggest b2b neobank In continental Europe. We’re also working with Penny Lane, and nibio. Were accounting software and compatible software for SMEs. So what are these guys, those platforms? It’s basically differentiation they can offer have a wider set of features to their end customers, its retention and its monetization. Because they can, either they usually put these, I would say lending solutions in premium plans. So for them, it’s, it’s an upsell opportunity.

Victor Swezey 5:22
I see. And how has this notion of embedding lending into these existing FinTech platforms grown out of the open banking movement in Europe?

Jordane Giuly 5:32
Yeah, so just a word of context before. So in Europe, you have these payment service directive to which which is commonly called Open banking. That is live since 2019, I guess, in basically asked banks to expose the financial data of their customers via API. And you and following this, you have like, I would say, a huge industry, huge number of players that that got built. On top of those, you have like payment aggregation players or payment initiation players, who are basically offering to the ecosystem, access to bank data via API and also payment initiation via API. So that’s one thing on the on the one hand, and so second, so how we leverage that this de facto. So credit is not new, right? There’s always been a need for credit, there will always be need for credit. But I would say the two assumptions that we’re making is that we can innovate in terms of distribution. And in terms of scoring, so on the distribution side, we are leveraging, we are making the bet of embedded lending. Because these drives with, say, user experience to the next level. And on the underwriting side, thanks to open banking, there are huge levels of automations in terms of the data that you can access to the data that you can process to build your scoring and run your your models.

Victor Swezey 7:15
So you know, given the existence of this open banking ecosystem, and in Europe, and you know, this, this growing startup scene in France, maybe we can zoom out a bit. And can you tell me a little bit about the startup ecosystem in France, maybe compared to the rest of Europe? And then maybe also compared to the US and maybe draw some contrast there?

Jordane Giuly 7:36
Yeah, sure. So obviously, very proud of what’s going on in France nowadays. If we put this out, if we put aside all the riots and stuff, due to some I would say, you know, necessarily political reforms. I think it’s been it’s been a few years since France, in Paris, is the second hub in terms of startup investments in Europe, London, London being the first and I think Balinese one is winning against the Berlin has been winning against London for the for the past few years. So the startup scene in in Paris is pretty young, right? When I launched my first startup 10 years ago, it was like a very small ecosystem, very few French VC firms, very few investments, no accelerators, or like incubators program. And now you have like, the biggest names in terms of VC like, I don’t know, Sequoia XL index a16z, just to name a few. We’re investing more and more in Paris. They don’t have Paris offices, yet. They still kind of based in London and operating from there. But still, it’s promising. In Paris, now you have the biggest incubator of startups in Europe. It’s called stache wife. And I think it’s the it’s, it’s, it’s a place where you can have like more than 1000 startups. So so so the there’s a real ecosystem that is also maturing, you have more and more I would say, Li cons in in France. And you have I would say, more and more of a second or third time founders will manage to exit their first company. reinvest a bit as angel investor on the one hand, and launched new startups on the on the other end. So it’s both a growing ecosystem and the maturing ecosystem, which is very exciting. Yeah, and

Victor Swezey 9:46
I think, you know, from from a government perspective, President Emmanuel Macron has been involved in trying to to add some fuel to that fire in terms of France’s startup, eat Also some and that’s kind of been one of his campaign promises and something that he’s made as a as a policy goal. Can you say a little bit more about some of his policies and maybe the ways that the government has helped create and grow France, as you know, what he calls a startup nation?

Jordane Giuly 10:17
Yeah, so so. So first of all, President Macomb kind of what I say, made startups, you know, be cool, right. And so he evangelized I would say, working in startups, you know, taking risk, entrepreneurship, all these kind of values. That before him was not that was not, I would say, the preferred carrier path for friendship engineers, or business guys, etc, the preferred career paths, were more doing bank or consulting, etc. And now, I would say, being an entrepreneur, and aiming for success, ending for monetary success as well is, is more broadly accepted in France, on the one hand, and second, I think prison, Miko contributed to build, to increase confidence in terms of form investors in France. And that’s that that’s really a big part of it, right? You need to build long term confidence from investors to attract investments, to develop projects, and to kind of have this the whole ecosystem maturing. And lastly, there are more and more firms from either like the French public bank, that’s called BP and also more and more investment firms, French investment firms that are dedicating, I would say, first add funds and investments to startups and to innovation. So all of that is contributing to going the ecosystem.

Victor Swezey 12:13
So what’s the what’s the environment like in Paris now for entrepreneurs? And you know, maybe what is that? What does that have to do with you know, Paris’s rich cultural history legacy? How does that history plan with the current startup environment?

Jordane Giuly 12:29
Yeah, so. So I’ve been, I’ve been based in Paris for the past 10 years, but my, my co founders, I’ve both had some pretty extensive international experiences. So they can definitely compare Paris today, compared to Paris like 10, five years ago, and a few things we see more and more, I would say, French guys will have been to working in the US in the past few years, or in London, etc, coming back to friends, actually, and kind of importing or their knowledge or their experiences in the, in the Silicon Valley or in New York or in other startup hubs, and contribute to bringing back knowledge, expertise experience, to Paris, that that’s one thing. Another thing that I can say is that compared to other places, the cost of hiring engineers, it’s is much cheaper in Paris compared to the US. And so you can see companies that have their I would say, r&d hub in Paris, although they are there, they have their their sales and marketing, you know, functions in the US to basically sell on the on the in the US market.

Victor Swezey 13:50
So, you know, looking forward into the future, what are some fintechs coming out of Paris that you think our listeners should be watching? What are some fintechs that you think are pretty exciting coming out of Paris right now?

Jordane Giuly 14:03
We are so super, at defaqto. We really like the fintechs that allow us to bring automation to a next level. And in that context, we are working with two, I would say banking providers, which are Swan, and Mimmo bank. So swan is a banking as a service provider, and mobile bank is actually a bank, they have this credit institution license, but they build their I would say bank banking offering with an API first approach. And I think I think it’s great. And the last one that will actually mention is one of our earliest partners spinny line. We are basically you know, building I would say QuickBooks, in France and they are kind of innovating in this accounting space.

Victor Swezey 14:56
Thank you for that. Um, and you just raised a one interesting See 7 million euro securitization, in partnership with Citi and viola credit. So tell me about what you’re planning to do with with that new race.

Jordane Giuly 15:10
It’s a so it’s. So basically, we’re super happy to be partnering with Citigroup, which is one of the largest banks in the world. And we’re also working again with Viola credit, which has been our partner since since day one. And most basically, the the announce was 167 million, you’re up to 167 million your debt facility that will allow, basically de facto to originate as much loans to our end customers and refinance those loans with the two partners that we mentioned. So it’s basically for us the opportunity to lend up to 1 billion euro per year to the European SME ecosystem that we that we like a lot and work on this on refinancing those loans with the two great partners that

Victor Swezey 16:08
you’ve been listening to the bugs, a bank automation news podcast, please follow us on LinkedIn and Twitter. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time, and be sure to visit us at Bank automation news.com For more automation news,

Transcribed by https://otter.ai

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August 1, 2023
Global Startup Cities: Bengaluru | Bank Automation News

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Financial institutions are looking to personal finance management tools to increase financial literacy among customers.

Indian fintech FinMapp breaks personal finance management into four categories — planning, budgeting, saving and investing — founder and Chief Executive Kumar Binit told Bank Automation News on this edition of the Global Startup Cities podcast from “The Buzz.”

“FinMapp [is] a full financial ecosystem in one app,” Binit said, pointing to services that include a financial health check, portfolio tracking and tax planning.

Founded in 2020, Finmapp partners with more than 40 FIs in India, including $313 billion HDFC Bank and $29 billion IDFC First Bank, which give a commission on all transactions initiated through the app and allow the company to offer its services to consumers for free, Binit said.

Listen as Binit discusses the flourishing startup scene in Bengaluru, India, and explains how the city went from IT hub to the “Silicon Valley of Asia.”

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Victor Swezey 0:04
Hello and welcome to a special edition of the buzz, a bank automation news podcast. Today is July 27 2023. My name is Victor Swezey, and I’m the editorial intern at Bank Automation News. Today is the third episode of our global startup cities series, where we take you to some of the most innovative tech hubs around the world to give you a look at these startup cultures and the markets they serve. Along the way, we’ll be talking to FinTech founders from new cities about the products they’re bringing to market. This week, we’ll be making a stop in Bengaluru, India’s lush garden city and buzzing tech capital will follow Bengaluru growth from IoT hub to full fledged startup ecosystem and compare it to the developing entrepreneurial culture in the capital of Delhi. Joining me today is the founder and CEO of FinMapp, a startup partnering with financial institutions to bring financial literacy to India’s growing middle class. Please welcome Kumar Binit.Kumar Binit 1:04
My name is Kumar Binit. I’m the founder and CEO of FinMapp. It’s a Fintech startup on a personal finance management space. As far as my background is concerned, I’m from the banking industry worked over two decades in multinational banks, in various locations in India, starting from Mumbai, to Bangalore to eastern side to Northern side in Delhi. And over the two decades of experience, whatever I’ve learned, being a banker, and the pain points, which normally a common working population faces in managing the day to day finances, is where we thought those experiences will come into the picture and we’ll be able to solve the problem of financial literacy which is not only an Indian problem, but a global problems even in the developed country like US or Europe have the financial literacy issue, right. And India specifically the financial literacy rate in India is probably less than 20% Among the Indian working population, and into which a lot of common people faces day to day challenges in managing their personal finance. That is the reason why a fin map came into existing existence, we just launched fin map around eight months back. And currently we’re expanding

Victor Swezey 2:25
to tell me a bit more about how food Map Works and you know, what tools does it provide users for tracking their financial health?

Kumar Binit 2:33
So, if you see personal finance management is categorized into four core sector which is planning budgeting, savings and investing right now, most of the people what happens so, just to give you a little bit of idea in terms of Indian household income, and India, how the markets is that top is that you know, say probably 40 million people in India belongs to a high income bracket right for example, earning probably you know $100,000 plus right, which is and but there is a huge middle class segment and India right, where people earn anywhere between you know, $1,000 to say 10,000 to $50,000. Now, these are the, this this segment is what we call as a middle class segment, and around 440 million people, you know, currently is within that segment. Now, in case if they want to take personal finance advice or take a financial advisor on board, it costs money right. Now, most of these people trust their parents for their work advisors or their close friends and families right, but those, but those hamper the decision making process, the reason why is whatever advice this they are taking from the parents from the friends and families are based on their own gut feel, and their own, you know, experience and that financial product, right. So, that is why we caught you know, fan map as a tools and services what we are offering as any user can do the entire financial planning, financial health check as to what they are doing is right or wrong, they can do the entire tax planning, they can get all the recommendations and advice on all the retail financial products, which is available in within the banking circle in India. They can get their real time, you know, portfolio tracking. So, all these tools and services are provided free of cost, you know, people can take and it’s on a real time basis. It’s run by, you know, a logarithm machine intelligence and AI right. Now, along with that tools and services. What we have also provided is all the retail financial products under one umbrella so that when people do their financial planning, take recommendations and advices from us that if and actually help capture they can do once the report is generated, you know, they have to take an action in order to, you know, to ensure their financial well being and the security of the families right. Now, when they take an action, we have all the retail financial products to help them to do it seamlessly. So you can call it fin map as a full financial ecosystem in one app. And that is what funnel map is all about.

Victor Swezey 5:24
I see. So if you provide this financial ecosystem, you know, free of charge to your to your users, what’s the business model? And where does the revenue come from?

Kumar Binit 5:34
Alright, so business model is basically so any transaction which is done by our users through my app, or if they buy any product based on our recommendations based on their financial planning based on their, you know, financial health check, right, whatever critic apps actions they do, and whatever product they buy, we have partnered with more than 40 banks and financial institutions in India offering more than 200 financial products across various retail financial products available in India. So whenever they transact, we don’t charge anything from the user. You know, but the banking and the financial institutions whom we have tied up with, they pay a certain percentage of commission on the transaction value. And that’s how fun map one of the revenue models often map as

Victor Swezey 6:18
I see, and I see the some of your partners include, you know, HDFC Bank. And

Kumar Binit 6:25
so as I said, we have more than 40 Plus banking and financial institutions, including the leading banks, and and ICSA, HDFC, IDFC. Bank, then we have all the all the asset management companies, people who are offering cards, Amex is one of them, which is already there in our app. So we have all the sub sectors of a FinTech industry covered under one umbrella, whether you require for a wealth tech, whether you’re you require it for lending tech, whether you require it for insurance, all insurance products are available. So that’s how it is currently,

Victor Swezey 7:05
you know, given your experience in the in the banking sector, how would you say that this banking landscape in India differs from the one that our users might be more familiar with in, in the US

Kumar Binit 7:17
banking landscape, I’m saying the banking landscape might be more or less similar to the US, right? But the way the product is offered to the end consumers is where through the technology is where, you know, probably you can differentiate, that’s that’s a good differentiation between Indian and the US banking approach towards towards the consumers. So, you know, and for example, if you see LM there, it’s more of a problem oriented approach, we take into hands where, you know, many Indian startups focus on solving local problems, you know, addressing the needs of the Indian population. Secondly, you know, if you see, if I compare with US and India, while the United States has a more mature startup ecosystem, India’s startup scene has gained prominence in probably recent years, due to these unique factors like collaborative ecosystem, venture capital funding offices of venture capital, family offices, rising middle class and digital penetration initiative taken by the government of India, diversity and talent load, which is which is, which is also dependent upon the first class education institutions we have. So, all these things put together, I guess that is where, you know, we see a combination of problem oriented approach. Our diverse talent balloon, a government support a growing consumer market, is what differentiates between the US startup ecosystem and the Indian ecosystem startups. It’s,

Victor Swezey 8:47
it’s fascinating, and do you think that this growing startups ecosystem is part of, you know, what’s created the market for fin map and the market for people you know, who require financial literacy tools? And what do you think that the impact of an increase in financial literacy could be on the Indian population?

Kumar Binit 9:06
See, the impact of financial literacy is somehow you can see it, you can you can see it on the data of the Indian working populations. Now, for example, you know, because of this low financial literacy rate, you will be astonished to hear that 80% of the Indian working population still don’t plan for their financial future. Right? They don’t invest in financial assets, you know, real estate and gold was a traditional way of investing. My father’s forefathers have invested in real estate and gold but they have never looked into various other investment opportunities, which is there in India and still 90% of the Indian working population still don’t invest in financial assets. You know, you know, probably more than 80% pay their medical bills from savings, they don’t have adequate insurance, you know, and probably, you know, more than 50% are not aware of the cop As required for retirement. So, you know the the statistics itself tells that you know, in case if we are able to increase the financial literacy problem in India, right or financial literacy rate in India, all these figures will come down and once these figures will come down it will help us in achieving a trillion dollar economic which we are invoicing and messaging. So, it gives an overall macroeconomic situation of India will improve considerably

Victor Swezey 10:30
understood. So, you know, returning to India’s startup scene, I think a lot of people associate Indian startups with Bengaluru and you know, its reputation as the Silicon Valley of Asia. Could you maybe walk our listeners through how Bengaluru became this startup hub? What the startup scene the develop there is? And, you know, where, where maybe where it’s going today?

Kumar Binit 10:55
All right, I mean, say for example, I mean, everybody knows that Bangalore is now called as a Silicon Valley finisher. And it can be attributed to various factors, you know, including the emergence of companies like Infosys and Wipro in the 1980s. The liberalization of Indian economy and the subsequent development in the 21st century, which has happened. So, for example, you know, I just mentioned Infosys and Wipro in the 1980s you know, Bangalore had become the birthplace of these two Indian leading IT services companies. And these companies were founded by Indian enterpreneurs focused on software development and IT services, their success chakra asked bangaloreans potential as a technology help and laid the foundations of city’s growth in the IT sector, liberalisation of Indian economy, you know, added of you to the file. And that’s how, you know, development of all the technology parks, the government initiative, like special economic zones, office spaces, infrastructure, electronic city, you know, all these initiatives and amenities provided a collaborative ecosystem for the technology companies to operate and thrive. And that’s how Bangalore came into existence. And along with that, obviously, because the education system in India is so robust, and there are very superior education institutions, like you know, and the bad ideas, you know, Indian Institutes of science etc, which is based out of Bangalore, you know, the talent pool just kept on growing, and it’s not about the growth of the talent pool also, it is about sharing the knowledge. So, if you see banglori, Bangalore, Bangalore is probably, you know, the hub of various, you know, accelerators, program, incubation programs for the startups and mentorship program for the startups and it is also backed by the government of Karnataka. So, that’s how, you know, the Bangalore, Bangalore came into existence in the world, global worldspace as a Silicon Valley of Asia.

Victor Swezey 13:00
Thank you so much for walking us through that history. I think that’s really informative for our listeners, and you compare maybe being based in Delhi, but you know, I believe you’re about to open an office in Bangalore and you compare the startup scenes there a bit that tell me what it’s like to be an entrepreneur in Delhi and you know, maybe how what similarities and what differences exist between those two, which I know Delhi, you know, some are saying that now Delhi startup scene is growing really fast too and it’s almost comparable to Bengaluru. So, can you maybe compare those two cities? Yeah. So,

Kumar Binit 13:33
probably if you see, if you see the history of investments, which has happened in startup in India, specifically in Bangalore tops, the second comes to Delhi right. And obviously, if you compare the startup ecosystem or the culture probably you know, Bangalore were the pioneers of that and Bangalore is currently the number one, but in comparison to Delhi, if you see the Bangalore and the Delhi comparison, if you see I can you know, there are three prominent you know, the comparison which can look at it Bangalore as a wretched talent pool, right, that is for sure, in terms of educations and institutions and you know, the learning or the even the basic education is on the learning which normally happens in Bangalore, the startup ecosystem culture, the environment, the diversity, which Bangalore has probably Delhi is yet to see that but it is still coming up to that ladder. So, you know, probably, I can see, five years down the line probably, you know, Bangalore and Delhi will be one comparative cities to look at it. The Delhi has proven over the last two, three years that they are catching up very soon, but the Bangalore City as such.

Victor Swezey 14:50
You’ve been listening to the bugs, a bank automation news podcast, please follow us on LinkedIn and Twitter. As a reminder, you can rate this podcast on your platform of choice thank you for your time and be sure to visit us at Bank automation news.com For more automation news

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July 27, 2023
Global Startup Cities Podcast: Justt | Bank Automation News

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Processing chargebacks has long been a time-consuming manual operation for e-commerce merchants, but now AI can be utilized to streamline the procedure for financial institutions.

Tel Aviv, Israel-based fintech Justt uses AI and data insights to automate the process of chargeback mitigation—a $125 billion problem—co-founder and Chief Risk Officer Roenen Ben-Ami tells Bank Automation News during this special edition of the Global Startup Cities podcast from “The Buzz.”

“When [merchants] receive our evidence or return, they’re manually reviewing that evidence, and it’s quite a tedious process for them to do,” Ben-Ami notes. “So, we’ve been working on helping them make their process more efficient.”

Justt’s tech is designed to help vendors navigate a system in which they are typically “guilty until proven innocent,” he says. “It’s actually tailoring the solution at scale per merchant to their end user flow, their industry, so that we could get the best solution on their behalf.”

Listen as Justt’s Ben-Ami discusses automating chargebacks and his experience as a founder in Tel Aviv, the startup capital of the Middle East and a global leader in cybersecurity innovation.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Victor Swezey 0:02
Hello and welcome to a special edition of “The Buzz,” a Bank Automation News podcast. Today is July 25 2023. My name is Victor Swezey, and I’m the editorial intern at Bank Automation News. Today is the second episode of our Global Startup Cities series, where we take you to some of the most innovative tech hubs around the world to give you a look at these startup cultures and the markets they serve. Along the way, we’ll be talking to 10 tech founders from these cities about the products they’re bringing to market. This week, we’ll be traveling to Tel Aviv, the capital of Israel, the Middle East’s startup nation. For years, Tel Aviv has been churning out innovative startups across multiple verticals, including social trading platform eToro and cybersecurity firm winds. As of March, the city alone was home to 95 unicorns, according to the Times of Israel. Joining me today is the founder of just a startup using AI to automate chargeback mitigation for E commerce merchants and banks. Please welcome Roenen Ben-Ami.Roenen Ben-Ami 1:08
Great to be here. Great to meet you, Victor. Thanks for having me. So I’m Roenen, I’m the co founder and chief risk officer adjust just solves the problem of chargebacks from mine merchants at the post transaction stage. In order to explain that I always like to give an example of what a chargeback is. So we’re all on the same page. So let’s say you’re an online merchant selling a pair of shoes and a cardholder buys those shoes, it’s shipped to their address. After receiving the merchandise, that cardholder has the ability to dispute that transaction. And many times it could be an innocent mistake, they forgot what they purchased. Someone else in the family made the purchase or actual criminal activity of trying to get something for free. What happens at that point is that the cardholder goes to their bank disputes the transaction and receive the funds in return. At that point, the bank, let’s say it’s Bank of America will submit into the card scheme networks Visa or MasterCard, an actual chargeback. And the funds are ultimately taken from the merchant, I say the system is built, that you’re guilty until proven innocent as a merchant, because the funds are automatically taken from the merchant. And unless they handle the process of proving that this chargeback is illegitimate chargeback, based on the reason called what the actual claim is, then they’re going to lose those on them. That process is quite manual with many rules and regulations. And what we have done is taken a three pronged approach to solve this for merchants. And the first approach is really hands free, we realize that merchants don’t have the time, when you don’t have the knowledge or resources to deal with their chargebacks, we take the entire problem onto our shoulders and handle it on their behalf. The second point is being an automated solution. And what we mean by that is really two items. First, it’s actually tailoring the solution at scale per merchant, to their end user flow their industry so that we could get the best solution on their behalf. And then running that solution in an automated fashion because chargebacks fluctuate and come in at a random split pace across the month. And what we’re doing is actually handling those cases automatically. So it doesn’t matter if one month, it’s several 100 chargebacks. And the next month, several 100 1000s of chargebacks, we’re gonna get all to all those cases, the same quality. And the final item is really being a data driven solution. So we’re actually running tests on the responses that we’re receiving once one and what’s lost finding where our weak spots are, per issuing bank per card scheme per reason code of the actual chargebacks per payment processor, we’re able to run a B tests there find those weeks that improve on those weak spots. And overall it the win rate and the amount of funds that we recover for our merchants improves over

Victor Swezey 4:03
time. Got it and why are chargebacks such a big problem for businesses? And can you set the scene of you know, I think a lot of banks are aware that there’s been kind of a rise in fraud in recent years. Can you can you go into that a little bit?

Roenen Ben-Ami 4:18
Yeah, definitely. I’ll start by going back to 2008. During the global financial crisis when the term friendly fraud was coined, when the when there was a difficult economic situation, many more illegitimate claims were being made in the online space around chargebacks. And there was a large increase. Then if you go back to pre COVID the rise was around 25 to $50 billion dollars a year were being lost due to friendly fraud chargebacks these illegitimate claims by the card holders and since since COVID, because so much has gone online and The chargeback problem is really an online problem, the majority of chargebacks are happening there, it’s turned into over $125 billion problem and growing, it’s growing in the double digits each year as well. So it’s really a growing issue. And it’s it’s quite a problem for merchants, because I always say the chargeback process has been stuck in the past, it’s still very, very manual with many rules and regulations. The car scheme has changed their rules every year, Visa just came out with new rules around fraud chargebacks, MasterCard last year made all these changes around subscription chargebacks. And there’s many more changes that are going to come. And it’s really the merchants that need to be on top of those rules, as well as manually handling the cases. When the volumes are so high, it’s just not feasible to get to all the cases in a manual fashion.

Victor Swezey 5:52
Can Can you dig in a little bit more to the role that AI plays in? Just how exactly do you use artificial intelligence to help manage this chargeback system?

Roenen Ben-Ami 6:03
Great, so I’ll explain it by where our technology works in the process. And then and then how the AI fits into the technology. So we really started with using the this automated approach by integrating with the actual payment service providers of the merchants, for example, Stripe, Avi and Braintree and many more. So we’re actually become a sub processor on behalf of the merchant and can pull directly their chargeback data from their from their PSPs. But they’re called. And then we have our third party solutions that we use that enrich our data, meaning that we’re able to find out more information about the actual transaction, what else happened in this that specific transaction that can help us understand and tell the story better on this specific case. And then there’s also third, the data points that we can take from the merchant themselves. Many times we can go live without that merchant data. But we can improve the solution. If merchant data is added, it can integrate with our API, or it can send us a CSV report. Once we have all that data in our system, our system is able to work alongside our specialists that are tailoring the solution using our smart tools specific for that merchants needs their end user flow. And then once they’re live with the tailored solution that the AI really kicks in. Once we’re starting to receive recent results on that merchants or cases, once we receive the we receive those results, we can run tests, where are we not performing very well? Where are we can we perform better? Let’s try different data points. Let’s try different arguments, different ways of designing the templates, run different AP tests with different issuing things. So I always say that the issuing banks, the banks of America or chases of the world are reviewing this evidence. And you can see with one one issuing bank, a 60% win rate and another one, a 20% win rate with the same scenario. So each one is analyzing your evidence in a slightly different way. And you have to tailor the solution to each issuing banks preferences.

Victor Swezey 8:21
Could we go through like a banking related case study?

Roenen Ben-Ami 8:24
Yeah, that’s a great point. Because the the chargeback ecosystem doesn’t only affect merchants, in the end, it affects the acquiring banks that are actually allowing the processing for the merchants as well as the issuing banks that are issuing the credit cards to the actual card holders. And as well as the card schemes themselves. And I will say the entire ecosystem of chargebacks is quite manual, and and challenging. And we’ve actually looked into both the pain points of the acquiring banks, as well as the issuers. We even have several pilots running on the issuing side to help them deal with their pain points. But the ecosystem itself has a lot of innovation, yet to come to make this a more efficient, scalable process and a more accurate process. That’s where we really see a lot of our play here is to help make this ecosystem more accurate and making the right decision. So issuing banks when they post the chargeback, they’re actually sending it into the card scheme networks into in a manual fashion posting it into those systems. And when they receive our evidence or return, they’re manually reviewing that evidence, and it’s quite a tedious process for them to do. So we’ve been working on helping them make their process more efficient.

Victor Swezey 9:49
Maybe let’s transition now to you know, a little bit broader scale about Tel Aviv and about what it’s like to be a startup there. So you know, Tel Aviv is we all know it’s a startup hub. Um, can you explain a bit maybe the history of that? And you know, what is exactly the environment for founders like there?

Roenen Ben-Ami 10:07
Yeah, sure. I always say that Tel Aviv is interesting in Israel in general is interesting that because we’re, you know, we’re a small startup country, though we say, we look to innovation not only within the country, but across the world. And we’re always outward looking, how we could change things globally, which a lot of times, you know, I feel like in the US, or in the places in Europe, you’re trying, you’re looking inward, and how you can deal with inefficiencies inside the specific area of the world, Israel really looks outward, and not only dealing with their own inefficiencies, and they see it with many of the startups around us. It’s an amazing environment, I have to say it’s under one very small city, amazing city, but it is a small city, I always, everybody always told me to go to San Francisco experience the startup environment there. It’s a great environment, but it’s very spread out. Tel Aviv is you know, I go down the street and have coffee with our investors, I go walk over to the offices of one of our have one of our merchants that work with us. Everything is in walking distance, it’s very easy and, and collaborative in the same way. Because I can tell you, on a personal level, when we we started to build a building just there were so many other entrepreneurs out there that were helping us with things and learning what we should do and how we should do things. And now that I’m in a situation that I can help, as well, I have many entrepreneurs reaching out to me and asking for my advice on things. And we’re very collaborative, and, and allow room for encouraging each other and to to succeed because we, we’ve all been there. It’s a challenging environment. And it’s nice to be in that collaborative environment.

Victor Swezey 12:05
So, you know, Israel is renowned for producing all kinds of high quality startups, advanced startups in all different industries. But I think especially cybersecurity, and you know, you’re sort of tangential, related to cybersecurity with anti fraud and charge backs. And I was just, I guess, wondering, how do you think this emphasis on high tech security came about? And is it tied at all to Israeli history and society?

Roenen Ben-Ami 12:29
Yeah, I think there’s something there. Especially, you know, as you mentioned, cybersecurity is a really big space and high tech scene in Israel, as well as where we sit more on the FinTech side and anti fraud side. There are a lot of things that are learned in the military here, especially in the intelligence branch that can be adaptable in Israeli into society and civilian life. And I feel that, especially in the in the anti fraud space, I feel like it was a chain reaction, if you look at when PayPal purchased fraud sciences, and Israel really became a hub for the anti fraud space after that, and you saw so many startups from that were ex PayPal, employees that went out to build amazing anti fraud startups. And then it was from the next generation to the next generation because I look at myself, before building just I spent time at startup that was purchased by nove called simplex that two of the founders there were ex Pay Pal employees. So kind of has been passed down from from two different entrepreneurs. And it’s been interesting to see how this chain reaction has occurred, has become a hub for the FinTech, anti fraud sector. So there’s definitely something that you could go back to the military things that have happened there, and then chain reactions that have occurred, and just the the education moving from, from person to person.

Victor Swezey 14:08
You know, where do you think things are going in the future? And what are maybe some fintechs that we should be watching coming out of Israel?

Roenen Ben-Ami 14:16
Yeah, I think there’s a lot of exciting things happening in Israel. I can tell you, for example, we work with a company called millio, which is a really amazing company what they’re doing. They’ve been around even longer than we have, but they’re just doing some really exciting things for SMBs in the United States, allowing them to pay their their actual vendors in an easier fashion through their system, they could pay through credit card, and then they’re behind the scenes paying the actual vendors in whatever way they need to cry. Ach check are many other ways. Another one is mesh, if you’ve heard of them, which is an amazing company, there Dealing with the financial side of companies and being able to manage your finances better and having corporate cards for the employees and allows you to actually manage the finances across the company in a lot more efficient MIT way. And there’s many more the scene is really hot and exciting to be a part of it.

Victor Swezey 15:28
You’ve been listening to “The Buzz,” a Bank Automation News podcast. Please follow us on LinkedIn and Twitter. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time, and be sure to visit us at bankautomationnews.com for more automation news.

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July 25, 2023
Global Startup Cities: Num Finance | Bank Automation News

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Stablecoins are driving financial services innovations in Latin America, a growing fintech market.

Argentine fintech Num Finance is using the technology to help businesses scale operations and weather economic instability, co-founder and Chief Executive Agustin Liserra told Bank Automation News during the first Global Startup Cities podcast from “The Buzz.”

“We are seeing a lot of new use cases being developed by our partners, our clients, the retail segment,” Liserra said. “For us, it’s really, really important to build the infrastructure to allow innovation.”

Founded in 2019, Num Finance uses stablecoins, which are collateralized and pegged to currencies like the dollar, to enable lending and cross-border payments without the volatility of unpegged cryptocurrencies like Bitcoin.

Listen to the first installment of the Global Startup Cities podcast from “The Buzz,” as Num Finance’s Liserra and co-founder Mariano Di Pietrantonio discuss their experience founding a fintech in Buenos Aires, a city brimming with innovation, where ever-changing economic conditions make resilience crucial.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Victor Swezey 0:04
Hello, and welcome to a special edition of The Buzz, a Bank Automation News podcast. Today is July 18, 2023. My name is Victor Swezey, and I’m the editorial intern at Bank Automation News. Today, we’re embarking on our Global Startup Cities series, taking you to some of the most innovative tech hubs around the world to give you a look at these startup cultures and the markets they serve. Along the way, we’ll be talking to fintech founders from new cities about the products they’re bringing to market. First up, we’re visiting Buenos Aires, Argentina, a city known for its world class cuisine, beautiful architecture, passionate soccer fans and so much more. It’s also home to some of the most exciting startups in Latin America and was the birthplace of Mercado Libre, Latin America’s leading online marketplace. Joining me today are the founders of Num Finance, a startup using stablecoins to help businesses across the region scale their operations. Please welcome CEO Agustin Liserra and CGO Mariano di Pietrantonio.Agustin Liserra 1:11
Thank you, Victor. From my side, well, I’m Agustin CEO of the of the company. Just as selling a quick introduction, from my side, I have a background in in both engineering and finance, a master’s degree in quantitative finance. And then over the course of my my career, I gained extensive experience in finance and risk management. I worked as financial exposure management manager at YPF. That is the the largest oil and gas company in Argentina. And since 2016, my interest was captured by the crypto and blockchain world. And I became incredibly passionate about this this world. So I joined Bitex, one of the first cryptocurrency exchanges in Latin America. And then in 2020, I made the move to Buenbit as the CFO of the company for two years and a half.

Mariano Di Pietrantonio 2:19
My name is Mariano, as I said, and I have more than 15 years of experience as a product manager in gaming and biotech. And my list was seven years working for MakerDAO. Maker DAO for those who don’t know, is the biggest protocol in the Ethereum blockchain with more than 10 billion in total value locked in in assets. I worked there as head of growth for four years strategies, communications and partnership.

Victor Swezey 2:55
Thank you. So I guess, you know, to begin, I just wanted to ask, you know, why did you found Num Finance, you know, when did that happen? And what problem were you hoping to solve?

Mariano Di Pietrantonio 3:09
Yeah, well, that’s a question that I always like to answer, right. It’s and we founded Num for for two main reasons. Right. Firstly, throughout our experience in fintechs, and startup, we identify that one of the biggest pain points in regional in the region is the cash management, right. And the process of moving money often creates bottlenecks, right, we something in higher prices for customers, and this is regardless of the industry, right? And secondly, we observed the growing adoption of blockchain technology in the region. After the popularization of a regional dollar, sorry, sorry, additional dollar back stable coins, we know that many people were integrating these stablecoins into their lives right, but not precisely for payments, but for savings, right. And for us, this indicated that there was an understanding of stablecoins as a type of asset, right. This is one of the main points and combining these two elements, right, the understanding of this type of a crypto assets and understanding also that mobile money originally is pretty difficult, right? Combining these two we are we realized that it was possible to create the original borderless and real time money management system using local stablecoins, right. And the cool thing about this and this is most of the talk at that time that we have with Agustin is that we wanted to have an infrastructure where settlements in the region can be done almost instantly, right? And this is how Num Finance came to life.

Victor Swezey 5:04
And so can you just remind our listeners quickly what a stablecoin is, you know, how does it fit into the whole crypto ecosystem? And you know, how does it fit into your business model?

Agustin Liserra 5:16
Yeah, sure. Well, stablecoins are basically blockchain-based tokens, representations of other assets, whose value is tied to an external asset, such as national currencies or precious metals or other commodities, for example. These digital assets serves as representations of traditional currencies like the US dollars, the euro, Argentine pesos, or other commodities like gold, for example. So, essentially, stablecoins are collateralized products that can be bought or sold within the cryptocurrency market ideally to send and receive money and for the creation of real financial products. One important thing here is that there are stablecoins in the in the ecosystem that are not collateralized. In our case, we we are going for the collateralized side of stablecoins and not algorithmic stablecoins that are like a different a completely different chapter.

Victor Swezey 6:30
So, can you walk me through like a specific banking-related use case?

Agustin Liserra 6:35
Stablecoins play a crucial role in in banking use cases, specifically in emerging markets. Here in Latin America, for example, they offer several benefits that help people in this region. First, stablecoins increase accessibility, allowing individuals without traditional bank accounts to participate in financial transactions and services. One one case, I would say that is living inertia Argentina is one big exchange that is offering a payments through a prepaid card in Argentina the same as Ripio and Let’sBit that are our main partners. Second, stablecoins promote financial inclusion by bridging the gap between the unbanked and the formal financial system enabling savings payments and access to credit and lending services. And in this example, for I was I was mentioning in one bit, it is possible to convert your prepaid card into a credit card by taking a loan and doing like a buy now pay later process as you want with the quantity and installments that you prefer for for your your cash flows and and your decisions basically, then a stablecoins provide a faster and much more cost effective and secure alternative for cross border remittances. I would say that it is the the first and the main use case of crypto in general, but with Bitcoin, it was like a nightmare to to do remittances hedging the exposure of the Bitcoin volatility. So stablecoins are really a use for useful for these kinds of services. And finally, stablecoins drive financial services innovation, facilitating the development of decentralized finance applications that expand access to financial products and services in in general. We are seeing a lot of new use cases being developed, but by our partners, our clients, the retail segment. So for us is really, really important to build infrastructure to allow innovation.

Mariano Di Pietrantonio 9:21
Yeah, one one cool thing that I would like to add to that is that we are here to help the banking infrastructure that’s already place right? We know that banking infrastructure sometimes seems to move very slow, right? And there are companies that take that opportunity to provide other services what we want you to hear is to kinda marry these two things right like the banking infra with the crypto in fact right and Num Finance is doing exactly that. Right. We are covering that that gap. So people in In this region can have the services that they need, right? Just remember that emerging markets are one of the most underserved markets in terms of financial services.

Victor Swezey 10:11
And I was wondering if we could zoom out a little bit. And maybe if you could tell me a little bit about what the startup scene looks like in Buenos Aires, you know, what is the what is the funding ecosystem like? What is the startup culture like? And how do you think that that might be connected to, you know, the history and identity of the city in general?

Mariano Di Pietrantonio 10:27
Yeah, yeah, that’s, that’s a cool question. The startup scene in Buenos Aires is really vibrant and is growing like rapidly, right? The city has become a hub for entrepreneurship and innovation, attracting a diverse range of startups across well, various industries. And the startup is seen in Buenos Aires particularly is very strong in technology and fintech sectors, right. Many ministers are focused on developing mobile software, mobile applications, e-commerce platform and other disruptive financial technologies. And we are also seeing this, like really cool, significant growth in sectors like for example, health, education, agro, there’s like a bunch of different verticals in which we are seeing a really cool growth. And I believe that the I mean, there are many cases of that, why is happening. But overall what I see, it’s like when I say this turning into one of the main spots for the digital nomads, right, to their cost of living, and, and the relationship of the cost and the quality of life that you have, right? Because although it’s really cheap for foreigners in Argentina, you still can have a pretty high, high quality lifestyle here, right? I have many friends from from abroad, and they always tell me the same thing by this about the food, how the food culture here, it’s awesome. It’s a it’s a secure city, right? It’s pretty safe cities, right? It’s a pretty safe city. And you can get also to travel a lot inside the country. And since we have a pretty big country with many different climates, and very different, you know, things to visit. So yeah, I believe that those factors plays a very important role to have these resources to get more people working here, and also to create startups.

Victor Swezey 12:31
And just more generally, how would you say that the startup culture in Buenos itis in Argentina and you know, maybe even in Latin America more broadly, compares to the United States? And what you know, what are you? What are some similarities you see? You know, what are some ways that you see this startup ecosystem that’s really been, you know, growing recently, how do you see it differing from what we have in the United States?

Agustin Liserra 12:56
Yes, well, I would say that I could define the ecosystem here in Latin America, by by towards and I would say that this was applied to every single entrepreneur in the US and in Latin America, but I consider that resilience and resourcefulness are the big key points in, in Latin America. And basically, startups in Latin America face significant challenges, limited access to capital, a really, really complex regulatory environment and political and economic instability and changes from the left side of the political parties to the right. So, it is a quite difficult to, to predict the future. So in Latin America, we choose to create. So, as a result, I would say that Latin American enterpreneurs have developed remarkable resilient, resilience and resourcefulness also, we find innovative solutions to navigate these obstacles, leveraging creativity and adaptability also, a and then the market characteristics are presents some similarities and some differences. I I will remark that Latin America presents like a unique market landscape by a large population and cultural diversity. So it is not, like trivial to, to conquer different markets like Brazil, Argentina, Colombia. So it requires a really deeply understanding of this landscape to to be successful.

Victor Swezey 15:22
And yeah, so to follow up on the point, you know, you were you were speaking about some of the economic instability in Latin America. And I know that, you know, that’s been in the headlines regarding Argentina recently with, you know, triple digit year over year inflation, and that’s something that you have been struggling with. And I was just wondering, how does how has this economic instability maybe affected the startup scene? And then, you know, from the Num Finance perspective, how do you see stable coins interacting with, you know, what happens when the currency that they’re pegged to is maybe not very stable, but also do you see them as a potential solution or something that might be able to help in these kinds of economic environments?

Agustin Liserra 16:04
Yeah, well, as as you said, economic instability, make it challenging really challenging for startups in Argentina to secure traditional funding from banks and investors, a different trading conditions currency devaluation, extremely high inflation rates create uncertainties, and that leads to a risk-averse averse environment in Argentina. And also economic instability often brings challenges in terms of capital controls, delays in payment processing, restrictions to, to capital markets, also, it is quite difficult to, to understand the evolution, for example, about international wires in Argentina, and if you can do it or not, and it changes every single week. And our business model focuses on on real time, money movement, using stablecoins can provide the startups with the ability to transact swiftly, both domestically and globally. And this can facilitate operations. It is a really efficient way for cross-border payments and greater financial flexibility also.

Victor Swezey 17:43
Yeah, so thank you so much, you know, for all of that, you know, both about your company and about the situation in Argentina and the startup culture there and in Latin America more generally. I guess I just wanted to finish by asking you, you know, what, are you touched on this, but what are some fintechs that, you know, people in the banking sector, people involved with bank automation might want to watch coming out of Buenos Aires coming out of Argentina? You know, what are some fintechs that you all are, are excited about? That, you know, maybe should be on our radar?

Mariano Di Pietrantonio 18:13
Well, I mean, one of the most prominent fintechs to watch it’s, I guess, you know, it’s Mercado Libre often referred as the as the Amazon of Latin America, and while Mercado Libre even started as an E commerce platform, it has expanded into FinTech services through its subsidiary Mercado Pago. And well Mercado Pago offers and a range of digital payment solutions mobile wallets, QR code payments, and I believe that they are turning right now into this kind of super app right in which you can pretty much have everything. They also added right now deliveries and some of these services too. And since they have like most of the market on their hand, they grow like really really fast right? But the cool thing is that they are also growing in all the countries in Brazil in Uruguay in Colombia and Mexico. They are really really, really big. Another FinTech that it seems really interesting to me for the thing that I that they are doing is Ualà while is another Yeah, wallet I would say and that it has integrated a QR codes that has integrated and these Yeah, like E commerce platform to create your own e shops. They even acquire the bank in Mexico, I believe the ABC bank. So yeah, there’s like a couple of these fintechs that are gaining a lot of traction in the in the region. Yeah.

Agustin Liserra 19:49
I will add to what Marian was was saying. Something related to your question about the Latin American a landscape and it is that this kind of of successful companies are being funded by Latin American people. And it is a the reason for that is that it is quite difficult to understand the Latin American problems from outside. So I could see some challenges in for big companies such as Amazon, Apple and, and worldwide companies to introduce the products here in in Latin America, and this reflects a huge opportunity for Latin American startups.

Victor Swezey 20:54
You’ve been listening to “The Buzz,” a Bank Automation News podcast. Please follow us on LinkedIn and Twitter. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time, and be sure to visit us at bankautomationnews.com for more automation news.

Transcribed by https://otter.ai

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July 18, 2023
Podcast: BofA talks AP automation| Bank Automation News

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Bank of America is looking to AI and machine learning within its accounts-payable technology capabilities.

The $3.1 trillion bank plans to use AI for invoice scanning, including the use of AI algorithms that can extract relevant data from invoices, Lindsay Huston, managing director and head of B2B Payment Solutions in Global Transaction Services at Bank of America, tells Bank Automation News on this episode of “The Buzz” podcast.

The AI tech used now for invoice scanning is only about 80% accurate, requiring human intervention for 20% of the work, she said. However, she noted that AI advances will allow the technology to reduce much human intervention going forward.

Listen as Bank of America’s Huston discusses AP automation enhancements through AI and ML.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:06
Hello and welcome to the buzz of bank automation news podcast. Today is July 11 2023. My name is Whitney McDonald, and I’m the editor of big automation news. Joining me today is Bank of America’s Lindsay Huston. She is here to discuss the bank’s Accounts Payable automation.Lindsay Huston 0:26
Great, thank you, Whitney. And thanks for the invitation. I’m super excited to be here. So my name is Lindsay Huston, and I lead a product team at Bank of America. I’ve been in payments for about 20 years. At Bank of America. Our goal here is just to help make payments easier and digitize payments. We’re helping companies move from paper checks and paper invoices, which are costly and error prone and bad for the moment to electronic payments. We offer solutions for companies anywhere from smaller franchise operator who maybe just wants to outsource their accounts payable altogether. To many Fortune five hundreds who have multiple subsidiaries very complicated processes and requirements, we do custom electronic payment solutions to fit their needs. So either way, our goal is to make AP easier on our customers and free up employee capacity. And my specific capacity in that role is leading the product team and innovation and strategy. They’re

Whitney McDonald 1:22
great. Well talking through some of what you do work on day to day, maybe you could start off by giving us an overview. Bank of America is account payable solutions, and maybe a little bit more broadly the b2b payments solutions.

Lindsay Huston 1:36
Yeah, absolutely. Thanks. I’m really proud of what Bank of America offers. Because we really have industry leading solutions, we are always our goal is to be top to three in every category and industry ranking for our car products in our payments solutions. And we offer a range of solutions for companies of every size. And in every region. When I started the bank, many years ago, I was in a sales capacity. And I worked with companies that were we call our in business banking. So those are companies that are, you know, 20 to 5020 to 50 million in annual revenue. And now, some of those companies and those operators that I’ve known for a while those companies are now a billion dollars in revenue. And we’ve been able to grow with them with our continuum of solutions that support every size company. So I’m super proud of that.

Whitney McDonald 2:22
Now, speaking of the banks solutions, and leveraging the data in specific ways, maybe we could talk through how those solutions actually work and talk through the technology behind them.

Lindsay Huston 2:35
Yeah, absolutely. So we have individual payment products. So a company can use our purchasing card. And they might use that for materials, for example, or we offer a virtual payables for invoice to spend, or we have end to end AP automation solutions, where companies can essentially outsource their payables to us, they send us a file of the payments they want to make. And we enroll the vendors, we maintain all that sensitive account information, we execute all the company’s payments on their behalf, we make sure that those payments actually get executed and follow up with the suppliers. So that’s really a combination of not just technology, like you mentioned, but that hand holding to ensure that that end to end experience for our clients is taken care of. We also have kind of in between solutions. So solutions that can be customized to our client’s buying behavior needs. We can manage the vendor onboarding and the credentials, but then we can let the buyer choose the payment type. Or we have intelligent routing solutions where we can recommend the best payment type based on the buyers preference. And that may be skewed towards working capital or they may be focused on rebate automation. But our job is to really navigate that labyrinth of b2b fintechs find best in breed and partner with them to bring those to our 10s of 1000s of Bank of America customers. Because b2b is really having kind of a renaissance right now. And there’s some solid, mature b2b payment fintechs. And then there are dozens of newer and emerging players. And we know our customers don’t have the resources and time to meet with an evaluate all of these. So what we do on behalf of US customers is get to know all these fintax and evaluate their technologies. And not just their technologies, like I said, also their support model, because many times we see fantastic technologies can fall down if they don’t have the people behind that to make sure that the end to end experience is great for companies. So we really take that on so that buyers don’t have to go and evaluate all of these fintechs on their own.

Whitney McDonald 4:44
Did you may we take that as a step further on what that vetting process entails?

Lindsay Huston 4:51
Yeah, absolutely. So I think of America we we hold risk in very high regard. So we are Not just meeting with the companies and evaluating their leadership, we are doing things like scanning their technologies and looking for vulnerabilities. We have industry leading technologies internally. And because of the size and scale of Bank of America, we often are on the edge of seeing what fraudsters are doing. So when we partner with fintechs, this scale of what we see in our own Bank of America portfolio, we can bring that to the fintechs and say, hey, there are these new vulnerabilities. These are things to look out for. So we’re helping fintechs in that way, with our maturity to help them get better what they’re doing as well.

Whitney McDonald 5:41
Thank you for explaining that. Now, bringing in some numbers last year, your accounts payable automated solutions process $300 billion, which was up 25%. Year over year. Can you talk us through what contributed to that increase in what was driving the adoption of those accounts payable solutions?

Lindsay Huston 6:01
Yeah, actually, we’re looking at what will be 350 billion in the next in a rolling 12 situation right now. And that’s just the digital payments, there are AP automation solutions. But to your point, it’s just been tremendous growth. And I really kind of bucket that into three things here. First is just for buyers, with fraud increasing more companies are seeing the value of payments automation. So in 2022, business email compromise accounted for almost three billions in losses last year. Through our API automation solutions. We hold vendor credentials, vendor account information. We know vendor preferences, because of the networks we manage. We know what time zones the vendors operate within. And we collect all this data and watch these transactions to help prevent fraud and business email compromise and all of these things. Last year, there was a healthcare payer that received a phishing email, we identified the fraud for them, we called the supplier who was an architecture firm that was building a wing for buyers for that buyers hospital. We told that supplier that they’d been hacked. And that actually helped prevent fraud with a lot of their other buyers who had also received a phishing email and not anticipated that fraud and that that architecture firm actually ended up joining our payments network because they realize the benefits of the additional monitoring and the network solution, which goes along with that. So the great story of how we prevent fraud, not just for the buyer, but for the supplier as well.

Whitney McDonald 7:32
Yeah, great example. Thanks for sharing.

Lindsay Huston 7:34
Yeah, another thing that we see driving that growth is supply chain issues. suppliers have more leverage and more power than they have in many times. So our buyers want to find solutions that provide value to the suppliers as well. And that’s, that’s always been here. But this, the pandemic has shined a light on this. So now we have introduced a lot of options that can benefit the supplier and how they get paid. With a card payment things that are as simple as pushing the payment into a suppliers account, where typically it’s a pooled payment. We also offer not just a basic Ach, but an enhanced ACH. So the vendor gets much better reconciliation data, they get custom cashed application files, w h and w nine. So this is making reconciliation a lot easier for the supplier, encouraging them to move away from check as well. And then the industry is also evolving to offer things like proprietary interchange rates as well. So if a supplier is processing millions of spend on card or on ACH to and that cost becomes a challenge, we have a different level where you can set a one to one interchange rate on that card or on that ACH. So instead of playing two and a half percent, it can be one and a half percent. And so that helps also move spend off of check and making it more economically feasible to move that to an electronic payment type. And then lastly, a lot of that increase is being driven because everybody’s being asked to do more with less in our current economic environment and looking at a potential recession, everybody’s looking for cost savings. And this is a really well illustrated by we had a family on regional retail shopping center that does property management, and they wanted to grow but they didn’t have the help headcount to do that in their kind of very manual operations environment. What we saw during the pandemic was they were putting invoices in a folder, passing that desk to desk than going to AP for a data entry. And it’s just they’re losing a wild amount of float from that desk to desk operation. And then on top of that during the during COVID They had to send check printers home with their AP staff, which opened them up for fraud and they had to have check printing parties in the office where they wore masks and printed checks and licked envelopes. And so all of that drove them to Do AP automation because they recognize the the fraud and the risk and the opportunity there. One of the benefits here. Yeah, yeah, it was just and you know, it’s it’s not a typical, we see this a lot. Everybody is looking at, you know, a hiring freeze and reducing expenses. And so they’re looking at how can they reduce headcount or do more with less. And I think one of the really interesting things is, ultimately, as Gen Z becomes more of the workforce, they are going to find it hard to believe that so many companies still do things like sending faxes and cutting checks and walking invoices around and and I think, as we try to backfill boomers who roll off of AP departments, Gen Z’s aren’t going to be willing to do that kind of work. So we’ll have to automate these roles, because there’s not going to be as many people who are willing to work with paper in the way that many have in the past, especially, again, older millennials and Gen Z’s who have grown up in a digital native environment.

Whitney McDonald 11:06
Yeah, I mean, this brings up several areas of opportunity, I’m sure for Bank of America in areas of innovation in this space. So based on this adoption, and move toward digital away from paper, anything that you guys are focused on working on for the second half of 2023.

Lindsay Huston 11:28
Yeah, for us, we’re looking at a lot of AI and ML, right, I’m super excited about the convergence of these, and it’s something that’s super a passion of mine. Everyone’s looking at the most the initial use cases for our worlds would be like, we do invoice digitization right now, and, and with digitization across most companies right now that offer that they’re doing what we call zonal invoice scanning, they’re looking for heading level information in one zone, and they’re looking for detail level information in another zone, and it’s maybe 80% Correct and 20% manual human has to come in and correct information. So now we’re seeing AI for invoice scanning. And the AI algorithms can actually extract relevant data for the invoices much better. That vendor detail the invoice number dates and amounts, they can actually anticipate what formats that should be at. And so that’s going to reduce a lot of human intervention that goes along with invoices. zation.

Whitney McDonald 12:33
Yeah, and you know, of course, all things right now are all AI and how to make it work best for for different financial institutions. So definitely an area that you can look into AI for.

Lindsay Huston 12:45
Absolutely.

Whitney McDonald 12:47
Now, looking ahead, and it doesn’t have to be super short term, but just kind of trying to get a gauge of what payments technology you’re looking out for, or what innovation is exciting right now that you’re monitoring.

Lindsay Huston 13:01
Yeah. For us, I think it’s so interesting. And and I kind of go a different direction with this question. We are always looking forward about the modernization opportunities. But as as just thinking about this question, I think about our customers and once friend of mine for them. And there’s still so much opportunity in what our customers are dealing with in basic API automation. That, you know, we’re excited about real time payments, and we’re excited about machine learning. And we’re excited about AI. But, you know, we, I was meeting with the other day, a well known company that is building rockets, and they are still 100% Check. And they struggle with getting off check. And they struggle with a fraud there. And I think many times there’s actually an inverse relationship between the maturity and technology, technological savviness of a company, and their API automation maturity. And so we’ve seen that repeated many times we another one is a hybrid car company we work with, they have grown super fast, they’ve modernized the modern car technology. And still they’re very behind in how they run their AP. So I get super excited about all the technological advances that the products may offer, but there’s still tremendous headway that we can make. across our entire portfolio of buyers, there’s still a ton of opportunity to help companies mature and advanced their API automation. If the listeners take away anything, it’s that as we look towards the end of the year, potential increase in rates and potential for recession. It’s a really good time to look internally into companies, AP departments, and there’s just tremendous opportunity to digitize As payments to reduce fraud, to improve operations to reduce expenses to be able to take people and put them on more valuable activities by driving automation within their company. So, thank you again for the opportunity to come and meet with you. This has been really fun and maybe we can do this again sometime.

Whitney McDonald 15:22
You’ve been listening to the buzz, a bank automation news podcast, please follow us on LinkedIn. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time and be sure to visit us at Bank automation news.com For more automation news,

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July 11, 2023
FIs Invest in AI for Customer Loyalty | Bank Automation News

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Financial institutions are looking to their digital capabilities as customer retention becomes more dependent on technology and less on loyalty.

“If we talk about millennials and Gen Zs of the world, they do not have a lot of loyalty inherent with their financial institution,” Rahul Kumar, general manager of financial services and insurance at cloud contact center Talkdesk, tells Bank Automation News in this episode of “The Buzz” podcast. “Banks have realized that in order for them to earn any sort of loyalty in these younger segments, they truly need to invest in technology.”

Banks need to meet their clients wherever they are in their journey, Kumar said, noting that technology allows FIs to offer personalized experiences based on preferences. One client may prefer a chatbot while another may prefer a phone call.

Banks can look to AI to create those personalized experiences, Kumar said. AI allows for a proactive approach to customer experience through predictive analytics.

“AI offers a much broader opportunity to drive a lot of personalization, a lot of opportunity to predict the reason somebody’s reaching out to you and proactively offering them solutions and resolutions for that [reason],” he said.

Listen as Kumar discusses how FIs can enhance customer retention through tech investment.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:01
Hello and welcome to the buzz of bank automation news podcast. My name is Whitney McDonald and I’m the editor of bank automation news. Joining me today is general manager for financial services and insurance at Talkdesk, Rahul Kumar he is here to discuss how FIS can improve customer retention through tech spend, including the use of artificial intelligence to meet clients wherever they are.Rahul Kumar 0:23
Thanks, Whitney. Glad to be part of the bank automation news podcast. Thank you for the invitation. I’m Raul Kumar. I am the general manager for financial services and insurance at talkdesk. So really tasked with driving our industry motions, Product Strategy go to market, as well as I’m responsible for managing and maintaining the strategic relationships with all our customers in the industry. Just a background about myself almost 15 years in the industry, primarily working with banks and credit unions, giving them the opportunity to leverage technology and innovation to drive business outcomes. So very familiar in this space very excited. I’m very passionate about you know, small to medium sized banks and credit unions truly realizing the potential of technology. From a top down perspective, talkdesk is a global globally recognized leader in the customer experience space, we offer a cloud native Contact Center as a service solution. Really purpose built to meet meet industry needs, that is one of the key differentiators of talkdesk. So not only do we have a contact center platform, we offer a contact center platform built for banking built for insurance built for healthcare and retail industries. We are in the midst of a cloud revolution when it comes to contact center. So we offer a truly cloud native omni channel AI infused platform that can really accelerate trying to value for our customers. So hope that gave you a bit of insight about myself and talk to us. And really, like I said very excited about this conversation today.Whitney McDonald 2:16
Well, thank you again for joining us and we can get into the conversation now we’re going to be talking through customer experience customer loyalty and where technology fits into all of this would be great if you could first start by setting the scene and explaining explaining the current state of customer loyalty today.Rahul Kumar 2:38
Sure, you know, in right now, banking, that is an interesting inflection point, especially with the macro economic conditions, some of the recent you know, large bank failures, banking, as an industry overall has a lot of scrutiny and eyes on it, but when it comes to customer loyalty, there is also an heightened need from for banks to prioritize customer retention. And there are a myriad of reasons for it, banks have realized and it has always been the case. But more so, now that every bank is looking at cutting costs, reducing costs, driving efficiencies, it is well known that the cost of acquiring a new customer is much higher, at least four to five times higher than the cost of retaining a customer. So in the in in that light, there’s a heightened need and you know, all banks have made customer loyalty and customer retention, a key part of the forward looking strategies, there is also enough research to suggest that customers at least in the US today, bank with three to four institutions, you know, when you when you think about that, banks have also realized that there is an opportunity to increase share of wallet just by focusing on their existing customer base and in driving revenue utilizing what they have, rather than what they can go after. They have also realized that the customer segmentation especially the younger segments, you know, if we talk about millennials, the Gen Z’s of the world, they they do not have a lot of loyalty inherent with their financial services institution. They are looking for ways where they can maximize the experience the you know, an institution that can meet their needs. So, banks have realized that it is, you know, in order for them to earn any sort of loyalty in these younger segments, they truly need to invest need to invest in technology need to invest in, you know, ways where they are positioning themselves as a desired partner, to these customers, and really also challenge the standard way that they have typically operated, which has primarily been a supplier of financial products and services, rather than truly offer these customers our partnership that ensures their financial wellness and financial well being. So those are some of the ways you know, I look at, you know, customer loyalty, the importance of it, and their invite investments in technology in is paramount for banks, as they’re looking or prioritizing customer retention and loyalty as a key part of their strategy.

Whitney McDonald 6:04
Let’s take those tech investments one step further, I’d love if you could share a little bit more about those digital capabilities and the role that they do play in getting customers to stay at a financial institution or pulling in whether it’s those younger millennials or Gen Z years, or any any customers, what technology really are those folks looking for?

Rahul Kumar 6:30
Yes, with me, I think, if you look at I always like to lead with a question. To everyone, where do you bank? And more? The the the most relevant answer that I get to that question is I bank on my phone? Everybody today? You know, most, most, I would say a majority of the population have shifted, you know, the relationship into the mobile device. So if you are in the mobile device, if you’re working, you know, if you’re interacting, engaging with your, with your banks, on the mobile device, it is paramount for banks and credit unions to realize it, realize that and make sure that the experience that they are offering to their customers is, is at par or is exceeding the experience that customers are getting from other providers, be it you know, everybody, sort of our customers today, say and compare if I can do something on Netflix, or I can do something on Amazon, why does my bank not allow me to do something like that? So yes, that is where investing in in mobile apps, investing in the digital capabilities sitting inside the mobile app, enabling feature sets, you know, giving customers the ability to not only look at information, but take action when when when they see something is off, right. So take action quickly. So when as an example, when you think about you, you know, as a customer, I go into my app, I see something that is a miss or is incorrect, I want my bank to be able to resolve that issue as quickly as possible. It and I can choose the channels that I want to use to engage with my bank to resolve that issue, I can reach out if I am a customer that likes chat, I should be able to chat if I’m a customer that likes to be on a call, I should be able to initiate a call directly from the mobile device. If I’m a customer that does not want to talk to a human agent, I you know I for for simple things I should be able to engage with, with a virtual agent and you know, or a bot and get the issue resolved. So, you know, the capabilities when you think about in terms of digital, that banks need to think about, they need to think about, you know, investing in platforms and solutions, that that can offer the customers a unified experience, irrespective of the channel that they are engaging in. So and ensure that the channels are not siloed. So what I mean by that is when the conversation may start as a chat, can transform into a voice call with with an agent, if it’s complex enough, can turn into a cobrowse session. You know, where the agent can can do that can offer that hand holding and on offer an elevated white glove experience. And banks need to be able to do all of that seamlessly while ensuring that the experience never breaks. So those would be some of the things when you think about digital and its impact on banking. It’s truly To help not only meet customer expectations, but truly offer a unified banking experience, irrespective of where the interaction starting or ending?

Whitney McDonald 10:11
No, no, you talk through the more omni channel experience meeting customers where they’re at. I don’t think that we can talk through financial services right now without bringing up AI, of course, can you discuss a little bit about the role that AI is also playing in all of this technology and customer loyalty? And where that fits into the puzzle?

Rahul Kumar 10:33
Yeah, absolutely. So when I look at AI, and you know, in terms in the context of banking, traditionally, AI has been looked at as a capability, yes, a technology capability. The focus that banks and credit unions have had is to leverage AI flecked interactions and other mechanism to drive more efficiency in, you know, accommodate for cost savings, when it comes to call deflections, could I deflect a call and save those costs, because obviously, sell services a cheaper channel of service, seven to eight times cheaper, at times. In so they’ve invested in in bots, they have invested in both on the chat bots or voice bots, you know, but I think one of the shortcomings of those investments that I have seen is that they’ve invested more into those capabilities as a standalone point solution, without really thinking through the overall experience that they want to offer their customers, what happens if the bot is not able to service the customer. So my challenge with, then the challenge that I sort of throw to banks and credit unions is how are you truly incorporating AI as a core part of your customer experience strategy, rather than just treating that as a technology capability, there is so much more that can be done with AI, the power that AI has to offer banks and credit unions is to move from a more reactive approach to customer service, to a more proactive approach to customer service, AI and machine learning has evolved to a point where you don’t really need the customer to tell you the reason they are reaching out to you, or you don’t really you should already be knowing and with the data you have about them, the reasons that they have called in the past, you should be able to predict, you know, why a customer might be reaching out to you. So I think, you know, investing in chatbots, and voice bots is, is, is perfectly fine. But I think AI offers a much broader opportunity to drive, a lot of personalization, a lot of opportunity to predict the reason somebody’s reaching out to you and proactively offering them solutions and resolutions for that. But then also utilizing AI, you know, on inside your organization’s empowering your employees with the information they need, you know, to drive a better experience for them. So, yeah, AI is important. You know, but it really needs to work in ways, you know, outside just being another technology capability that that you’ve invested in.

Whitney McDonald 13:59
Yeah, that all makes sense. And of course, having those predictive capabilities in place on that know of, of investing in these capabilities. How can a financial institution ensure that they are being strategic about these investments? I know that you talked through back end investments as well as customer state facing AI capabilities? How can you be sure that you’re investing in areas that are either going to offer ROI or retention or more efficiencies from from employees as well?

Rahul Kumar 14:36
Yeah, I think, great question. Whitney. I think the way we at talkdesk in general have been advising our customers is to really look at the value. You know, really look at the outcomes that you’re looking to achieve, you know, and then building out a strategy A both from a customer experience perspective, but also your technology strategy should be outcome driven. You know, a lot of times, we still, at times run into situations, where if organizations are not prioritizing, you know, the value, and the outcomes that they are looking to achieve through investment, they end up doing nothing. Like they, they spend a lot of time evaluating, you know, partners and vendors and capabilities, but because the outcomes are not defined, they end up sticking with what they have, because there’s no real quantification of the ROI that they can expect. So, you know, we might, you know, at least from my perspective, my two cents on this, as always lead with value, always define the business outcomes that you’re looking to achieve, and then start to connect capabilities, be it AI, be it omni channel, be it the cloud to as as a mechanism or enablers to help you achieve those business outcomes. So, each fundamental capability be a chatbot whether it influences your handle times, whether it influences you know, your cost of doing business, whether it influences you know, the or reduces your the cost of servicing your customer, or so, I think that’s the way I approach it, it technology investments cannot be looked at, in silos, without truly, you know, putting some real thought or know around the value each of those capabilities can help your organization achieve. So we, you know, sometimes especially when it comes to customer experience, we look at a look at it as a quadruple quadruple impact. How is the investment impacting your customer experience and the ease of doing business with you as an organization? How is the investment, looking to improve your employee experience? You know, you is the investment going to help you retain your employees and delight them and empower them with the tools and information they need to become much more productive and efficient. How is it improving the agility of your of your organization and to to proofing you. Future, basically future proofing your growth ambitions by offering you scalability and flexibility? And finally, what impact is it going to have in terms of accelerating time to value for you as an organization? How quickly can you start really realizing ROI? So I think that is that is the quadruple sort of value framework that I think organizations should start looking at, and then start to sort of creating their own business as well as technology strategies to achieve it.

Whitney McDonald 18:25
So we talked about investment strategy, we talked about the omni channel approach and the importance of of digital capabilities right now, wondering if you can give some insight into what technology customers are really gravitating toward right now. What are those top technologies that are pulling people into certain financial institutions?

Rahul Kumar 18:47
So I think one of the trends that we’re seeing is, customers accept expect a seamless, frictionless experience with their financial services institutions, there’s a you know, they are they get fully frustrated, when the experience is fragmented, if it is impersonal, and then the it leads to frustration for them when their issue sets are not resolved, as you know, quickly and efficiently. So customer expectation is, you know, meet me in the channels that I want to engage with you ensure that the experience remains consistent. Irrespective of the channel that I’m engaging with you. Make sure that you know you know who I am before you know, you are because I am trusting you with my finances. You should already know who I am without having me having to go through multiple hoops to even identify myself to you And then ensure that my my, my experience is is not only fast and seamless, but it is also secure. So if you look at some of those aspects that the customers are expecting, you start to tend to gravitate, gravitate towards, Hey, we should eliminate our investment in point solutions and prioritize investment in platforms, we should invest in platforms that help us achieve some of the things that we’re looking to do platforms that can give back and enable omni channel platforms that are infused with AI platforms that, that ensure data and privacy security, a platform that can mitigate fraud early and often in platforms that that can aggregate information from multiple places that drives efficiency and productivity in the way customers get serviced. So I think if you think about that, then some of the capabilities that truly come to mind is, you know, we spoke about omni channel, that’s a no brainer. We spoke about AI, but AI that is pragmatic. That is completely, you know, it could be voice bots, but Smart Voice bots, smart chat bots, that can truly understand industry terminology that can execute industry workflows, capabilities, such as voice biometrics as a better way to authenticate customers, you know, fraud tools that that do phone validations spoofing detection, to ensure that fraud is not entering into the banking ecosystem. And then, you know, Agent desktops that can aggregate information, and help agents deliver the best white glove experience possible, where they are more focused on delivering the customer experience without having to worry about the systems they need to work or look at to deliver the best experience possible. So all in all, you know, you know, I might have been biased when in terms of my response in terms of contact center, but truly investing in a modern customer experience platform that brings all of these capabilities together, and ensures the best experience possible for both customers as well as employees is what I think, you know, is going to be the future cloud based AI infused modern, flexible, scalable platforms. I think one of the things that the last thing that I’d like to say is banks, it is high time banks and credit unions realize that complacency and an approach to be a follower is not good enough. I think the you know, there is enough technology capabilities out there in the market that are, you know, partners and vendors that they can truly they should start truly evaluating today, rather than waiting and sitting in status quo, because it is truly an existential crisis for them. The customers continue to evolve their expectations continue to evolve. Good enough, is no longer a strategy that that I think banks and credit unions need to can afford to continue to follow. So it’s all about you know, investing today, future proofing, looking at the customers what their expectations are, and pivoting their strategies to truly address and delight customers, both from a product and services perspective, but also from an experience perspective. So that’s, that would be my final two cents on this topic.

Whitney McDonald 24:11
You’ve been listening to the buzz, a bank automation news podcast, please follow us on LinkedIn. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time and be sure to visit us at Bank automation news.com For more automation news,

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July 3, 2023
Podcast: Envestnet President Farouk Ferchichi on hyper-personalization | Bank Automation News

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Financial institutions can look to data to create hyper-personalized experiences within back- and front-end operations — if they prioritize data and analytic literacy throughout their institutions.

In creating a hyper-personalized experience, banks must lay a “foundation of culture change around data, machine learning, artificial intelligence and machine learning literacy,” Farouk Ferchichi, president of data and analytics provider Envestnet, tells Bank Automation News in this episode of “The Buzz” podcast.

Through data and analytics, machine learning and AI, banks can benefit from improved risk management for decisioning, fraud detection and anti-money laundering capabilities, he said. Additionally, clients benefit from a personalized experience based on their needs.

Listen as Envestnet’s Ferchichi discusses how financial institutions can harness data to create efficiencies in front- and back-end operations.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:09
Hello, and welcome to the buzz of bank automation news podcast. My name is Whitney McDonald and I’m the editor of bank automation news. Joining me today is president of investment Farukh for Chi Chi. He’s here to discuss the importance of harnessing the power of data through technology for added efficiencies and better understanding of the target audience.Farouk Ferchichi 0:29
Yeah, first of all, hi, Whitney. Very good to see you. Again. For the listening audience, my name is food for cheeky and I am the president of investment data analytics line of business, also known to many of your listeners as Yodlee. Or like we’d like to joke internally and say, it’s usually to point out, and we serve globally, the banking tech and wealth industry with an alternative data and AI powered bank as a service platform that brings together candidate data connectivity, that data intelligence, and hyper personalized digital money management experiences in one integrated ecosystem.Whitney McDonald 1:15
Now, I know that investment has been busy, definitely for the past six months or so can you talk through some of the latest upgrades and newest offerings that investment has been working on?

Farouk Ferchichi 1:29
Yeah, I mean, investment generally has had a lot of new things going on. And particularly here in the investment DNA line of business, a lot has happened over the past 18 months. For example, in wealth management. We we launched our wealth data platform, or as our clients know it as w DP. And the focus there has been on driving and measuring growth for our clients and their end clients that are investors. In the banking, retail banking space, we have a lot going on, we moved from a pure aggregation to a leading open banking and alternative data value providers. We invested more in the AI and machine learning and data and AI governance, in addition to kind of grow in our open banking footprint here in North America and abroad. And as a result, we were able to launch kind of a new alternative data solutions. We were actually our alternative credit, credit data solutions, our small business solution, and continue to kind of improve our customer facing digital experiences, taking kind of PFM, or the personal financial management experiences to the next level growing from what is used to be just a money discovery tool, to more of a planning and execution of your money management experiences, like tokenization, for verification and identity check, goal setting savings, and subscription management to name few, of course, all of powered by our unique set of alternative data, database, as well as the analytical capability we have behind.

Whitney McDonald 3:14
Now with these recent launches in mind and new products in mind. And of course, being in the business of data. I’d love to start things off by talking about really just the importance of harnessing data and analytics for financial institutions. Can you talk us through that?

Farouk Ferchichi 3:29
Yes, Whitney. When you think about this, going to generally speaking about the socio political and economic challenges that are facing us in the world. Financial institutions are obviously not immune, and are seeking a stable business that can overcome these headwinds, and the way they do that is balancing the risk management side of the business and the growth side of the business. And more importantly, in these days with a finite number of resources available to them. So as such, we see the the weight and the importance put into harnessing the power of data is essential. It is a great tool, especially these days to enable automation and productivity on one hand, enabling faster and cheaper development and augmentation of risk management processes, while enabling at the same time, deeper sales and product and marketing, segmentation. Enabling them truly to differentiate product offering with a higher degree of targeting.

Whitney McDonald 4:53
Now getting into the how behind that, really, how can FIS approach this stuff? Energy of harnessing data, and maybe you can talk through where the technology element comes in. Yeah,

Farouk Ferchichi 5:07
as we listen as we constantly are listening and talking to our clients and at the same time finding ways to respond and serve their needs, we see data, AI, and technology harness in delivering, particularly the hyper personalized services to the employees in the back office, to do their job better and of course, the front office to their clients to achieve their financial needs. Focusing on the employee and the back office, we see it in risk management improvements of existing like credit risk management processes for decisioning. Around 40, decision a credit decisioning, loss forecasting or even collection, as well as in the operation risk management processes side automation, we spend improvement and augmentation, we see it in that including like fraud detection, security monitoring, as well as augmenting anti money laundering capabilities. We see also an emerging an emergence at scale of deploying data and AI in the product planning aspect, understanding the lifetime needs of existing clients and build that personalized roadmap of what and when a given a product can be offered at what price to a given customer. We also see marketing segments become segmentation becoming more refined, allowing the organization frankly to meet the needs of their clients in a more hyper personalized way. And again, hyper personalized not to fall but at the right time, using the right omni channel that is preferred by the clients. But But honestly, Whitney for this data, AI and analytics harnessing to be deployed effectively. We see companies who are the most effective at this have laid the foundation of a cultural change around quote unquote, data and artificial and machine learning artificial intelligence and machine learning literacy. The second area where we see is laying the foundation of data governance as well as model governance processes, and then data and AI infrastructure, preferably in the cloud. When you have these type of technical prerequisites, I like to say, they will enable a faster and more effective and efficient deployment of the data AI and technology combined. Obviously, we preach this to our clients all the time, different clients and advisors at different stages of their maturities. But all three areas are our areas we are actively consulting at no additional cost to our clients because for them to take the to get the most return that to achieve the most return from our products and services. We work with them in laying that prerequisite foundation.

Whitney McDonald 8:43
Now speaking of that foundation, and I know you touched a little bit on some of the areas where you can see the benefits coming through the back end, the front end, maybe we could dive a little bit deeper into some of those benefits that a financial institution might see from leveraging their data and analytics.

Farouk Ferchichi 9:02
Yeah, absolutely. We do. We do believe the benefit to end consumers or clients is access to the promise of open finance powered by open banking. And that promise needs to be featured with this hyper personalized product options that they have access to that they don’t today at a competitive price at the right time. On the flip side, for the financial institution, the benefits are to grow and be more productive. And when I say grow, I mean via higher client retention, and more holistic kind of lifetime relationship and value from from the customers they managed today. Above and beyond. They’re onboarding new clients and prospects. And then when I say productivity, I mean the ability to scale and differentiate back office processes around product management, servicing and marketing plans and strategies at a lower cost.

Whitney McDonald 10:07
Now wondering if you can discuss or give an example of a bank or client that’s doing this? Well, what data has brought to a certain financial institution or client? May we talk through what some of those time savings, or monetary savings might look like?

Farouk Ferchichi 10:29
Yeah, absolutely. This is one of my favorite topics with me because, well, while whether internally within our organization, or more importantly, with our clients, we like to talk a lot about value captured. Because we as a business to business to the end client kind of provider, we want our, we want to make sure that our products and services are adding measurable value. And without naming names. As you know, many of our clients are using our open banking and value add data, AI and digital technology services. And I want to share with you a couple, a couple of examples, one of our one from one of our large ePHI clients, where the customer retention across multiple product line and segments has improved incrementally because customer considering another firm, maintain their accounts and respective fee revenue. For the composite organization or this organization, I’m talking about the total risk adjusted operating profit increased due to this improved client retention, believe it or not by 24 million over a three year period of time. And then another client of ours who’s a little bit smaller mid size, regional FYI client, increase their wallet chair. And that’s due to more efficient reliable aggregation of financial data of their customer and supporting behind the scenes, the intelligence and the analytical services that we provide customers account managers get increased visibility into the assets, they do not actively managed with their client, which allow them to put the programs together to compare services of external assets and design internally products and solution to bring those assets in house leading to fundamentally an increase in revenue to the new due to the new asset and their management, the composite three year risk adjusted, which is the value metric that we use with our clients and confidence, profit increase for this FY with the effect of this wallet share program to a total of $15 million.

Whitney McDonald 12:58
Yeah, when you put it into those quantifiable measures, and I know that you said of course there’s the value capture and value add it really the the times the money savings, the time savings at all, it all adds up. And that’s exactly what you guys are working toward anything that we didn’t hit on that you wanted to be sure to. Yeah.

Farouk Ferchichi 13:25
If I may, I know everyone speaks about Chad GPT, and AI and generative AI and all of that. And a couple things I’d like to share are three things one, it is reality, you cannot run from it, it is coming. We invest in it in general and DNA. In particular data analytics line of business in particular, we’ve been using generative AI for years right now. It is our core IP behind the scenes, we just didn’t advertise it because it was not something that people talk about. It’s too technical. But we do now, the second thing I would say the best application that we see and we invest in it of how to implement charge GPT it is going to be on the back office to gain back credibility with the employees with the organization. It will be focused on automation creating content at scale, and so on. And then finally, I would say for charge GPT to be accepted and rollout at scale that has to be a deliberate effort around AI literacy as well as AI governance and openly discussing the AI ethics and The Good, the Bad and the audio that comes with it.

Whitney McDonald 14:52
You’ve been listening to the buzz a bank automation news podcast please follow us on LinkedIn and as a reminder, you can rate this podcast on Your platform of choice thank you for your time and be sure to visit us at Bank automation news.com For more automation news

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Whitney McDonald

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June 27, 2023
Envestnet Group President on Hyper-personalization | Bank Automation News

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Financial institutions can look to data to create hyper-personalized experiences within back- and front-end operations — if they prioritize data and analytic literacy throughout their institutions.

In creating a hyper-personalized experience, banks must lay a “foundation of culture change around data, machine learning, artificial intelligence and machine learning literacy,” Farouk Ferchichi, group president of wealthtech giant Envestnet Data & Analytics, tells Bank Automation News in this episode of “The Buzz” podcast.

Through data and analytics, machine learning and AI, banks can benefit from improved risk management for decisioning, fraud detection and anti-money laundering capabilities, he said. Additionally, clients benefit from a personalized experience based on their needs.

Listen as Envestnet’s Ferchichi discusses how financial institutions can harness data to create efficiencies in front- and back-end operations.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:09
Hello, and welcome to the buzz of bank automation news podcast. My name is Whitney McDonald and I’m the editor of bank automation news. Joining me today is president of investment Farukh for Chi Chi. He’s here to discuss the importance of harnessing the power of data through technology for added efficiencies and better understanding of the target audience.Farouk Ferchichi 0:29
Yeah, first of all, hi, Whitney. Very good to see you. Again. For the listening audience, my name is food for cheeky and I am the president of investment data analytics line of business, also known to many of your listeners as Yodlee. Or like we’d like to joke internally and say, it’s usually to point out, and we serve globally, the banking tech and wealth industry with an alternative data and AI powered bank as a service platform that brings together candidate data connectivity, that data intelligence, and hyper personalized digital money management experiences in one integrated ecosystem.Whitney McDonald 1:15
Now, I know that investment has been busy, definitely for the past six months or so can you talk through some of the latest upgrades and newest offerings that investment has been working on?Farouk Ferchichi 1:29
Yeah, I mean, investment generally has had a lot of new things going on. And particularly here in the investment DNA line of business, a lot has happened over the past 18 months. For example, in wealth management. We we launched our wealth data platform, or as our clients know it as w DP. And the focus there has been on driving and measuring growth for our clients and their end clients that are investors. In the banking, retail banking space, we have a lot going on, we moved from a pure aggregation to a leading open banking and alternative data value providers. We invested more in the AI and machine learning and data and AI governance, in addition to kind of grow in our open banking footprint here in North America and abroad. And as a result, we were able to launch kind of a new alternative data solutions. We were actually our alternative credit, credit data solutions, our small business solution, and continue to kind of improve our customer facing digital experiences, taking kind of PFM, or the personal financial management experiences to the next level growing from what is used to be just a money discovery tool, to more of a planning and execution of your money management experiences, like tokenization, for verification and identity check, goal setting savings, and subscription management to name few, of course, all of powered by our unique set of alternative data, database, as well as the analytical capability we have behind.Whitney McDonald 3:14
Now with these recent launches in mind and new products in mind. And of course, being in the business of data. I’d love to start things off by talking about really just the importance of harnessing data and analytics for financial institutions. Can you talk us through that?Farouk Ferchichi 3:29
Yes, Whitney. When you think about this, going to generally speaking about the socio political and economic challenges that are facing us in the world. Financial institutions are obviously not immune, and are seeking a stable business that can overcome these headwinds, and the way they do that is balancing the risk management side of the business and the growth side of the business. And more importantly, in these days with a finite number of resources available to them. So as such, we see the the weight and the importance put into harnessing the power of data is essential. It is a great tool, especially these days to enable automation and productivity on one hand, enabling faster and cheaper development and augmentation of risk management processes, while enabling at the same time, deeper sales and product and marketing, segmentation. Enabling them truly to differentiate product offering with a higher degree of targeting.

Whitney McDonald 4:53
Now getting into the how behind that, really, how can FIS approach this stuff? Energy of harnessing data, and maybe you can talk through where the technology element comes in. Yeah,

Farouk Ferchichi 5:07
as we listen as we constantly are listening and talking to our clients and at the same time finding ways to respond and serve their needs, we see data, AI, and technology harness in delivering, particularly the hyper personalized services to the employees in the back office, to do their job better and of course, the front office to their clients to achieve their financial needs. Focusing on the employee and the back office, we see it in risk management improvements of existing like credit risk management processes for decisioning. Around 40, decision a credit decisioning, loss forecasting or even collection, as well as in the operation risk management processes side automation, we spend improvement and augmentation, we see it in that including like fraud detection, security monitoring, as well as augmenting anti money laundering capabilities. We see also an emerging an emergence at scale of deploying data and AI in the product planning aspect, understanding the lifetime needs of existing clients and build that personalized roadmap of what and when a given a product can be offered at what price to a given customer. We also see marketing segments become segmentation becoming more refined, allowing the organization frankly to meet the needs of their clients in a more hyper personalized way. And again, hyper personalized not to fall but at the right time, using the right omni channel that is preferred by the clients. But But honestly, Whitney for this data, AI and analytics harnessing to be deployed effectively. We see companies who are the most effective at this have laid the foundation of a cultural change around quote unquote, data and artificial and machine learning artificial intelligence and machine learning literacy. The second area where we see is laying the foundation of data governance as well as model governance processes, and then data and AI infrastructure, preferably in the cloud. When you have these type of technical prerequisites, I like to say, they will enable a faster and more effective and efficient deployment of the data AI and technology combined. Obviously, we preach this to our clients all the time, different clients and advisors at different stages of their maturities. But all three areas are our areas we are actively consulting at no additional cost to our clients because for them to take the to get the most return that to achieve the most return from our products and services. We work with them in laying that prerequisite foundation.

Whitney McDonald 8:43
Now speaking of that foundation, and I know you touched a little bit on some of the areas where you can see the benefits coming through the back end, the front end, maybe we could dive a little bit deeper into some of those benefits that a financial institution might see from leveraging their data and analytics.

Farouk Ferchichi 9:02
Yeah, absolutely. We do. We do believe the benefit to end consumers or clients is access to the promise of open finance powered by open banking. And that promise needs to be featured with this hyper personalized product options that they have access to that they don’t today at a competitive price at the right time. On the flip side, for the financial institution, the benefits are to grow and be more productive. And when I say grow, I mean via higher client retention, and more holistic kind of lifetime relationship and value from from the customers they managed today. Above and beyond. They’re onboarding new clients and prospects. And then when I say productivity, I mean the ability to scale and differentiate back office processes around product management, servicing and marketing plans and strategies at a lower cost.

Whitney McDonald 10:07
Now wondering if you can discuss or give an example of a bank or client that’s doing this? Well, what data has brought to a certain financial institution or client? May we talk through what some of those time savings, or monetary savings might look like?

Farouk Ferchichi 10:29
Yeah, absolutely. This is one of my favorite topics with me because, well, while whether internally within our organization, or more importantly, with our clients, we like to talk a lot about value captured. Because we as a business to business to the end client kind of provider, we want our, we want to make sure that our products and services are adding measurable value. And without naming names. As you know, many of our clients are using our open banking and value add data, AI and digital technology services. And I want to share with you a couple, a couple of examples, one of our one from one of our large ePHI clients, where the customer retention across multiple product line and segments has improved incrementally because customer considering another firm, maintain their accounts and respective fee revenue. For the composite organization or this organization, I’m talking about the total risk adjusted operating profit increased due to this improved client retention, believe it or not by 24 million over a three year period of time. And then another client of ours who’s a little bit smaller mid size, regional FYI client, increase their wallet chair. And that’s due to more efficient reliable aggregation of financial data of their customer and supporting behind the scenes, the intelligence and the analytical services that we provide customers account managers get increased visibility into the assets, they do not actively managed with their client, which allow them to put the programs together to compare services of external assets and design internally products and solution to bring those assets in house leading to fundamentally an increase in revenue to the new due to the new asset and their management, the composite three year risk adjusted, which is the value metric that we use with our clients and confidence, profit increase for this FY with the effect of this wallet share program to a total of $15 million.

Whitney McDonald 12:58
Yeah, when you put it into those quantifiable measures, and I know that you said of course there’s the value capture and value add it really the the times the money savings, the time savings at all, it all adds up. And that’s exactly what you guys are working toward anything that we didn’t hit on that you wanted to be sure to. Yeah.

Farouk Ferchichi 13:25
If I may, I know everyone speaks about Chad GPT, and AI and generative AI and all of that. And a couple things I’d like to share are three things one, it is reality, you cannot run from it, it is coming. We invest in it in general and DNA. In particular data analytics line of business in particular, we’ve been using generative AI for years right now. It is our core IP behind the scenes, we just didn’t advertise it because it was not something that people talk about. It’s too technical. But we do now, the second thing I would say the best application that we see and we invest in it of how to implement charge GPT it is going to be on the back office to gain back credibility with the employees with the organization. It will be focused on automation creating content at scale, and so on. And then finally, I would say for charge GPT to be accepted and rollout at scale that has to be a deliberate effort around AI literacy as well as AI governance and openly discussing the AI ethics and The Good, the Bad and the audio that comes with it.

Whitney McDonald 14:52
You’ve been listening to the buzz a bank automation news podcast please follow us on LinkedIn and as a reminder, you can rate this podcast on Your platform of choice thank you for your time and be sure to visit us at Bank automation news.com For more automation news

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Whitney McDonald

Source link

June 27, 2023
Podcast: Payments innovation post-SVB | Bank Automation News

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The collapse of Silicon Valley Bank, First Republic Bank and Signature Bank has companies looking to technology providers to ensure they have the right payment strategies in place.

Companies are looking at “due diligence, redundancy, single points of failure,” and wondering whether they are set up with the correct providers globally, Ralph Dangelmaier, chief executive at global payment platform BlueSnap, tells Bank Automation News on this episode of “The Buzz” podcast. “These are the things now people have to look at when they’re setting up their payment networks around the world.”

The bank collapses also present an opportunity for payments innovation in areas of super apps, embedded banking and platform upgrades, Dangelmaier said. “I think we’re on a small pause; innovation is down a little bit because we’re in the middle of this sort of transition period — but it is going to spike back up.”

Listen as BlueSnap’s Dangelmaier discusses payments innovation, lessons learned from collapsed banks and the state of global payments rails today.

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 0:01
Hello and welcome to The Buzz, a bank automation news podcast. My name is Whitney McDonald and I’m the editor of bank automation news. Joining me today is Ralph Dangelmaier chief executive of FinTech BlueSnap. He is here to discuss the growing need for payment innovation, learning experiences from recent banking collapses in the current state of payments rails.Ralph Dangelmaier 0:23
Great. Hi, I’m Ralph Dangelmaier, the CEO of Blue snap. Bluesnap helps merchants accept payments globally. And we do that through our platform, which we call the payment orchestration platform. And what that does, it allows merchants to accept payments in hundreds of countries with hundreds of payment types, hundreds of currencies, what makes it unique is that we can process those payments in 47 countries around the world, which allows merchants to have a higher authorization rates or less declines and lowers their cost of processing payments. So that’s what blue snap does around the world for merchants.

Whitney McDonald 1:08
Well, thanks so much for joining us. We’re definitely in a unique environment right now in the financial industry. I figured we could kick things off by talking about the recent collapses from SBB, first republic, Signature Bank and of course, the crypto environment as well wondering if you could kick us off with some lessons learned takeaways, just from your perspective on what’s been going on in the past several months.

Ralph Dangelmaier 1:35
Great. Well, I think there’s a lot of lessons learned here. I mean, boy, have we had a turbulent ride, right? I mean, COVID came, everything started booming, nobody could do anything wrong. And then whammo, everything hit. And I think the lessons learned are that you really can never put all your eggs in one basket. Right? So the people that didn’t have multiple bank accounts, that people that weren’t prepared for either higher interest rates, or were prepared for backups on their bank accounts. We had, I think a story that didn’t get told well is a lot of these banks were processing payments for people. So not just payroll, but actually payments. So we heard of 1000s of merchants that were down for the weekend processing payments. So really, it’s a redundancy story is one here that I think is the big lesson learned is where are you redundant? Where are your single points of failure if you have a problem? So that’s one big lesson. I think the other thing you mentioned, and I’ll just touch on it simply is you could not do a podcast or you could not do a story without someone bringing up crypto, crypto, crypto, crypto, it was everywhere. And I think some people understood it, some didn’t. And now we’ve seen crypto collapse. So we had this banking collapse and crypto classes the same times really, really think made people nervous. And I’ll throw a third thing in there as lesson learned, is this Buy now pay later was literally the hottest thing ever. And so you’re constantly like borrow money and spend everything you can to grow and get into crypto and do buy now pay later. And all of a sudden, all three of those sort of stuff came tumbling down and merchants were left hanging Wait a man, this was my strategy a year ago? And now what do I do? So I don’t think I’ve seen so many real hot trends, crash, or really take this deep dive in so rapidly in any period of time and payments. So due diligence, redundancy, single points of failure, am I setup with the correct providers globally? These are the things now people have to look at when they’re setting up their payment networks around the world.

Whitney McDonald 3:58
Now, speaking of payment networks and payment rails and where we stand today, maybe we could just talk through the current environment and what exists today. Before we talk about the good stuff, the innovation.

Ralph Dangelmaier 4:13
Yeah, so what we ended up talking to a lot of our customers about is, you know, they get confused. So if you think about it, there’s hundreds of companies, hundreds of territories or countries out there, they all have their own payment rail in their country, right. So they all have their own like Pay Pal in their own countries. And then you have these global networks. There’s about seven of them, right like China, UnionPay and Visa and MasterCard, American Express, and when do I use them? And then there’s bank transfers that happen like ACH or EFTPS in certain countries. And now there’s real time gross settlement which is happening, which is like fed now, and open banking sort of in another little Avenue Over in Europe, and this is confusing people. That’s really what the message here is they’re confusing. What rail do I use? For what customer type? In what country? In what currency? And what does it cost. And so I think what’s happened is we’ve taken something that was very simple. When you use sort of ACH for payroll, you do buy things online with a card, and the smartphone and the innovation and the worlds can, again, smaller is confused everyone, because now there’s literally hundreds of wallets around the world. And they got to work on hundreds of different connected devices. And you’re trying to work with hundreds of currencies, and people that are just confused. So I think trying to really map out payments, and what rails you’re going to use as part of your product plan when you roll things out. Like let’s catch people doing it right, like people like Uber, or maybe Intuit. That’s where I think the rail conversation really comes about. And usually if you’re selling outside of your own country, you have to educate yourself on what’s the right rails that aid process for those customers outside of the country. Whitney,

Whitney McDonald 6:12
if we can take that a step further, what are those conversations look like? How do you know that you are selecting the right payments? Well, especially with more coming to market fed now coming in July? How do you know you’re making that right? Choice? Yeah,

Ralph Dangelmaier 6:29
so it really comes down to is what it? Who’s your customer? I know it sounds simple, but it’s who’s a customer? Is it b2b is a b2c? Is it a mix? How does that customer now what’s the way it likes to pay? So there’s a payment method called ideal, which does about 70% of all online transactions. In the Netherlands, right? So that’s how people want to buy as a consumer. Bigger business may want to pay with a bank transfer, or something called SEPA over in Europe, right? Very similar United States, right? Where we pay with small transactions use in cards and big transactions, we’ll probably use an ACH or wire, that wire now might move to a Fed now. So you really need to look at who’s my customer base? Where are they located? What’s their preferred currency? What’s the preferred payment method? What’s the dollar amount? Because if it’s $100,000 payment, you’re probably not going to put that on a credit card. But if it’s a $10 payment, you most likely are? And what’s the work involved in the back office on collecting payments? And how much work it is? So there’s a little analysis that has to be done by the company to figure out what does make the most sense based on who my customers are? And that’s really the question that I know we spent a lot of time to is who’s your customers BBB Z both is an invoice, you know, they buy online, and that’s helped figure out what then is the most optimal payment method that you need to offer on your checkout to really cater to those customers.

Whitney McDonald 8:07
So one of the things that comes up is that that confusion that you’re hearing from customers, there’s friction in this process, maybe we can shift into some innovation talk here where there is opportunity for innovation in payments, and the importance of innovating within this space.

Ralph Dangelmaier 8:26
So there’s been so much innovation in payments in the last 15 years is one of the I think it’s a second most invested space by private equity firms in the world after biotech. We’ve seen all of it come with the invention of lots of cool things right? Apple Pay By now pay later crypto, all the things we mentioned. So are we going to stop innovating? No, I think we’re on a small pause innovations down a little bit because we’re in the middle of this sort of transition period. But it’s going to spike back up. And where’s innovation going to spike? At least from our point of view? Well, I think absolutely real time payments and open banking those concepts. cutting out the middleman is absolutely going to be a spike. I think you’re going to see this concept of super apps, right? Where Why am I going to log into so many different apps? Why do I have so many of a wallets on my phone to check out? And it really, you know, it looks like, you know, just a confusing menu. I mean, I was buying something the other day from a well known retailer and they must have had it looked like a NASCAR racetrack there was so many stickers on there. I’m like, which one do I pick to choose to buy? So it’s making things so we’re going to see that consolidate in my opinion, you’re gonna see so many wallets. I think the other thing you’re going to see is the concept of pain more in what I call ubiquitous or common currency is going to change right and right in the changing things back and forth. So think of like a common Euro that we’re going to see around the whole world, we’re all using a single currency, sort of what Bitcoin is trying to do, I think you’re gonna see innovations in FX. And the other one that I think is kind of one of my favorites is, you’re going to see platforms, which really run companies, if you think about it, right, the likes of whether it’s Salesforce or HubSpot, or Intuit, or SAP, or Salesforce, they’re really running, they’re the heart of what runs these companies, right in this specialized ERP and CRM systems per industry, they’re going to start offering banking services, you’re going to be able to open your bank account as a law firm, or accounting firm or school or camp, you’re gonna be able to open your bank account on your platform, and you’re gonna be able to form payments, and you’re gonna get lending there, it’s already started to happen, we’ve seen about, we’ve done a survey ourselves. And we’ve seen a lot of outside data that says about 10% of the platforms today are serving up and opening bank accounts. And the trend is being called embedded banking or embedded payments. And you’re gonna hear a lot about that over the next 10 years that this business is gonna go from very little to potentially a trillion dollar business in the next years. And that’s one of my favorites, because I think it makes it easy. It’s frictionless for the merchant. And when they’re filling out their application to sign up for Intuit, or Salesforce, they’re also opening the bank accounts and to do something different. And they don’t have to go do this coding integration, hire system integrators to do it, which we have a huge problem in the world with technical debt, right? Everything requires technical resources, and we just don’t have enough of it. So I think that’s ripe for disruption and innovation right now and where we are in the market.

Whitney McDonald 11:45
Now, with all of those examples in place, and different opportunities within the payments industry, what are you looking forward to or expecting from the payments world? Whether it’s innovation or reimagining money movement? What are you looking forward to or watching for even working on?

Ralph Dangelmaier 12:03
Yeah, well, I’m gonna follow up on my past theme, I’m really looking forward to watching these, these platforms starting to sell on open bank accounts and how powerful they become. And I think it’s going to be a big shift in banking, I’m going to think the SMB business is not going to go to the bank anymore. And I think you’re gonna see lots of bank closures, I think you’re gonna see a lot less use of cash. You know, cash is still rising every year. And the people don’t believe that, but they really are. Because, globally, cash is on the rise, especially as we get into tough economic times. So I’m looking forward to see that. And I think as soon as, as we come as recession, we’re gonna see explosion of investment and innovation on those topics I mentioned earlier. It will really I don’t know when it’s gonna exactly happen. But my guess is every time we’ve been through one of these things, when it was 1999 2000, we had a we had a sort of a low in the internet, and then boom, exploded. We saw another low in Oh, 708 the smartphone came along and exploded. We saw COVID Law things and we came out things exploded. I think we’re gonna see a real mass investment and explosion of innovation. Probably 2425 is what I see happen. And it’s just fun watching these companies, you know, kind of start and bloom into something very interesting.

Whitney McDonald 13:26
You’ve been listening to the buzz, a bank automation news podcast, please follow us on LinkedIn. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time, and be sure to visit us at Bank automation news.com For more automation news,

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Whitney McDonald

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June 20, 2023