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Tag: AB – Technology

  • Did the OCC hire a con artist to oversee fintech?

    Did the OCC hire a con artist to oversee fintech?

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    The Office of the Comptroller of the Currency announced in March that it had set up a new division to oversee fintechs and banking as a service, which it called the Office of Financial Technology. To run the unit, it hired Prashant Bhardjwan, whom the OCC said had “nearly 30 years of experience serving in a variety of roles across the financial sector,” to the position of Deputy Comptroller and Chief Financial Technology Officer, effective the following month. 

    But an investigation conducted by The Information reporter Michael Roddan has found that Bhardwaj’s resume contained many easily discoverable lies.

    Through a Freedom of Information Act request to the OCC, Roddan found that Bhardwaj had listed C-level technology roles at several large banks on his CV. He also found that Bhardwaj hadn’t worked at any of them.

    “On his resume, Bhardwaj claimed he was the chief information officer at Ohio-based Fifth Third Bank between 2006 and 2010, a role that reported to the chief financial officer and oversaw a $330 million budget,” Roddan wrote. “The bank — one of the largest consumer banks in the midwest — never employed Bhardwaj, a spokesperson said.”

    Roddan reported that Bhardwaj’s resume stated he was a director of information technology at Citi between 1994 and 2000, but that the bank has no record of his employment.

    “He also claimed to have held the role of chief information officer and digital transformation officer at Ohio-based Huntington Bank from 2010 to 2015, reporting to the CEO and the board and managing a $250 million budget while overseeing a team of more than 500 employees,” Roddan wrote. “However, the position of chief information officer was held by other people during that time period. One of the men who held the role said he had never heard of Bhardwaj. Huntington declined to comment.” Bhardwaj could not be reached for comment.

    An internal memo Roddan saw listed the prior roles Bhardwaj cited. The public press release did not mention any of them.

    Sources also told Roddan that Bhardwaj is 42, belying the “30 years of financial industry experience” the OCC cited in its March press release.

    In response to several questions about Bhardwaj and the OCC’s hiring and vetting process, an OCC spokeswoman said, “the OCC does not comment on personnel issues.”

    Acting Comptroller of the Currency Michael Hsu mentioned Bhardwaj in an April 19 speech. After that, it’s hard to find any record of Bhardwaj’s work at the OCC or anywhere else. In September, the OCC named Donna Murphy, who had been with the agency since 2013, as the new chief of its fintech and baas office.

    Industry observers were shocked that the OCC had hired someone whose resume contained falsehoods that could have been easily uncovered in a background check.

    “Quite frankly, this aspect of this incredible story is the most gobsmacking,” said Michele Alt, co-founder and managing director at Klaros Group. “Large banks are subject to continuous, on-site supervision by OCC exam teams.” In other words, the OCC has examiners embedded full-time at Huntington, Citi and Fifth Third.

    “They are also subject to specialty IT exams,” Alt said. “These teams would have interacted with the banks’ CIOs and other senior IT managers. I am very surprised that Bhardwaj’s vetting did not include checking with these exam teams.”  

    Some wonder about Bhardwaj’s motive and mindset.

    “The question that fascinates me is Bhardwaj’s psychology,” said Todd Baker, a senior fellow at the Richman Center for Business, Law & Public Policy at Columbia University and managing principal of Broadmoor Consulting. “How did he ever think he was going to get away with this? Once he was inside the OCC, his claims that he had held senior executive positions at Fifth Third and Huntington would inevitably be exposed as false by the banks themselves and the examiners covering those companies. What was the point of the whole thing?”

    The OCC faces challenges in hiring senior technology leaders, Alt noted. 

    “The OCC — like all government agencies — cannot pay market rates for this talent,” she said. According to The Information, Bhardwaj was paid a $300,000 salary. 

    This is not enough to attract top tech talent. 

    “A $300,000 salary seems like a lot, but a senior bank tech executive would be paid five times as much,” Baker said. “So I can understand why the OCC jumped when this guy’s resume crossed someone’s desk. But sometimes something seems too good to be true because it is, and the hiring process clearly failed here. That’s the lesson for the agency going forward.”

    Technology oversight is not the OCC’s primary job, Alt pointed out. 

    “Most OCC examiners have finance, accounting and similar degrees that are highly relevant to the OCC’s core bank supervision mission,” Alt said. “These OCC professionals are talented and dedicated, but they are not themselves technologists. This can make it difficult for the OCC to evaluate a candidate’s technology chops.”

    But more than anything else, Bhardwaj’s hire suggests a due diligence failure, she said. 

    “Vetting — rather than a bigger hiring budget or technological prowess — was the only thing necessary to uncover the lies in Bhardwaj’s employment application,” Alt said.

    Alt also worries that Bhardwaj was given access to highly sensitive systems and data. “If the OCC were a bank, it would be cited for a violation of the interagency guidance on third-party relationships, which requires a bank to conduct due diligence on third parties before onboarding them,” she said. 

    Baker warns against using this incident to discredit the OCC.

    “While this is deeply embarrassing for the OCC, it isn’t the first time that a brazen fabulist has fooled smart people before being found out nor should it be used as an excuse to chase Acting Comptroller Hsu out of office or stymie the Biden regulatory agenda,” he said.

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    Penny Crosman

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  • Big Tech companies’ latest forays into financial services

    Big Tech companies’ latest forays into financial services

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    How much should traditional financial institutions fear the creep of Big Tech firms into banking, payments and prospective superapps?

    Mega technology companies such as Amazon, Apple, Meta and Alphabet, the parent company of Google, occupy the tricky space of being both a vendor and perceived threat to traditional financial institutions. X, formerly known as Twitter, is making its own noises about entering financial services.

    On one hand, these companies’ credit cards, buy now/pay later products and deposit accounts depend on traditional financial institutions or fintechs to get off the ground. Banks are also increasingly migrating to cloud services offered by Amazon and Google. On the other hand, they periodically play with the idea of rolling out financial products to their massive customer bases that would compete with bank partners. 

    Some of these firms could be examined and supervised by the Consumer Financial Protection Bureau as early as 2024; the agency’s director, Rohit Chopra, has expressed concern with restrictions Apple and Google have placed on their mobile wallets.

    None of the companies mentioned have taken steps to obtain a banking license, so for now they need the support of financial institutions to offer bank products. Moreover, these entities have no desire to become banks themselves, said Peter Wannemacher, principal analyst in digital banking at research and consulting firm Forrester, in a recent interview.

    “Our research has more consistently pointed to tech titans being overstated or misunderstood as a threat to traditional financial services providers rather than as an unseen or underappreciated threat,” he said. “Bank executives have tended to be more worried, at least in the short term, than was appropriate.”

    Still, potential threats lurk in the long term view, especially in two key areas.

    One is the tendency of Big Tech firms to build products that offer a “superior value proposition for people with financial needs,” said Wannemacher. He points to Apple Card and its easy transaction views as one example, an area where many big banks fall short in their mobile apps, according to Forrester research.

    “Banks still basically chase other people’s ideas,” said Wannemacher. “They’ve fallen short at thinking of new ideas, products, and ways of interacting with people.”

    Another growing area of concern is these firms’ ability to lock customers into their ecosystems and nurture brand loyalty — which could provide a built-in customer acquisition funnel when they introduce financial products.

    “If the battle is for attention and affection, traditional financial institutions are in trouble,” said Wannemacher.

    Here is a closer look at the latest investments Amazon, Apple, Meta, Google and X have made or are teasing in their financial services arms.

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    Miriam Cross

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  • Banks are excited about AI, but that doesn’t mean they’re using it

    Banks are excited about AI, but that doesn’t mean they’re using it

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    Bankers show a lot of interest in advanced AI, as well as a daunting list of challenges, according to American Banker’s innovation readiness survey.

    Adobe Stock

    Artificial intelligence is a top priority for banks, but applying the technology can be slow-going as due diligence, potential regulation and limited resources bog down the process.

    Banks believe AI and machine learning are the technologies most likely to create a competitive edge in the next two years, according to recent research from Arizent, American Banker’s parent company. However, while the technology is buzzy, less than 30% of respondents to the Arizent survey named chatbots or generative AI as key to their strategies.

    At American Banker’s AI Summit last week, Amir Madjlessi, a banking industry advisor at Salesforce, said in a panel that larger clients have allotted resources to invest in AI.

    “In this environment where capital expectations are rising, the fight for deposits is real,” he said. “I think there is this reality check of, we can’t do all things. But gosh, if we don’t get started, we’re going to be so far behind that irrelevance might be a problem, too.” 

    Additionally, while banks are more bullish about AI than other technologies, the excitement isn’t overwhelming. Per Arizent research, 20% of banks named AI or machine learning as the technology they’re most excited about, and 15% listed generative AI and chatbots. Law and consulting experts have said that banks are hesitant to deploy the technology due to risk and potential federal regulation.

    Christine Livingston, a managing director and leader of AI at Protiviti, said in an August interview that nearly all banks are evaluating AI opportunities, but few have started applying the emerging technology meaningfully. Major banks like JPMorgan Chase, Goldman Sachs and Morgan Stanley have been able to execute AI strategies, but smaller banks struggle with access to the talent and technology needed for similar innovation.

    Even technology leaders at larger regional banks expressed the importance of easing into innovation. Michelle Grimm, Fifth Third’s senior director of conversational AI, said at the AI summit the institution is focused on a “crawl” before it can “run” with generative AI. The bank is testing the technology on internal uses, like writing job descriptions for recruiting purposes.

    “We’re a bank, and risk always seems to be top of mind,” Grimm said during a panel. “People want to be quick to say, ‘No, we can’t do that.’ But we’re trying to say, ‘What can we do then?’ How do we get people comfortable [enough] to allow us to take some of these use cases that have been bubbling up and saying … we can try this with these controls.”

    Eyvonne Mallett, an attorney at Loeb & Loeb, said in a September interview that banks are trying to implement AI that takes future regulation into account, and complies with existing rules around anti-discrimination and data privacy.

    “The challenge right now is, there’s a lot of talk about AI regulation, but there hasn’t really been much traction or movement,” Mallett said. “So sitting in the role of the bank, I would really be thinking about those policies and regulations that are already in place, and how AI impacts them.”

    Limited resources also curb banks’ roads to innovation. Forty percent of respondents to American Banker’s recent survey cite limited resources as the biggest challenge. Especially among smaller banks, vendors and fintech partners are key to bridging the gap to emerging technologies.

    At American Banker’s AI Summit last week, Thomas Novak, chief deposits and payments officer at Visions Federal Credit Union, said the institution doesn’t have the bandwidth for internal development. He added that since the credit union relies on partnerships, asking questions about a fintech’s data and AI models is key for diligence.

    Protiviti’s Livingston said in September that it’s imperative that banks allot the resources to support the innovations.

    “I think everyone’s going to need to do it, or they’re going to be out of the game,” Livingston said. “You need to either identify or hire the appropriate resources to support and sustain these innovations. It is going to be part of your core infrastructure in your core tech stack. And I think it will be very hard if not impossible to compete without having AI as a core part of your enterprise architecture.”

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    Catherine Leffert

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  • How banks can cross the ‘uncanny valley’ as AI becomes more human

    How banks can cross the ‘uncanny valley’ as AI becomes more human

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    One might suspect that most bankers — especially community bankers — fear that generative artificial intelligence could generate misinformation or that the biggest banks will leave smaller rivals in the dust as they invest hundreds of millions of dollars in the advanced technology. 

    Yet, bankers have said in recent interviews they’re more worried that if they deploy advanced AI such as the enterprise version of OpenAI’s ChatGPT, the technology might work too well and confuse or creep out customers who have trouble discerning whether they’re talking to a human or software-generated bot. 

    This concern has a name — uncanny valley — and it’s been around since 1970, when Masahiro Mori, then a professor of engineering at Tokyo Institute of Technology, coined the term and wrote an essay about it. 

    “I have noticed that, in climbing toward the goal of making robots appear human, our affinity for them increases until we come to a valley, which I call the uncanny valley,” Mori wrote.

    Industrial robots are fine, in his thinking, because there’s almost nothing humanlike about them. But if a robotic arm is covered with material that looks and feels like human skin and by “adding a bit of fleshy plumpness,” he said, it can appear more like a person.

    “When we realize the hand, which at first sight looked real, is in fact artificial, we experience an eerie sensation,” Mori wrote. “For example, we could be startled during a handshake by its limp boneless grip together with its texture and coldness. When this happens, we lose our sense of affinity, and the hand becomes uncanny.”

    Gene Fichtenholz, vice president of digital strategy and engagement at Meriwest Credit Union in Mountain View, California, agrees with this concept and believes virtual assistants that mimic human voices can enter uncanny valley territory.

    “There are a bunch of companies that are working on incredibly powerful resemblance of human speech,” he said in an interview. “They design voices to go up and down, to be curious and to transmit the empathy of conversation.”

    His team deliberately designed Meriwest’s virtual assistant, Scout, to not seem human. It’s depicted as the letter “M” with cartoonish eyes and hands.  

    “It’s a gender-neutral creature of some sort,” Fichtenholz said. “It’s super cute, but it’s not human. If it’s completely not human, but cute, people can relate — this is fun, I know I’m talking to a machine, but it’s a cute machine. As soon as it becomes too realistic, the creepiness is there.” 

    Meriwest, which has $2.2 billion of assets and originally served only IBM employees, launched Scout in February around the same time it was switching to a new digital-banking platform. The digital assistant, which is based on technology from Kasisto, saved hundreds of hours of call center representatives’ time, Fichtenholz estimated, by taking some of customers’ questions during the transition.

    But even a cartoonish virtual assistant could still put off customers who have an aversion to change and new technology, Fichtenholz noted. 

    “We, on the banking side, create something new and we think it’s going to be really exciting, but for some people it’s not exciting, because you’re changing things,” he said. “That translates to the digital assistant as well — why is this thing talking to me?” 

    A considerable portion of customers do not want to play with new digital-banking technology, but just want to be able to click on three buttons and be done, he said. Another group, mostly young people in the credit union’s Silicon Valley market, have embraced the new technology. 

    ‘Uncanny valley’ meets virtual assistants

    Every now and then a new AI capability is launched and received with mistrust.

    At an event five years ago, Google demonstrated its Duplex AI assistant. In the demo, a user asked Duplex to book an appointment at a hair salon. Duplex did so using a female voice and using “mmm-hmm” in a convincingly human way. The crowd cheered. Then Duplex was asked to make a reservation at a small restaurant. In a male voice this time, Duplex said “um” several times and then “Oh, I gotcha.” Again, the crowd was impressed. 

    But reviewers criticized the demo, calling it “creepily real,” and Google quietly shelved the project for a while. 

    “It was very weird,” Theo Lau, founder of Unconventional Ventures, recalled in a recent interview. “I did not like it at all. It was creepy to me.”

    It can be hard for any company to build trust using AI-based virtual tools, Lau said.

    “What we’re struggling with now is you have deepfake videos, so you don’t know whether or not it’s true,” she said. “You have deepfake pictures that you don’t know whether or not it’s true. And now you have deepfake voice. When you are one layer removed from an actual human being, you don’t know.”

    This was once something bankers thought about as they experimented with avatars, according to Dan Miller, lead analyst and founder of Opus Research.

    “The evergreen issue surrounding the uncanny valley used to be solely about the creepiness of interacting with an avatar that seemed a little off,” he said. 

    As a result, “the financial service providers we’ve worked with have shied away from animated avatars, preferring to have invisible assistants that manifest as chatbots to answer questions and guide clients through the processes it takes to complete a task or get to the right information,” Miller said. 

    Automated resources powered by large language models and generative AI, such as ChatGPT, Bard and Claude, are largely disembodied, text-based search assistants or voicebots, Miller pointed out. 

    “We’re observing that, thanks to the utility of today’s conversational AIs, customers are more comfortable than ever before when they interact with a humanlike voicebot or chatbot,” Miller said.

    It’s true that most banks’ virtual assistants are far from crossing the line into being too humanlike. Still, as banks experiment with ChatGPT-like generative AI, the worry about confusing or upsetting customers is growing. 

    One concern about the uncanny valley effect is that fraudsters can take advantage of any “is it human, or is it a bot?” uncertainty to commit fraud.

    “Fraudsters are apparently getting better at creating synthetic humans as part of their efforts to defeat security systems,” Miller said. “That’s a valid concern.” 

    Full disclosure of AI use

    Even using disembodied, text-based bots, it can be unclear to customers whether they are talking to a person or a bot. 

    One way to bring clarity and avoid the uncanny valley is to disclose upfront that answers are coming from technology, not a human.

    Being honest helps avoid creepiness and suspicion, Fichtenholz said. Also, people tend to be forgiving of dumb answers if they know they are talking to technology.  

    “When companies build AI, we need to make it clear to people when they go from AI to humans,” said Zor Gorelov, CEO of Kasisto. “It’s ethically the right thing to do.”

    This kind of disclosure is “the first step of establishing trust,” Lau said. “If I don’t even know whether I’m talking to a human or a bot, and somehow I find out it’s the opposite of my preference, I will think, well, I can’t trust you.”

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    Penny Crosman

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  • How blockchain is helping Northern Trust self-execute contracts

    How blockchain is helping Northern Trust self-execute contracts

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    Northern Trust’s use of smart contracts is part of a trend. JPMorgan Chase has incorporated them in its blockchain projects, and just this week PayPal integrated them in its new stablecoin project.

    Mark Elias/Bloomberg News

    When Northern Trust executives think about smart contracts, they see better products and money saved. 

    The blockchain-based contracts partly cut out the role of third parties in enforcing legal contracts, boosting productivity by around 20% on simple deals and up to 70% on more complex ones, said Justin Chapman, Northern Trust’s head of digital assets and financial markets. What’s more, the programs allow the Chicago-based bank to store and repurpose data from past transactions. That helps make other deals happen seamlessly, he said.

    Northern Trust is part of a trend: JPMorgan Chase has incorporated smart contracts in its blockchain projects, and just this week PayPal integrated them in its new stablecoin project. Meanwhile, Alenka Grealish, senior analyst at Celent, said she has been working with other financial institutions to use smart contracts on permissioned blockchains in supply chains, environmental-social-governance matters and trade finance.

    Todd McDonald, co-founder of the enterprise vendor r3, said that he has yet to find a sector in the financial services area without an internal use case for smart contracts. 

    “This is part of a broader discussion on the future of finance,” said R.A. Farrokhnia, a professor at Columbia Business School who studies fintech. “Who’s going to be left behind, who’s gonna do it right — and what it takes for you to disrupt your own organization.”

    The contracts cut out middlemen. That’s why they became central to the decentralized finance, or defi, movement that helped popularize them. But they predate that trend. And, with more crypto providers sinking in legal troubles, they may be set to outlast it. 

    “The entry point”

    The $156.8 billion-asset Northern Trust entered the digital arena in 2017, when it developed a regulator-approved blockchain network for private equity fund administration. Months before it transferred that network to Broadridge Financial Services in 2019, it started using smart contracts to capture and automate the legal terms attached to asset transfers.

    “Smart contracts are a representation of a traditional contract,” Chapman said. “You are capturing the definition of the asset itself, the issuance of the asset and the issuing process through a smart contract, and you’re entering [that information] onto a register for onward transactions to happen on it.”

    That boosts productivity. But Chapman said the biggest benefit is in research and development.

    “What you tend to find is that the insights are stronger,” Chapman said. “You see an enhanced product. If we have a business idea or a problem, we can repurpose different types of smart contracts for different purposes.”

    Another upshot is that deals on shared networks are more transparent to the parties involved, Chapman said, even while that has taken getting clients to understand how to interpret legal clauses in code.

    “We don’t get as many challenges or questions as we used to,” Chapman said. “Smart contracts are just a code conversion from a written set of documentation. They’re nothing too complicated.”

    With the Chicago-based bank expecting that 5%-10% of all funds will be tokenized by 2030, the computer programs have become critical to its plans for the digital age.

    “The smart contract is the entry point to the new ecosystems and environments as we see them,” Chapman said.

    In 2020, Northern Trust also began exploring bond tokenization and fractionalization agreements, a year before it helped launch the crypto asset custodian Zodia Custody. It has since also become a participant in Swift’s digital-asset project.

    Northern Trust had $14.5 trillion of assets under custody/administration and $1.4 trillion of assets under management at June 30. Those client-asset categories are drivers of its largest segment of fee income, the company said in its second-quarter earnings news release.

    “The weakest point”

    Smart contracts pose one big problem: They’re prone to hacks.

    “Historically, we’ve seen in the industry, [that] the smart contract could be the weakest point, particularly as the code point,” Chapman said. “We have taken on additional cadence [to address that risk].”

    When the bank first started using smart contracts, it plucked them straight from infamously fraud-prone defi protocols. That required them to recode contracts built on public networks, said Arijit Das, senior vice president in digital asset innovation technology at Northern Trust.

    “Most public smart contract standards did not cater to the privacy needs of closed networks,” Das said. “The implementers of smart contracts had to code these privacy and security needs into the smart contract logic.” 

    Northern Trust soon developed its own system on hyper-ledger fabric technology with smart contracts coded in Golang, Google’s open-source programming language. That, along with recent fintech strides to pioneer smart contract languages that are more secure, has made the programs safer. To double-check smart contracts’ cyber protections and avoid fat-finger mistakes, the bank has also introduced an internal audit system.

    “We see activity in this space as the industry has recognized the need to solve the problem of privacy for all chains,” Das said. “A lot more attention is focused on the needs of large, private permissioned systems with institutional participants.”

    Safeguards needed

    But some experts think there may need to be even more protections in place before smart contracts can be safely integrated into traditional financial services.   

    That includes placing a “pause” button — often called an “article” — in case one party encounters a hiccup or needs to renegotiate the deal, said Hillary J. Allen, professor at American University College of Law. 

    Other risks involve human error, picking the wrong coding languages, or trouble in sourcing external data, said Monica Summerville, head of capital markets at Celent.

    Then there are also unresolved questions over who bears liability for any legal issues the contracts cause. “I would say the safer rule is that if it’s your system, you own it,” Allen said.

    Banks should also beware that smart contracts, while traceable, are irreversible. That means that they can fail to account for unwanted eventualities that leave parties unable to overwrite prior terms. At Northern Trust, there is often no way to reverse smart contracts, though the bank can layer other contracts on top of them to override the previous terms, Chapman said.

    “What if these things work exactly like they’re supposed to, and we still don’t want that?” Allen asked. “Sometimes there will be situations where you want some flexibility and discretion. There’s no discretion. That’s sort of touted as a feature, not a bug. But I wonder if it’s a bug.”

    Tech tailwinds are nonetheless pushing financial institutions toward the blockchain, and with it, smart contracts.

    But the switch to digital assets is going to be harder than the one from fax machines to email servers, Farrokhnia said. That could be a problem for banks with technology architectures that don’t integrate with blockchain servers or executives who aren’t up to date on the new technology.

    “The learning curve was relatively easy, and it didn’t require banks to change their entire systems. Blockchain is the exact opposite,” Farrokhnia said. “How do you … still, run the company the way you’ve been running it, but in an alternate universe?”

    To avoid being left behind in an advancing tech race, financial institutions may need to start catching up. They can start by watching the fintech scene, Farrokhnia said.

    “Ensure that you have your pulse on the market,” he said. “Startups are very good at innovation. But big banks are good at distribution. If you marry the two, then you have something powerful.”

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    Charles Gorrivan

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  • AWS, Google and Microsoft are in an AI arms race. Banks are watching.

    AWS, Google and Microsoft are in an AI arms race. Banks are watching.

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    The three big cloud computing vendors — Amazon Web Services, Google and Microsoft — have marshaled much of their forces around generative AI. Microsoft has invested $13 billion in OpenAI, creator of the massively popular ChatGPT generative AI search engine. Last month, AWS announced a $100 million investment in a generative AI innovation center. Google has invested an estimated $300 million in AI startups. All three offer a slew of proprietary technologies for developers, data scientists and lay people to create and use generative AI and large language models. 

    At the AWS Summit this week in New York, for instance, speakers talked of nothing else.

    “Generative AI has captured our imaginations for its ability to create images and videos, write stories and even generate code,” said Swami Sivasubramanian, AWS’s vice president of database, analytics and machine learning. “I believe it’ll transform every application, industry and business.” Though it’s been around for years, it’s reached a tipping point, he said.

    Most banks work with these three vendors, yet unsurprisingly lag behind on the generative AI curve, due to the risks of errors and hallucinations in this advanced form of AI. They’re in test-and-learn mode, trying out different use cases, like improving chatbots and summarizing documents. Meanwhile, the generative AI craze seems to be spurring more interest in more traditional forms of AI, such as the use of machine learning in anti-money-laundering work.

    Bankers are certainly asking their cloud vendors about generative AI.

    “In almost every conversation that I’ve had over the last six months with a leader in any financial services organization, generative AI has come up as a topic,” said John Kain, head of financial services market development at AWS, in an interview. “Because in the financial services industry, our customers see how transformative this could be and none of them want to be left behind.”

    Synchrony Financial and SouthState Bank are letting employees experiment with enterprise versions of Microsoft/OpenAI’s ChatGPT. 

    “It’s game changing,” said Chris Nichols, director of capital markets at SouthState Bank in Winter Haven, Florida. “It’s worth all the hype.” His staff is using it to summarize email threads and find information. Synchrony has held internal hackathons to come up with the best uses for the technology. 

    But most banks are proceeding cautiously. 

    “Like most new technologies, you have to limit it for folks who may not fully understand the power and could do something unintentional,” said Carol Juel, chief technology officer and chief operating officer at Synchrony, in a recent interview. “So as a good steward and as a company, you have to protect against that.” 

    Banks are right to take a slow, cautious approach to generative AI while technology vendors are betting their future on it, according to Sumeet Chabria, CEO of ThoughtLinks. 

    “The current pace of AI investment in cloud and other technologies surpasses the ability of banks to adopt it responsibly,” Chabria said.  

    On the other hand, banks may face increasing pressure from consumers who get more familiar with the technology as more products come bundled with generative AI, he said. Banks and technology vendors need to come together to discuss parity before it is too late.

    “This could mean technology vendors slow down a bit to fully comprehend the responsible banking concerns, including on cybersecurity,” Chabria said. “Banks on the other hand need to be willing to partner on low-risk, non-customer-facing use cases to help progress the technology and ensure the broader teams are trained on its potential and risks. There are use cases even today where generative AI may help mitigate risk in banking as an additional line of defense, like predicting the next big technology incident. Even a 1% probability of getting this right is a big deal.”

    Where generative AI makes sense in financial services

    In banking, traditional forms of AI, like machine learning and natural language processing, are used in many places: detecting fraud, monitoring cyber threats, chatting with customers, onboarding new customers, assessing potential borrowers and personalizing offers, to name a few.  

    A large language model like GPT-4 or Titan brings great scale. It can analyze vast quantities of data and documents. Generative AI can generate text and code based on such massive datasets.

    “What I think everyone’s realized is the power of a large language model to do many of those tasks,” Kain said. All AWS customers right now are finding out which use cases are best suited to generative AI and which work better with traditional AI, he said.

    PennyMac and Black Knight, for instance, use traditional AI to extract data from mortgage documents, and they’re looking at whether a large language model would provide added benefit, he said. 

    JPMorgan Chase has been testing the use of generative AI for customer recommendations. Washington Federal and JPMorgan Chase have been exploring the use of generative AI for analyzing call center transcripts to figure out how to provide better prompts for customer service reps.

    Document classification is another strong use case for generative AI, Kain said. Though companies can do this with traditional AI today, “you tend to have to give it a little bit more training material, a little bit more prompting to actually do that classification,” Kain said. 

    Bill Borden, corporate vice president, financial services industry, at Microsoft, sees three top use cases for generative AI in banks. 

    The first is content creation — for instance, generating proposals, reports and presentations, and summarizing internal meetings and customer conversations. HSBC India, for instance, is using the OpenAI GPT-3 davinci model to summarize regulatory briefs published by the Indian government.

    The second is semantic search — using natural language and context to make searching smarter, faster and continuously trained.  

    The third is code generation. 

    “With copilot capabilities for generating sophisticated code, developers will spend less time writing lines of code and more time designing new statistical models and mathematical tools for actuarial challenges,” he said.

    Part of the appeal of generative AI to financial services clients is the idea that it could help reduce operating margins and change customer interactions, according to Yolande Piazza, vice president of financial services at Google. 

    “Many controls are still manual today,” said Piazza, who was formerly CEO of Citi Fintech, in an interview. “How do you start to automate that so you can be much more predictive in your control functions and how you report out to the regulators? So I think people are able to clearly visualize the opportunity that will bring to the businesses.” 

    Google offers an enterprise version of Bard, its ChatGPT-like search engine, to banks. It can be completely focused on a bank’s internal documents and data. It could also be set up to ingest certain external documents such as SEC filings. 

    “[Customers] control the data sets, they control the models that they build,” Piazza said. “So there’s no risk of IP leakage. There’s no risk of them pulling in data sources that would give them competitors’ answers. If you just go out and train this on the world of the internet, you’re potentially bringing in competitors’ information.”

    In its search results, Google Bard lists every source, to provide auditability.  

    “If you want to go in and start reading in more detail, to validate the information, you have the ability to do so,” Piazza said. “You can control if this is just internal data, whether it’s internal plus external data. And that’s how a company will control its own destiny as far as accuracy, security and the distribution of models.”

    No one in the financial services industry is going to adopt such technology blindly, Piazza noted. 

    “What it will do initially is reduce the time to gather that information, that validation step and process,” she said. “Humans will stay in place for a long, long time. What we focused on is the research that nobody likes to do. Then a human can go through and say, what about this summary am I comfortable with? Where do I want to dig deeper?”

    Generative AI is kick-starting interest in traditional AI

    Piazza said the hype around generative AI is driving more interest among financial services clients in traditional forms of AI like machine learning. 

    “Generative AI has forced people to go back and really look at the unlocked capability with AI and machine learning fundamentally,” said Piazza. “What you’ll find is they are all on a journey of AI, whether that’s models that they’ve built internally, whether that’s how they’re thinking about machine learning.” 

    A case in point is HSBC, which recently co-developed AI-based anti-money-laundering software with Google.

    The London bank operates in more than 60 countries and has more than 40 million customers. 

    “We want to make sure that our products and services are not exploited by individuals who would use them for crime,” said Jennifer Calvery, group head of financial crime risk and compliance at HSBC. The bank reviews more than 1.2 billion transactions every month to look for signs of financial crime. Last year it filed more than 73,000 suspicious activity reports. 

    Like other banks, HSBC files a report every time there’s reason to think someone has used its products and services to engage in a crime such as terrorist finance, money laundering, tax evasion, fraud, bribery or corruption. 

    “Our job is to prevent them from doing that,” Calvery said. “And if they do get into our bank, to find them as fast as we can and to get them back out. So it’s a scale problem for us.”

    She wanted to be able to use all the data the bank has at its disposal to understand the probability that any given customer or counterparty would use the bank to commit financial crime, in real time. 

    “That was the dream,” Calvary said. “We had absolutely zero capability to do this. We were using the same rules-based systems that everyone in industry was using at the time. They are not real time, not capable of using all the data at our disposal. There’s thousands of people whose only job it is to close out noise because they generate so many false positives.”

    It’s also difficult to identify financial crime by looking at individual bank transactions, said Calvery, who is a former prosecutor. 

    “I did many investigations,” she said. “I never once tried to find a criminal by looking at transactions one at a time. That’s just not how you find criminals. So we wanted to invent something new.”

    Google Cloud’s AML AI provides a machine learning-generated customer risk score based on bank data including transaction patterns, network behavior and know-your-customer data. This helps the bank identify its highest-risk customers. Other providers of machine learning-based anti-money-laundering software include IBM, Quantexa, Thetaray and ComplyAdvantage.

    HSBC has been using the new anti-money-laundering software for a year in the U.K., Singapore, Mexico, the Channel Islands and Hong Kong.

    “We’re finding more financial crime faster with far less noise and far less calls out to customers, asking them questions for what ultimately turned out to be a false positive,” Calvary said. 

    Some may wonder if the hype around generative AI is a passing fad. Kain does not.

    “You’ve already seen the quality of the output, from just a richness of the human interaction experience, that these language models can bring,” he said. “And that’s very tangible. There are definitely productivity benefits that you can see within that.”

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    Penny Crosman

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  • Banks take stabs at speeding up account-opening in branches

    Banks take stabs at speeding up account-opening in branches

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    Banks keep shaving off the number of minutes they say it takes to open an account online. But in the branch, the process can take an hour.

    The topic came up during Michelle Moore’s keynote at American Banker’s Digital Banking conference in June. Moore, the head of consumer digital at Wells Fargo, said the bank is aiming to further digitize account opening in the branch.

    “If it takes two minutes or less to open a checking account on the phone, why is it not that process in the branch?” she said as an answer to an audience question. “The checking account opening experience should not be a 45 minute, hour conversation, printing all kinds of materials and typing in 40 fields of information. The application should be about five minutes. The rest of the time should be the conversation.”  

    In-branch account opening is typically handled by teller management systems, whereas online account opening is on a separate platform, points out David Schiff, head of retail and consumer banking at West Monroe. The know-your-customer and anti-money-laundering checks that were optimized for fluidity online have not all migrated to the branch. Financial institutions may be hesitant to devote the time and resources to changing their systems and re-training branch staff.

    There are also infrastructure limitations.

    “I was surprised at how many banks don’t have public WiFi in their branches,” said Schiff.

    Some banks, including Bank of America and F.N.B. Corp. in Pittsburgh, are taking steps to upgrade their branch technology. Despite advances in online and mobile account opening technology, people sometimes still prefer coming to the branch for guidance or advice, or may want to start the process in one channel and finish in another.

    Banks can capitalize on these face-to-face opportunities to deepen their relationships. This ability to make a sales pitch in person is one reason banks still prize branch account opening.

    “That initial touchpoint is the most valuable and why sometimes account opening takes so long,” said Schiff. “There is a perverse incentive for banks to make that process feel advisory and mechanical because it gives them an opportunity to have more conversations while the system is processing.”

    Moreover, “There is still a mentality at a lot of banks that most information they can collect about the customer is through that face-to-face interaction,” said Schiff.

    Some people just feel more comfortable having a person on standby.

    “I like to ask a lot of questions,” said Vincent Delie Jr., president and CEO of FNB, speaking of his experience as a bank customer. “Sometimes it’s easier to give people permission to key in your name, address and phone number, and walk you through the process than it is for you to fumble online.”

    FNB has made leaps in digital account opening that it plans to integrate into its branches. The bank’s eStore platform lets users of the website, app or in-branch kiosk browse an array of deposit accounts, loan types, business products, financial education content and more, add selected items to a “shopping cart,” and “check out” — that is, apply or learn more. In June, FNB announced its eStore Common application, which lets users apply for multiple products simultaneously with pre-filled information. The middleware is proprietary to FNB but it uses vendors to authenticate customers.

    But the ultimate vision for the $44.1 billion-asset bank is weaving digital and traditional channels together for a consistent user experience, or what Delie Jr. calls “Clicks-to-Bricks.”

    “A lot of what you have observed [concerning redundant and paper-based processes] is what drove our whole strategy,” said Delie Jr. “The goal for Clicks-to-Bricks is to have the same type of speed and interaction capability we have with mobile and online in our physical branches.”

    Today, users of the in-branch kiosk can send their eStore cart to their email address or inform the branch that they’d like to check out there. Relationship bankers are also equipped with tablets they can use to educate customers on products. If customers want to open an account in a branch, for now they have to go through FNB’s traditional platform with a banker; alternatively, they can do so on their personal device digitally with the assistance of a banker. (There is no public WiFi, however.) A next step is to embed more of these fast, slick eStore capabilities into account-opening technology in the branch.

    FNB is also working on other upgrades to make the whole eStore experience smoother, such as letting customers upload a photo of their identification as part of KYC. The bank plans to introduce account-opening capabilities into its video teller machines.

    Bank of America, meanwhile, is bridging the benefits of in-person guidance with the ease of using a personal device.

    “One of the biggest challenges when a prospect or a customer new to the bank comes to open an account is, if you don’t have any data on them, the associate often has to do a lot of data entry to open the account,” said Ryan Furey, digital executive for retail at Bank of America. “It becomes slow and laborious. But when you think about digital, newer technology and capabilities add a lot of convenience and make it more personal for the individual.”

    When someone discusses new accounts with an associate in a branch, the banker can now push any consumer products they recommend to the “saved items” list in the customer’s mobile app. (A new customer would have to first download the app and build a basic profile.) The customer will receive a notification that something was added to their saved items. From there they can begin the application on their phone, with the banker standing by in case they have questions. Public WiFi is available for customers.

    Bank of America has done this for existing customers for several years, and started piloting it for new customers last year before expanding the capability to all branches. A higher percentage of new customers want to open an account in a branch compared with existing customers. 

    One question banks must contend with is how to handle the incentives tellers get for opening accounts in a branch, and how to avoid creating unintentionally perverse incentives.

    “It’s less common post-Wells Fargo, but still common enough to be viewed as typical in the market,” said Schiff. Incentive programs can be tied to opening target volumes of specific products at the individual banker, branch or market level. Bank of America was recently ordered by the CFPB to pay $250 million for, among other things, illegally opening a small number of credit card accounts without customers’ knowledge or authorization.

    FNB geocodes customers who arrive via a digital channel and gives credit to the nearest branch. It is also converting tellers into “relationship bankers” who are equipped to handle a broad range of consumer banking tasks and whose positions are incented differently.

    At Bank of America, “When they engage with the client through the saved items list and make recommendations, we can account for that within our internal systems that they were involved with the sales process,” said Furey. 

    Another issue banks want to solve is letting people start the process in one channel and finishing in another.

    “For a number of years this is something account opening vendors have been focusing on,” said Mark Schwanhausser, director of digital banking at Javelin Strategy & Research. “This idea that if we can create a single platform where someone starts online or mobile, they can resume it there, or if they go into a branch, the material is there. There are not two systems for processing.”

    Delie Jr. said it’s a critical piece of FNB’s strategy. Furey said Bank of America started out by testing for situations where someone was interested in a product, but needed time to think about it. Adding it to their saved items list made it easy to retrieve at home.

    “It’s not enough to make your process faster, to take it from six minutes to five minutes,” said Schwanhausser. “The important thing is to get them in the right product, get them engaged and get deeper relationships as quickly as possible. Ideally a banking relationship goes for decades. How can you start that off on the right foot?”

    Even purely digital account opening capabilities have their hiccups.

    “Some banks have put in really slick digital solutions for online account opening, but it may take ten to 12 days for the account to fully open because they are verifying things like my driver’s license picture,” said Schiff, who regularly opens bank accounts for his work. “If I weren’t doing it to experiment and understand what the process was, I would probably abandon it and open my account somewhere else.”

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    Miriam Cross

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  • Here’s how banks are using and experimenting with generative AI

    Here’s how banks are using and experimenting with generative AI

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    Large language models could change how banks interact with customers and their own knowledge bases, and how they protect themselves and their customers from fraud and financial crimes, but few have released products that actually deploy the nascent technology.

    That has left smaller banks that are in the learning and experimentation stages to take cues from technology leaders on where large language models — the kind of technology that powers OpenAI’s ChatGPT — will become most useful in banking.

    Large language models are one example of generative AI, a type of artificial intelligence that can generate content to mimic text, images, videos or other content on which it has trained. According to Michael Haney, head of product strategy at Galileo Financial Technologies, ChatGPT put this technology on many banks’ radars very suddenly.

    “There are very few banks who’ve put this into the production environment,” Haney said of large language models. “Most banks may have not even been aware of generative AI until ChatGPT made headlines.”

    Two examples of banks using large language models in an experimental capacity or otherwise keeping its use strictly internal include Goldman Sachs using generative AI to help developers write code or JPMorgan Chase using it to analyze emails for signs of fraud.

    Additionally, JPMorgan Chase trademarked a technology in May for a product called IndexGPT that could select investments for wealth management clients. The product is apparently part of a larger effort by the bank of leaning into technology investments, specifically in artificial intelligence. Unlike others, the trademark specifies that customers (not just bank employees) would interact with the model.

    As banks grow more interested in adopting AI for various use cases, they need to be careful about their strategy for doing so, according to Jen Fuller, U.S. financial services lead at PA Consulting.

    “One of the big risks about AI for organizations at the moment is it turning into a Frankenstein’s monster of pet projects,” Fuller said. “Everybody’s doing their own little thing with AI, but to really get the organizational value at a strategic level, you need to build a framework where AI is part and parcel of the way that your organization does business.”

    One way that banks are making AI part and parcel of their business is by organizing their knowledge bases by training language models on internal documentation and allowing employees to interact with a language model that can answer questions that can only be answered by searching that documentation.

    Organize institutional knowledge

    SouthState Bank’s director of capital markets said last month that the bank has been training OpenAI’s ChatGPT on bank documents and data (not customer data) to allow employees to query the system to summarize and assimilate the bank’s internal records.

    Similarly, in March, OpenAI and Morgan Stanley announced a partnership that was helping Morgan Stanley wealth management employees locate information within the investment bank’s large repository of content. A spokeswoman for Morgan Stanley said Friday that 900 advisors now query the system.

    Internal uses of large language models to organize institutional knowledge have the advantage of filtering model output through bank employees rather than giving it directly to the customer, as one of the well-known problems with large language models is that they can hallucinate — state something as fact that sounds plausible but is actually false.

    This is one of the main motivations for Sydney-based bank Westpac partnering with AI company Kasisto to train a language model solely on conversations and data in the banking industry, but keeping the model for internal rather than customer-facing use. Kasisto started a similar partnership with TD Bank in 2018.

    Bloomberg has also taken a stab at organizing financial knowledge, by training a large language model of its own on Bloomberg sources and public text corpuses such as Wikipedia. In March, Bloomberg released a paper on its model, which has 50 billion parameters. While small compared to the reported 1 trillion parameters in OpenAI’s GPT-4 model and 1.2 trillion in one of Google’s models, BloombergGPT does outperform top open source language models on certain benchmarks such as understanding dates in text and making logical deductions.

    Provide customer service

    Few banks have deployed chatbots that they publicly claim are powered by large language models, but companies like Kasisto and Monarch offer services to banks and consumers respectively that promise powerful chatbots by large language models.

    As for chatbots overall, some of the leading customer service chatbots include Capital One’s Eno, Bank of America’s Erica, HDFC’s Eva, and Santander’s Sandi. However, these banks do not advertise these services as being powered by generative AI.

    “I haven’t seen anyone market their chatbot as a large language model,” though banks will often market them as AI- or machine learning-powered, said Doug Wilbert, managing director in the risk and compliance division at Protiviti.

    Rather than working like a language model, some chatbots work more like interactive voice response. Also known as IVR, this technology enables the automated interactions customers have when they call a company’s support line. Rather than telling the caller to select from a menu of options by pressing a number during the call, IVR enables the caller to give short descriptions of what they need and redirects their call accordingly.

    As banks started to release chatbots, some viewed them as replacements for IVR, according to Galileo’s Haney. Rather than run the user input through a large language model to sift through the nuances of what the customer said, these chatbot systems tend to look out for keywords, which can lead to shortcomings.

    “The problem is you can’t anticipate every random question that the customer is going to have,” Haney said of these IVR replacements.

    For example, such systems struggle to interpret longer user inputs that provide context for their inquiry (“I deposited my paycheck before going shopping, but my card declined. Why did that happen?”). These systems can also struggle with inquiries that include multiple requests in one (“I want to see my checking balance and put half of it into savings”).

    These are the exact kinds of shortcomings the Consumer Financial Protection Bureau warned that chatbots in consumer finance can have. Specifically, the bureau said chatbots “may be useful for resolving basic inquiries, but their effectiveness wanes as problems become more complex.”

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    Carter Pape

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  • Banks can meet Gen Z where they are, via platforms like Spotify

    Banks can meet Gen Z where they are, via platforms like Spotify

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    Financial institutions should seek to engage with younger customers on their preferred platforms and in mediums that resonate with them, like on Spotify, panelists at American Banker’s Digital Banking conference said.

    At the conference in Boca Raton, Florida, this month, experts said that Generation Z wants to feel like their financial institutions understand them and that they can trust their banks. Banks can strike this balance of being hip and trustworthy by leveraging user data to market to clients through outlets like audio streaming platforms.

    Brian Elkins, head of the financial services practice at brand consultancy Monigle, said Gen Z is seeking decision support, meaning resources that provide financial literacy and information for them to map their financial journeys. He said Gen Z wants to understand their financial needs “on their terms,” in ways tailored to match their identities. Elkins added that younger people don’t look at financial planning the same way older generations did now that people are living longer and shifting careers more often. 

    Elizabeth Song works at Spotify, helping financial institutions market and find their audiences on the audio platform. Banks can run ads within podcasts and other content that’s popular with target clients. Song said music is also an opportunity for banks to be more creative by making or sponsoring playlists that could resonate with potential clients.

    “If you really mean what you say about meeting customers where they are, the fact is that music streaming and podcast listenership are on the rise,” Song said. “Gen Z and millennials can’t live without their playlists. They can’t live without their favorite podcasts.”

    She said her goal is to make ads nondisruptive to listeners. She added that the more people are engaged with the content they’re listening to, the more they’ll be engaged with the ads attached to that content. 

    Song said younger generations want more from banks than just financial products, they want personalized content and services. According to Spotify’s 2022 Culture Next report, 80% of Gen Z financial service customers said they like when brands are able to connect with different sides of their personality. She added that, for banks, transactional data from users isn’t enough information to design a fully tailored experience.

    “We have a lot of fun data that we can share with [financial institutions] for a 360 audience profile,” Song said. “If you really want to understand what Gen Z and millennials are going through, it’s also going to be the data about their nonfinancial moments. What do they love doing? What do they love listening to? What are their passion points? That’s really going to help bridge that gap from being a transactional provider to more of a lifestyle brand.”

    Gen Z is also more comfortable giving their data to financial institutions in exchange for content that feels in line with their identities. According to a study by Arizent, American Banker’s parent company, in partnership with Monigle, 73% of people said they are willing to share their data in order to receive personalization. 

    For example, Spotify Wrapped is an annual marketing campaign in which Spotify creates personalized snapshots for each user based on their listening data from the previous year.

    Elkins said he’s worked with some financial institutions that worry about leveraging user data. Younger generations prefer personalization that can be determined by their behavior and activity, he added, in part because they’re accustomed to that type of service from companies like Amazon, Netflix and Spotify. He said the mindset around companies using user data has shifted over the last five to ten years and that financial institutions should conform their “voice” based on platform, demographic and medium.

    “Personalization can be everything from the actual product that you’re delivering, but more than anything, it’s about how you show up in a moment,” Elkins said. “What voice are you using? What kind of content? Is it more snackable at that moment? Is it more long form? Or is it digital audio? I think it’s really about being into that, and thinking about user-specific moments and how you shape your communications.”

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    Catherine Leffert

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  • JPMorgan Chase aims to create $1.5 billion in value with AI by yearend

    JPMorgan Chase aims to create $1.5 billion in value with AI by yearend

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    Lori Beer, global CIO at JPMorgan Chase, said the bank is continuing to execute its technology strategy outlined last year.

    JPMorgan Chase is on track to invest more than $15 billion in technology in 2023, with the goal of driving $3 billion in cost savings and efficiencies across infrastructure and data initiatives, as the bank continues to execute on the firm-wide strategy it laid out last year.

    Lori Beer, global chief information officer, said at the company’s investor day last week that it is investing almost equally in running the bank and changing the bank, evaluating generative AI applications and staying on track with its infrastructure modernization.

    JPMorgan Chase expects that its investments in data analytics and AI to increase customer personalization and client insights will deliver $1.5 billion in business impact by the end of 2023. The bank’s infrastructure modernization, which includes optimizing its data centers and migrating applications to public and private cloud, is slated to bring in an additional $1.5 billion in cost savings and efficiencies over the next three years.

    The industry giant’s interests in AI and cloud computing aren’t unique across the sector. Keri Smith, who leads Accenture’s applied intelligence banking practice in North America, said as AI innovations become table stakes, banks will have to search for ways to differentiate their services. 

    Last year, the bank outlined its four technology investment priorities: developing strong products and customer experiences, strengthening infrastructure, increasing investments in and use of data analytics and AI, and maintaining cybersecurity. In 2022, the bank spent about $14.3 billion on technology.

    Neil Hartman, a senior partner at consulting firm West Monroe, said major banks have been updating their foundations for several years, and now can work on emerging technology projects.

    “We’re seeing a shift from the biggest banks into modernizing the bank, and leveraging new technologies to set the bank up for the next business cycle,” Hartman said. “There’s benefits for the banks today around efficiency and cost savings.”

    One of the pillars to JP Morgan’s strategy is investing in data, AI and machine learning.

    Last year, Beer said the company hoped to create $1 billion in value through AI by the end of 2023, but increased its goal due to recent results. In the last year, AI has driven $220 million in retail at the bank through personalized offerings, like credit card upgrades. The technology has also yielded $100 million in commercial business in 2022 by offering bankers suggested products and growth plans for clients. The bank has more than 300 AI use cases in production for risk, marketing, customer experience and fraud. JP Morgan measures value through cost savings and efficiencies, tracking the costs and return associated with investments.

    Hartman said the biggest difference between a major institution like JP Morgan and a smaller regional bank is the size and complexity of its lines of business and client portfolio, which raise its imperative to innovate.

    “The biggest thing for the largest banks, especially right now, that we’re seeing is automation and trying to drive better efficiency throughout their entire ecosystem,” Hartman said. “Automating as much as possible, leveraging AI tools, leveraging robotics of workflows, and APIs, all those types of technologies to really drive more efficiency within their four walls.”

    Hartman said it’s especially important for banks to find and automate inefficiencies in their operating models during uncertain economic environments, when reducing costs is a bigger focus.

    JPMorgan Chase is currently working on a generative AI product that could select investments for wealth management clients, CNBC reported, based on a recent trademark application. The company’s product, IndexGPT, uses GPT software as a service to analyze and select securities “tailored to customer needs,” per the bank’s trademark application.

    Samir Datt, who leads Protiviti’s technology strategy and operations practice, said implementing proper governance for trusting AI and monitoring use cases is as important as adopting the technology. 

    Beer said the bank had a team of data scientists, ethicists, risk professionals and others to evaluate generative AI use cases. She added in her presentation that the bank’s policy is, “successful AI is responsible AI.” 

    JPMorgan Chase has hired more than 900 data scientists, 600 machine learning engineers and 200 AI researchers to execute its technology initiatives. Datt said that as banks increase their AI and automation capabilities, it’s important to upskill employees to appropriately use and assess that technology. The company has a total technology team of more than 57,000 people.

    Hartman said big banks are focused on bringing in those technical skill sets to compete with fintechs and Big Tech companies.

    “We couldn’t discuss AI without mentioning GPT and large language models,” Beer said. “We recognize the power and opportunity of these tools and are committed to exploring all the ways they can deliver value for the firm. We are actively configuring our environment and capabilities to enable them. In fact, we have a number of use cases leveraging GPT-4 and other open source models currently under testing and evaluation.”

    Other major financial institutions are also evaluating generative AI opportunities. Goldman Sachs CIO Marco Argenti said at the Fintech Nexus conference earlier this month that his bank was experimenting with the technology to increase software development productivity, to extract information from documents and to use robotic process automation. Morgan Stanley Wealth Management launched a project in March with OpenAI to create a product that provides financial advice.

    Smith said that as the pace of development in generative AI and large language models rapidly picks up, financial institutions have prioritized hitting AI milestones faster. She said companies are adjusting their innovation investment appetites and timelines, looking for ways to automate processes that can lead to faster bottom-line impact.

    “When you think about some of the tech investments that are needed to be made, some of these may be giant investments,” Smith said. “But what we’re finding is people are starting to look at, ‘How do I think about this in bite sized chunks, and do this in sprints so that I’m able to get results faster, but also not necessarily have a sizable price tag?’”

    JPMorgan Chase’s infrastructure modernization, which includes increasing cloud migration and optimizing data centers, is foundational to developing other innovative technologies like AI, Beer said. The company has delivered $500 million in productivity and cost efficiencies from infrastructure investments, and is aiming to hit $1.5 billion in the next three years.

    “These gains are tied to investments and actions we’ve taken in the way we deliver software and our modernization efforts,” Beer said. “Specifically, we have driven $300 million in efficiency through modern engineering practices and labor productivity, and we have developed a framework that enables us to identify further opportunities in the future. Our infrastructure modernization efforts have yielded an additional $200 million in productivity, driven by improved utilization and vendor rationalization.”

    Beer said the modernization investments enable the company to migrate large amounts of data to the public cloud, and increase the data platforms’ capabilities. Cloud investments will make up 38% of JPMorgan Chase’s total technology infrastructure spend in 2023.

    “Our cloud journey will ultimately create a faster, more efficient environment for our business,” Beer said. “By working toward our target state of multi-vendor public cloud and modern strategic data centers, we have been able to keep our infrastructure expenses relatively flat while our compute and storage volumes have increased 50% since 2019, and tripled since 2015.”

    JPMorgan Chase has moved more than half of its in-scope applications to more efficient data centers and decommissioned 300 legacy applications in the last year. In the fourth quarter, the bank completed its migration of Chase.com to the public cloud through AWS.

    Datt said updating or migrating off of outdated infrastructure can be tedious and risky, but necessary to keep up with pushing out products and services to meet customer demand.

    “[Banks] have got to have the underlying infrastructure, the process discipline, things like true agile enablement and strong devops practices, to move through the development lifecycle, and push that kind of functionality out to production in rapid, controlled fashion while managing risk,” Datt said.

    The bank is also increasing its use of APIs that allow consumers to share information from their bank accounts with apps and companies, which Hartman said is an expanding trend among large financial institutions. 

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    Catherine Leffert

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  • Brex tried to buy a piece of Silicon Valley Bank in March

    Brex tried to buy a piece of Silicon Valley Bank in March

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    Brex was one of the 20 companies that put their hat in the ring to acquire Silicon Valley Bank, or chunks of it, in March, newly-released Federal Deposit Insurance Corp. data shows.

    The San Francisco-based neobank tried to buy some deposits and credit card accounts from Silicon Valley Bank when the bank was seized by the FDIC, Brex CEO Henrique Dubugras said in an interview. The deposits and card accounts were all held by early- and growth-stage startup clients. 

    Dubugras knew Brex’s bid was a long shot because it isn’t a bank and it wasn’t aiming to buy all of Silicon Valley Bank, but the overlap of the two companies’ focus on serving startups made the opportunity attractive to the neobank.

    “We understand the community really well, and we thought we could serve it really well,” Dubugras said. “We didn’t bid for the winery or the private bank, or any of these assets that we don’t understand. We only went for the ones we thought could do a really good job and keep the ethos of SVB.”

    Dubugras said that the acquisition of the early- and growth-stage portfolio would have brought customers and talent to Brex, but it would not have brought the company a bank charter.

    Jonah Crane, a partner at the advisory and investment firm Klaros Group, said acquiring a portion of Silicon Valley Bank’s deposits could have been an opportunity for Brex to accelerate its growth with the company’s target customer base at a bargain price.

    Raleigh, North Carolina-based First Citizens BancShares ultimately won the auction for Silicon Valley Bank, assuming $72 billion of loans and all $56.5 billion of deposits. The FDIC published all 25 bids and the 20 firms that submitted them on Wednesday, but it didn’t disclose which company submitted each bid. Although nearly half the bidders were nonbanks, including Blackstone, Apollo Global Management and Sixth Street Partners, Brex was the only neobank. 

    Brex declined to disclose financial details of its offer, but Dubugras said the company planned to use cash on its balance sheet to buy the deposits and card accounts. He added that Brex was never in contact with the FDIC about the bid. The company decided to submit its pitch at the recommendation of a Brex customer who was also a customer at Silicon Valley Bank, Dubugras said. Brex’s executive team put together the proposal, which was approved by its board. 

    Neobanks that serve startups saw a massive influx in business following Silicon Valley Bank’s failure as  venture-backed businesses looked for ways to safely, quickly stash their capital. Since the bank’s collapse, Brex said it has added $2 billion of deposits. The company has also added to some products and features, including raising the amount of deposits it could protect through money sweep programs and expanding travel booking. Brex’s main strategy going forward is still focused on its expense management software.

    “We’re not trying to win all the deposits,” Dubugras said. “We want to be your operating account. We want to make all your payments, run your payroll and pay your bills because our software is really good at doing that. And if you want to keep a lot of money in our treasury, too, we have a product for that. But we really excel at simpler treasury use cases where you just want a money market fund, or day-to-day operation, like bill pay, wires, checks.”

    The CEO added Brex isn’t interested in acquiring a bank charter the way some fintechs that focus on online lending like SoFi and LendingClub have done in recent years.

    Klaros Group’s Crane said it could make sense for Brex to try to acquire a bank charter, depending on its long-term strategy. When fintechs try to buy banks, they usually look for small, healthy community banks.

    “Brex is offering banking services to customers as a nonbank, and they found some relatively creative structures to do that,” Crane said. “But ultimately, they’re not going to be able to be the core operational account or core banking relationship with their customers without a banking license. I think it’s just too hard to run a core treasury and payments function for sizable commercial businesses as a nonbank.”

    Dubugras said that Brex is still open to other potential acquisitions but is prioritizing internal investments. He added that distressed Silicon Valley Bank was a “very unique” situation because of its customer base’s overlap with Brex’s. There aren’t many banks that have similar portfolios, except First Republic Bank, which was also based in San Francisco and served similar startup clients but failed Monday following a steep drop in deposit, he said. JPMorgan Chase bought all of First Republic’s deposits and “substantially all” of its $229.1 billion of assets. Dubugras said Brex didn’t have a chance to look at submitting a bid for First Republic. 

    Bloomberg News and Reuters reported at the time that the FDIC had asked banks to place bids the day prior, including PNC Financial Services Group, U.S. Bancorp, Bank of America and Citizens Financial Group. JPMorgan Chairman and CEO Jamie Dimon said his company had 800 people working to assess First Republic’s books.

    “Our government invited us and others to step up, and we did,” Dimon said in a news release at the time. “Our financial strength, capabilities and business model allowed us to develop a bid to execute the transaction in a way to minimize costs to the Deposit Insurance Fund.”

    Crane said finding nonbanks able to take assets out of failed, or even healthy, banks could help the banking industry shore up capital positions. He added that he thinks if more banks fail, it will be easier for a nonbank to get in on the purchase action.

    “Even if the vast majority of banks are reasonably healthy, they’re all looking at the balance sheet, and they’re all looking at the economic environment, and they’re all getting a little risk-averse right now,” Crane said. “It makes sense that you would want to attract capital from outside the banking system to provide part of the solution here. … JPMorgan can’t buy everybody.”

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  • JPMorgan chooses Vestwell’s tech for small-business 401(k) services

    JPMorgan chooses Vestwell’s tech for small-business 401(k) services

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    Vestwell, a digital recordkeeper for 401(k)s and savings plans, has forged a partnership with JPMorgan Chase.

    JPMorgan Asset Management will be using Vestwell‘s technology to run its Everyday 401(k) program for small businesses, the companies announced on Thursday. 

    “Enhancing our offering by coupling a modern technology platform with an assigned client success professional, like Vestwell, will enable us to quickly and efficiently meet the increasing demand [as the retirement industry grows],” said Steve Rubino, head of retirement at JPMorgan Asset Management. 

    Vestwell has also formed partnerships with several banks including Morgan Stanley at Work, the workplace solutions arm of Morgan Stanley; Wells Fargo; and RBC Clearing and Custody.

    Aaron Schumm, founder and CEO of Vestwell, has formed several partnerships with large banks.

    However, “this new partnership with JPMorgan showcases the flexibility in creating access to workplace savings programs through thousands of bank branches and digital distribution solutions to reach a significantly larger audience of small businesses across the country,” said Aaron Schumm, founder and CEO of Vestwell, via email. 

    As JPMorgan expands its recordkeeping options in the small plan market, “Vestwell’s recordkeeping technology helps JPMorgan provide its small business clients with a user-friendly and streamlined solution, including small businesses that require the use of TPA [third party administrator] involvement,” Schumm said.

    Wealth managers are focusing on small-business retirement plans “for both offensive and defensive purposes,” said Andrew Besheer, the director of Aite-Novarica Group’s wealth management practice, via email. “Vestwell has partnered with a number of well-known wealth managers to deliver their retirement plan platform, but JPMorgan Chase is certainly one of the biggest names on their list. For JPMorgan, this gives them a great platform to allow their advisors to offer a service that aligns strongly with their small and midsize business banking relationships. This should extend wealth management into those relationships, creating uplift for that business as well as enhancing stickiness for the banking relationships.”

    Vestwell was one of American Banker’s Best Places to Work in Fintech in 2022.

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  • Fintechs tout ways to invest business clients’ cash above FDIC limits

    Fintechs tout ways to invest business clients’ cash above FDIC limits

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    Businesses that want to safely stash sums of cash above Federal Deposit Insurance Corp. limits have options that don’t involve juggling multiple accounts at multiple banks.

    They can invest directly in government money market funds or Treasury bills. They can inquire about programs within their bank, such as deposit networks and reciprocal arrangements engineered by IntraFi and the like, or automatic sweeps of amounts exceeding $250,000 into money market mutual funds.

    Or they can turn to fintechs that offer a tech-forward version or combination of the above.

    The disconnect between the size of accounts that enterprises typically maintain and deposit insurance levels has existed for a long time, said Brian Graham, a partner at Klaros Group. But the three days between Silicon Valley Bank’s failure and the FDIC’s assurance that it would cover uninsured deposits jolted people into action.

    “There has been a lot of scurrying around in the last several weeks as these organizations figure out what they want to do,” said Graham in a March interview.

    Fintechs such as Meow or Vesto, and business-oriented neobanks such as Brex and Mercury, have mechanisms that let business customers invest idle cash in Treasuries or money market funds. Some companies began turning to Meow and Vesto well before the recent bank collapses, particularly for easy investing in low-risk, high-yield instruments. As such, the reasons they have to stay are likely to persist even if the FDIC elevates levels of deposit insurance for businesses.

    “The fintechs are moving faster” than banks, said Graham. “They are piecing things together to come up with solutions that they expect will appeal to customers, and they are not wed to a single set of tools.”

    The safety of each investment product varies.

    “There are lots of flavors of money market mutual funds and lots of flavors of government securities,” said Graham. “U.S. Treasury is a different credit risk than some local sewer authority in a muni bond.”

    Mercantile, which partners with organizations to create custom branded cards, has been holding excess cash at Vesto the past six-plus months. Vesto defines itself as a cash management platform for venture capital-backed startups and mid-market businesses. It builds customized portfolios for its customers according to their risk tolerance, liquidity needs and more, typically investing in Treasury bills, money market funds, corporate bonds and certificates of deposit. The back-end custodian is BNY Mellon Pershing.

    “With the market changing and Treasuries being a little more interesting, we wanted something that was very easy to use and exposes us to a high-yield Treasury option without endangering cash at hand,” said Samuel Poirier, CEO and founder of Mercantile. “Vesto understood the need to take cash out on a monthly basis to fund the company.”

    He chose Vesto, which launched in 2022, because of its simplicity and its understanding that companies such as his will withdraw funds on a regular basis. He only invests in U.S. Treasuries through Vesto.

    Benjamin Döpfner, founder and CEO at Vesto, says he has seen an influx of new customers since SVB collapsed. 

    “There has been a desire to diversify their holdings and cash,” he said. “We found a lot of companies have almost all their cash sitting in one bank account.” He says his customers choose Vesto to find a secure home for their cash and to earn high yields.

    “Oftentimes founders and CEOs don’t have the capital markets experience to do this themselves,” said Döpfner.

    Döpfner describes the company’s investment style as “incredibly conservative.”

    “We take the viewpoint that safety and liquidity are priority number one and yield is priority thereafter when managing corporate cash,” he said. “We only work with highly liquid ‘ultra-low risk’ investment products like U.S. Treasuries.”

    Stocktwits, a social network for traders, began investing in Treasury bills through Meow well before SVB and Signature Bank collapsed in March. Meow is a banking platform that lets businesses purchase Treasury bills using partner registered investment advisors and broker-dealers.

    “As the Fed started to raise rates, we saw an inverse yield curve, so it made sense to put some of the firm’s capital to work in addition to diversifying credit risk,” said Philip Picariello, vice president of finance and operations at Stocktwits.

    He considers the firm’s capital as being divided among three buckets: immediate liquidity for payroll and accounts payable, near term liquidity to fund product development and core capital. Like Poirier, he wanted to earn yield in a low-risk way.

    “When I started digging into Meow I liked the team and the way they built it,” said Picariello. “I was sold on the fact that BNY Mellon Pershing is in the back end. It’s very seamless to move money over, allocate it, and ladder it out.” Stocktwits uses an insured deposit sweep program at its bank to protect funds that should stay liquid in the near term. He allocates the rest to Treasuries through Meow based on what the company needs in the next month, three months or six months.

    As suggested by Stocktwits’ strategy, these accounts are not meant to hold operating cash.

    “When you want to get your money, it takes some time,” said Graham. The success of this strategy “depends on your ability to look ahead and know when you need the cash.”

    Picariello is not concerned.

    “If a corporate treasurer or chief financial officer has a good handle on upcoming liabilities, you should never have to worry about it taking a day or two to get your money,” said Picariello.

    Döpfner said almost all the investment products his company works with are highly liquid, and customers can usually access their cash within one to two business days. Brandon Arvanaghi, CEO of Meow, said in a March interview that it would take customers one to two business days to receive their funds after selling their T-bills.

    Business-oriented neobanks have developed their own products they hope will entice customers to park large amounts there instead of at regular banks. Brex has increased its deposit insurance from $1 million to $6 million since SVB’s failure by using a sweep network. Customers can choose to store funds above that limit in a BNY Mellon money market fund. Mercury has increased the amount of cash it can protect per customer to $5 million in a product called Vault. Deposits exceeding $5 million are placed in a money market fund that is almost entirely invested in U.S. government-backed securities.

    Brex and Mercury touted thousands of new customers since the bank failures in March, although it’s an open question as to how many they will keep over the long term. Döpfner of Vesto and Arvanaghi of Meow also report a wave of new customers in the wake of those disasters.

    “These kinds of alternatives tend to be really effective if you know you won’t need the money for X period of time and you’ll get a heads up when you need it,” said Graham.

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  • Community bank, loan marketplace pilot transaction-based underwriting

    Community bank, loan marketplace pilot transaction-based underwriting

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    Texas National Bank has been strategizing how to tackle social issues in the Rio Grande Valley. 

    One example is its no-fee small-dollar loan, built with bank and credit union technology provider Velocity Solutions and meant to counter the abundance of payday lenders operating in the bank’s communities. The interest rate will hover just under 18% and the product is expected to launch within days.

    Another initiative is a pilot project with Lendio to deploy transaction-based underwriting for small-business loans. Although Lendio is better known for its business loan marketplace, where it sources borrowers and solicits offers from its network of bank and nonbank lenders, it is testing alternative underwriting capabilities with Texas National, which is based in Mercedes.

    “We realized through years of experience that fintech lenders have gotten really sophisticated at quickly analyzing borrower applications, generating decisions and often using transaction data as a way of evaluating the borrower rather than relying so heavily on income statements and credit scores,” said Philip Taliaferro, general manager and senior vice president of software as a service at Lendio.

    The goals are reflective of other small banks and minority depository institutions: to learn how to lower costs, increase efficiency and improve the customer experience using technology, in this case with small-business loans. Taliaferro and Rey Garcia, executive vice president of Texas National, will discuss their pilot on June 12 at American Banker’s Digital Banking Conference.

    “When we see the fintech world taking over the banking world, it keeps me up at night,” said Joe Quiroga, president of the $679 million-asset Texas National. “This was our small attempt to say, we’ve got to innovate and keep up with it; we might not develop the next best product but we will learn a lot,” such as which algorithms or automated processes can take over more efficiently from human analysis.

    “We don’t have huge expectations for growth, but we have huge expectations for learning,” he continued.

    Such experiments with alternative data may also trigger the question of how viable alternative transaction-based underwriting is compared to traditional credit scores.

    Texas National’s largely immigrant customer base frequently operate in cash, and do not borrow often, which means creditworthiness may not be reflected in their credit scores.

    “What got us excited about this product is how we can be socially mindful and create this responsible solution to allow small-business owners that primarily operate in cash to get credit,” said Garcia. “This tool that analyzes alternative data lets us improve the speed and accuracy with which we make decisions.”

    Lendio’s technology will mine customer deposit data from the bank’s core system, run it through algorithms and classify the transactions. It will tabulate the results in its model, detect factors such as revenue over the last 30 days, or number of days where funds dropped below a certain threshold, and pre-qualify customers for a loan.

    Taliaferro cites two reports: one from the Bank for International Settlements in 2022 that studied two lenders that used alternative data and found they predicted future loan performance more accurately than the traditional approach to credit scoring, particularly in areas with high unemployment; another co-written by New York University associate professor of finance Sabrina Howell, which found that process automation boosts lending to Black-owned businesses.

    “If I rely exclusively on traditional credit scoring and traditional underwriting models I am more likely to exclude the type of borrower I should be more focused on supporting,” said Taliaferro.

    Texas National is starting slow. Currently it is restricting the pilot to existing customers, because the bank has a rich history of their transactions and wants to test the solution with well-known customers of the bank before opening it to a larger market.

    “We put on tighter risk limits so we can monitor performance, measure progress, and evaluate potential issues that come up, then iterate from that,” said Garcia. “We’re trying to be mindful about how much we are lending until we’re more comfortable.”

    Although Texas National is its first pilot customer, Lendio is also piloting transaction-based underwriting with a large regional bank and another community development financial institution.

    Transaction data has not reached the mainstream with underwriting among traditional banks.

    “I’m willing to argue that statistically speaking, it won’t result in better loan repayment because historical transaction data is very difficult to utilize to extrapolate future transaction data,” said Mitch Wein, head of community banking and credit unions at Aite-Novarica. There are some businesses where transaction data may be more predictive than other types, he believes, for instance a business with fixed and steady contracts underpinning its revenue.

    However, nontraditional data can augment credit score underwriting to potentially give users better outcomes in certain segments of lending, said Wein. “If you can collect that data in a usable repository, in a consistent way, and tune the algorithms effectively, you can get that outcome, which is a win for the banks.”

    Texas National is currently using credit scores in addition to transaction-based data. The bank says it will continue to assess the underwriting evaluation process as the product evolves.

    “Over time we will see the importance of alternative data continue to increase,” said Wein, “as there is more data being generated and because of capabilities like artificial intelligence and more advanced machine learning, [which means we] will be able to more deeply evaluate the quality of that data for algorithmic purposes.”

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  • Cybersecurity researcher finds 1 million invoices in public, unencrypted database

    Cybersecurity researcher finds 1 million invoices in public, unencrypted database

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    A cybersecurity researcher says he discovered a public, unencrypted database earlier this year associated with a business banking fintech that contained more than 1 million names, physical addresses and phone numbers of consumers and business owners who used a certain invoice-creator app.

    The database is said to have been secured in January, and where the fault for any vulnerability lies is murky. But the incident highlights the widespread problem of unprotected online databases — which sometimes are linked with seemingly innocuous, free apps — that present risk management challenges for players from digital startups to large banks.

    The security researcher, Jeremiah Fowler, announced the disclosure Wednesday and said the database belonged to NorthOne, a Toronto-based fintech offering mobile-first banking to small businesses, because the invoices he found in the database say “powered by NorthOne.”

    NorthOne CEO Eytan Bensoussan told American Banker that, despite appearances, the vulnerability actually stems from an app called InvoiceMaker that is not connected to NorthOne. He acknowledged that some of the people who helped build the app now work for NorthOne and that the company marketed itself with the app, but the app has “no product, technology or corporate connection” to his fintech.

    “NorthOne is a completely separate entity from InvoiceMaker,” Bensoussan said.

    Yet NorthOne launched a free invoice creation tool in 2018, according to multiple news reports. The app, which prominently featured NorthOne’s old logo and branding, used both the names Invoice Maker and Free Invoice. As of June 2022, the app had 4,900 ratings on the Apple app store.

    Invoices in the database, which was not password-protected, included names, physical addresses, email addresses, phone numbers and details about the services provided.

    Jeremiah Fowler

    Despite the invoice app using NorthOne’s old logo, “there is no crossover between databases,” Bensoussan said in an email. In explaining why NorthOne’s old logo appeared in the app, he said NorthOne once “leveraged Invoice Maker for awareness purposes, but as you can see from the outdated logo, that was a long time ago.”

    Bensoussan said his team terminated the invoice creation service after Fowler told them about the vulnerability in January, and NorthOne’s invoice creation app is no longer available on the app store. Fowler said the database he found is also now secured, thanks to his disclosure.

    In his comments, Bensoussan played down the importance of the vulnerability, saying the invoicing app had “no payment capabilities and did not involve any payment data.” Rather, the app was “a free PDF generator for invoices,” he said, adding it had “as many as 20,000 users at its most popular but was due to be sunsetted later this year because it had run its course.”

    Security researcher Brett Callow said he could not comment on the specifics of this invoice data vulnerability but noted that it is often difficult to determine the significance of exposed databases. Often, it is not necessarily clear even to the company that manages the data whether anybody other than the researcher who discovered it accessed the data, he said.

    northone1-850x638.jpg
    Invoices found in the database also feature NorthOne branding. The fintech’s CEO maintains the company affected a now-defunct invoice creation tool, not NorthOne.

    Jeremiam Fowler

    “Still, even if it was only a researcher who accessed a database, that means an unauthorized third party had access to information — and that’s a data breach,” Callow said.

    Ali Allage, CEO at Bluesteel Cybersecurity, offered a different take, saying a data breach occurs when data is taken without the knowledge or authorization of the system’s owner. That does not appear to be the case here, she said, for which NorthOne should consider itself lucky.

    “This organization got extremely lucky that this didn’t snowball into something worse and having to deal with much larger consequences,” Allage said.

    Bensoussan said “no breach or leak occurred,” adding “we have confirmed no data was ever compromised or made public.”

    As of Friday, no state attorneys general had reported any data breaches from NorthOne, Free Invoice or Invoice Maker, suggesting the responsible party has not reported the breach pursuant to any of the state laws governing data breach disclosures.

    According to Fowler, his interaction with Bensoussan — an email in which the CEO let the researcher know the vulnerability had been taken care of — provided no indication that he had misidentified the responsible party. Had he messaged the wrong company saying he found their exposed database, “they would have been very eager to tell me that it does not belong to them,” he said.

    Bensoussan said he is “thankful that the issue has been addressed” and said Fowler called his team’s attention to the vulnerability before it escalated into a breach.

    “In this case, the system worked as intended with a security researcher helping to address a problem before it became an issue,” Bensoussan said. 

    Invoices are a “goldmine for criminals,” according to Fowler, because they can target victims using both the contact information they glean from the documents and the details of private transactions.

    “The criminal could reference the real invoice number and transaction details, making it difficult for the victim to doubt the scammer’s legitimacy as a representative of the company or service provider,” Fowler said.

    The database was so easy enough to find, Fowler said, that it would have required little expertise for a criminal to get to it — and no password to decrypt the files once found.

    Fowler monitors multiple IoT search engines to find the data, including the exposed database of invoices. IoT search engines scour the web for internet-connected devices like webcams and smart home appliances. Shodan is a popular example; others include Censys, GreyNoise and ZoomEye.

    According to Fowler, the incident is an example of why companies need to establish good processes for and relationships with security researchers, since the analysts work to protect data and plug security vulnerabilities. In many cases, including this one, they do so free of charge.

    “The biggest thing is that companies need to take that extra step and realize that, if you collect data, it’s valuable to somebody other than you,” Fowler said.

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  • TitleMax hack exposes 4.8 million customers’ data

    TitleMax hack exposes 4.8 million customers’ data

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    TMX Financial, which operates title loan brand TitleMax and other services, publicly disclosed on Thursday that it suffered a data breach exposing the personal information of 4.8 million people, including their Social Security numbers.

    The company said in a letter to affected consumers that it detected suspicious activity on Feb. 13 and concluded on March 1 that there had been a breach starting in December. Hackers stole the data between Feb. 3 and Feb. 14, according to the letter.

    The specific information involved in the breach, according to TMX, “may have” included names, dates of birth, passport numbers, driver’s license numbers, federal or state identification card numbers, tax identification numbers, Social Security numbers, financial account information, phone numbers, street addresses and email addresses.

    One measure financial companies can take to protect personally identifiable information (PII) on consumers is to collect less of it, according to James McQuiggan, a security awareness advocate for cybersecurity awareness training platform KnowBe4.

    “One of the most critical steps companies can take to protect PII is collecting only the data necessary to conduct business and storing it securely so unauthorized parties cannot access it,” said McQuiggan. “Organizations should also ensure that any third-party vendors or partners they work with are implementing strong cybersecurity measures.”

    Among financial companies, the breach is the largest so far this year to be reported to the Maine attorney general’s office, which publishes reports about data breaches affecting any Maine resident.

    The data breach is not the only trouble TMX has faced this year. The Consumer Financial Protection Bureau announced on February 23 that it would fine TitleMax $10 million for violating the Military Lending Act. TitleMax allegedly provided title loans to military families illegally and, oftentimes, by charging nearly three times the 36% annual interest rate cap, according to the CFPB — a practice that it has allegedly engaged in since 2016.

    Debt collector NCB Management Services also reported a large data breach earlier this month. On March 24, the company told the Maine attorney general that hackers stole data from 490,000 consumers, specifically information about their ID cards and Bank of America credit card accounts. That breach did not impact Bank of America’s systems, NCB emphasized in a letter to affected consumers.

    So far this year, 10 other financial companies have reported data breaches affecting more than 500 people. The bank or credit union with the largest breach so far this year is Hatch Bank, which had 140,000 consumers’ data stolen. In that case, hackers exploited a zero-day vulnerability in file-transfer software known as GoAnywhere, according to a letter the bank sent to affected customers.

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  • What bankers can learn from the 2023 banking crisis

    What bankers can learn from the 2023 banking crisis

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    Transcription:

    Penny Crosman (00:03):

    Welcome to the American Banker Podcast. I’m Penny Crosman. What can be learned from the recent failures of Silver Gate Capital, Silicon Valley Bank and Signature Bank? We’re here today with Brian Graham, partner and co-founder of Klaros, an advisory and investment firm. Welcome Brian. 

    Brian Graham (00:19):

    Thanks for having Penny. It’s great to be here. 

    Penny Crosman (00:21):

    Thanks for coming. So I understand you were involved in some past banking crises. Can you tell us a little bit about that? 

    Brian Graham (00:30):

    Sure. I think it’s another way of saying I’m old, so I’ve seen my fair share of these. So beginning in the late eighties I was involved as an aid to then Congressman Chuck Schumer in the savings and loan crisis. And in the 1987 stock market collapsed, the Brady Commission that studied that. And then during the global financial crisis, I was involved by working with the F D I C in a publicly traded non-bank finance company to help a failing bank through a transaction that the F D I C facilitated. So been through a few of these wars. 

    Penny Crosman (01:10):

    And are there any clear differences between what’s happened over the last couple of weeks and what happened in those older crises? 

    Brian Graham (01:21):

    So there are always differences. Every one of these things is triggered by a different confluence of events and has its own little spin. But the sad truth about it is that they’re all kind of out of the same cloth. Something happens that triggers a liquidity crisis, but that liquidity crisis really only peels back the layers that were covering underlying problems in the global financial crisis. It was the credit quality of the underlying mortgage loans and the the fact that there were a bunch of really bad loans there in both the savings and long crisis. And to a large extent today, it was about the interest rate risk that was embedded there once you pulled back the curtain. And the fact that a lot of assets with long-term fixed rates were booked at a time when interest rates were lower, interest rates go up, they go down in value. And so even though it’s not caused by credit risk, it’s, it results in the same thing. So I wish I could tell you everyone’s a new scenario, but there’s a lot of paths that echoes here. 

    Penny Crosman (02:32):

    Well, so to piggyback on that point, how widespread do you think that problem is of banks that have assets on their books that have lost value? It seems to me that would be fairly common. 

    Brian Graham (02:47):

    It is very widespread, but it’s not whether or not they have assets that have lost value because interest rates have gone up. The answer to that is yes, for every bank out there, what the more important questions are twofold. One is were those positions hedged? Did the value of your liabilities change as the assets change? So did you match fund them? Did you have explicit hedges interest rate derivatives and the like to protect yourself against that? And the second is how big were these exposures, these fixed rate exposures relative to your total balance sheet? The problems don’t occur when somebody has assets that are a small proportion of their balance sheet that get impacted. It’s really when it’s large and they didn’t hedge it, that things become very problematic. 

    Penny Crosman (03:44):

    So if you were running a bank today or a CFO of a bank today, perhaps, would you be taking a hard look at the balance sheet and trying to perhaps make some changes if there were a lot of say long-term treasuries, et cetera? 

    Brian Graham (04:05):

    Well, I would hope that if I were the c o of a bank, I would’ve done this long before any of this happened because that’s kind of our job as CFOs in that context. We’re supposed to manage these kinds of risks. We’re supposed to monitor and measure them. And if you were monitoring and measuring the interest rate risk embedded in your balance sheet and doing it effectively consistent with the right asset liability management policies and everything else, you wouldn’t find yourself in a position where you had to do something dramatic or severe. It’s only when that isn’t managed effectively that you really get that brutal wake up call. 

    Penny Crosman (04:50):

    And so why do you think this was the case for so long, especially for Silicon Valley Bank, and why wouldn’t their regulators have said something to them sooner to correct this issue? 

    Brian Graham (05:05):

    Yeah, so Silicon Valley Bank is an outlier and we just have to acknowledge that if you look at their unrealized losses on their securities portfolios, whether those securities were held at available for sale, in which case they’d show up and that weird A O C I bucket on the accountant statements or in held with maturity, in which case they, they’d be disclosed as a foote. You can see what’s happened to Silicon Valley banks assets over the last year and a half as the Fed has steadily raised interest rates. And as we speak here today, they just raised him again another 25 basis points and it’s really not a surprise. What is different though at Silicon Valley Bank is first those fixed rate investments were a very large percentage of their balance sheet much larger than is the case of most other banks because Silicon Valley Bank did not really have a large loan portfolio. 

    (06:08)

    So they kind of used investment securities to bolster, I presume, to bolster their net interest income and had just a lot of these fixed rates securities. And the other thing is you can see how these unrealized losses accumulated with time and it’s pretty clear, again, going back to the first quarter of 2022, and it’s pretty clear that no action was taken in the first quarter of 2022 or the second quarter or the third quarter or in the fourth quarter or even the first quarter of this year until their hand was forced by a rating agency basically. And that’s that, that’s a shame. So if you add up all of the unrealized losses on their securities, they exceeded the total tangible book value of the bank. And it’s one thing to argue if you’ve got some variation in your securities portfolio values and it moves things up or down 50 basis points or something like that, but if your exposure to interest rate risk is going to wipe out your entire capital, that’s something that should have been handled with respect to the, I’m sorry, pe, go ahead. 

    Penny Crosman (07:24):

    No, it’s just curious that as you say, if no action was taken all of 2022 that no bank examiner pointed that out or there wasn’t any attempt to rectify it. 

    Brian Graham (07:38):

    So I don’t think we know whether or not that was the case. I think that’s to be determined as they look at what did and didn’t happen. From a regulatory point of view, I would say it’s pretty clear that the way in which the regulatory capital ratios are constructed for banks under 250 billion in size played a role here that if you are JP Morgan Chase, you can’t kind of ignore these unrealized losses. They show up in various of your capital requirements and if had made bad interest rate decisions and put all of your book value at risk and used it up in these unrealized losses, the regulators would’ve been all over them because their capital ratios would’ve been in the tank. And that isn’t true for smaller banks because they’re allowed to ignore any and all of these unrealized losses. And unfortunate thing here is, again, if it were a difference of a half a percentage point on a capital ratio, that’s okay, but when it takes a bank that the day before failure was had nearly 8% leverage capital as recorded by the rules and marks it to zero because essentially all of that 8% was chewed up with these unrealized losses, that’s probably something for the policymakers to have a think about. 

    (09:15)

    Whether that’s the way we want those regulatory ratios to operate, they should have for, first of all, I would say even if the regulatory ratios aren’t sending a warning signal management of the bank should have been, I think in my judgment, much more active in seizing the bull by the horns. But I hope and that the regulators were engaged in this well before the events of the last two weeks. But I don’t know one way or the other, 

    Penny Crosman (09:46):

    So correct me if I’m wrong here, but my sense of one aspect of these failures is that all these banks suffered a run on the bank, and that was partly because people became aware of the falling value of these assets on their books, the losses that Silicon Valley Bank suffered when they tried to sell off some of its assets and then people went and through email and through social media told others to pull all their money out of the bank at once. Is it fair to say that these banks could have survived if they hadn’t had those kinds of runs? 

    Brian Graham (10:27):

    I think they could have kicked the can down the road a bit more. I mean, as we were just discussing Silicon Valley encourag, its first unrealized losses in scale and 15 months ago, and it didn’t kind of come to a head until recently, but I did it, the fact that you can kick can down the road a little bit doesn’t mean you’ve solved the fundamental problem. And the fundamental problem here was there really two sets of capital standards at work. There’s one that’s run by the regulators and Silicon Valley Bank the day before it failed past that swimmingly. And there’s one that operates within the mines and hearts of the counterparties to the bank, whether it be depositors or customers or loan customers or anybody else. And those customers spoke very, very loudly and very, very quickly and very collectively that they didn’t believe that the institution was in good shape. 

    (11:32)

    And candidly, they were right if this was just a liquidity crisis. The Fed and the federal home loan banks and everything else have a ton of tools to serve a pure liquidity crisis. But it was more than that. I think I started by commenting that what’s old is new again, and that these crises kind of echo through the past here. There is one thing new about this one in a very real way, and that is Twitter and the ability of customers to grab their phone and initiate a wire or an ACH transfer or those kinds of things dramatically accelerated how fast the run happened. So it didn’t occur over weeks or months. It occurred over minutes. And I think that really is something that we as a banking industry and probably the regulators as supervisors, weren’t as prepared for as we probably in retrospect should be because things are going to happen much more quickly than they had in the past. The fact that it was a liquidity crisis that laid bare the underlying problem important, but the underlying problem stays true regardless. 

    Penny Crosman (12:56):

    Yeah, I was talking to one banker who felt that if this had happened 20 years ago and we were talking about Gate capital specifically at this point, if this had happened 20 years ago, the bank would’ve had more time to kind of regroup. And I’m sorry, we were talking about Silicon Valley Bank because Silicon Valley Bank happened so quickly after Silver Gate announced some of its problems that between the speed and the coinciding of those two banks kind of falling into difficulties at the same time that, and then everybody talking about this on Twitter and venture capital firms telling their portfolio companies to pull all their money out, that all of that kind of just brought Silicon Valley Bank down in a way that 20 years ago maybe might not have happened, maybe 20 years ago. The bank could have quietly gotten some more funding, fixed some of the issues that it had, and before everybody knew about it and started talking about it and initiated Iran on the bank. Do you think that has merit? 

    Brian Graham (14:15):

    I don’t think it would’ve changed the ultimate outcome. The ultimate outcome could have been wildly less painful. So the ultimate outcome is the bank incurred a bunch of losses, unrealized or not, those were losses and it was going to need to fill the resulting hole on balance sheet with incremental equity. If in my judgment, if the bank had started to do that earlier, if they’d started to do that a year ago, they’d be in fine shape. They could have raised a significant amount of equity on a very orderly basis at probably very attractive evaluations. But if they’d even started a week or two or three or four earlier than that than the panic at the end, I think they could have managed the situation to a much better outcome. They still would’ve needed to fill the hole in the balance sheet. But that speed that you talk about Penny is really important because so many of the tools that supervisors have at their hands are they take time, they take time to figure out, they take time to implement. 

    (15:28)

    There was a Wall Street Journal story today about the TikTok of what happened at Silicon Valley Bank and talking about how they needed to send a test file from the Fed over to from the Federal Home loan banks over to the Fed, and it took ’em too long and they just passed the 4:00 PM mark and all those kinds of things. And it goes to show that what Twitter and everything else has done is reduce the time in which decision makers and policy makers have the freedom to act. And that really means that puts the onus on all of us to do a lot more planning in advance because you can’t wing it when you’ve got an hour to figure this stuff out and to make sure we’re kind of ahead of that curve because we’re not going to have time in the midst of any crisis, whether it be institution specific or more to kind of figure that out. 

    Penny Crosman (16:25):

    Now in the case of Signature Bank, Barney Frank, who was on the bank’s board has said the bank was not insolvent, but that regulators kind of rushed in to seize control because it was a crypto friendly bank. Do you think that point has any merit? 

    Brian Graham (16:44):

    It’s really hard to tell from the outside. There are a couple things that are consistent between Silicon Valley and Signature that are probably important to notice. And the most important is that they both had very large balances of uninsured deposits and logically uninsured deposits are the ones that are most likely to leave the soonest if there are hints of concern about the solvent saving institution. And so I think they were both kind of in that circumstance. Interestingly, the reason they were in that circumstance was because they were serving commercial customers by and large, we’ll get to the crypto in a second, but they were serving commercial customers and deposit insurance and the deposit insurance cap of $250,000. That makes sense if you think about it from the perspective of a household $250,000. So it’s a lot of money to have in a checking account for a household, but you’re a company and you have any material number of employees, $250,000 doesn’t cover payroll, it doesn’t cover the healthcare insurance premiums you got to pay, et cetera. 

    (18:01)

    And by their nature, those kinds of customers tend to hold balances that are much larger than that. And so these two banks, because they were serving companies, which is obviously an important part of the whole economy here, were susceptible to that dynamic. If you throw in the crypto thing, I think it is it not unreasonable to speculate a solids, but it is speculation, which is Silicon Valley Bank had a small amount, relatively small amount, I think it was like 3 billion that my memory serves of reserves that back a stablecoin. The stablecoin are the ones that are designed to always be a dollar and supposedly are fully backed. And those reserves, since it’s 3 billion, is greater than $250,000 not fully insured. And over the course of the weekend, you could see by tracking the market price of these stable coins, that there was a great deal of concern until the government came in and dealt with the uninsured deposits issue about whether or not stable coins would kind of blow up. 

    (19:20)

    It turns out signature had orders of magnitude, more stablecoin reserves in deposits on their balance sheet than Silicon Valley. It wouldn’t surprise me if that dynamic contributed to the speed at which the government decided to act with respect to signature. And I wouldn’t at all take a different opinion than former banking committee chairman of Marty Frank with respect to the outlook of regulators towards crypto, which has become quite negative over the past six to 12 months. I’m not sure that’s really what caused either the underlying problem or the actions that were taken. Again, I wasn’t in the room. I don’t know for sure. 

    Penny Crosman (20:07):

    So if you were running a bank right now, that’s not one of these three, but any other, say mid-size or smaller bank in the us, what would be some of the things that you might be trying to do right now? You talked about looking at the balance sheet very carefully, maybe doing some hedging, maybe making sure you’re adequately capitalize. What are some of those specific things that you think banks ought to be pretty wary of right now? 

    Brian Graham (20:42):

    I think obviously interest rate risk management is got to be top of the list list for almost a generation. Interest rates have been close to zero or going down, and as a consequence, a lot of the people who are running these banks and operating in the treasury departments just haven’t had personal real life experience with rates going up. And I think we probably have lost some of that muscle tone of interest rate risk management because we didn’t have to do it for 20 plus years or put differently. We should have been doing it, but it didn’t have an impact. This rates always moved in a way that was net favorable. So stretching out those muscles and working out our interest rate risk management, I think has got to be a critical priority. And the sets further move today to increase interest rates in other 25 basis points, underscores that it’s going to continue to be important regardless of what happens. 

    (21:48)

    So that’s number one. And that means making sure you understand the sensitivity of your assets and your liabilities to rates, and it means matching both sides of your balance sheet as best you can. And it means making sure you don’t have outsized exposure on either of your asset or your acid reliability side to your balance sheet to significant swings and interest rates. So I think that’s number one. Number two is liquidity is really important right now. And if I were a banker, even if I had plenty of liquidity right now, I’d be making sure I had the right collateral, federal Home Loan bank to ensure I could access funding there. If God forbid it became necessary, I’d make sure I’d already tested my files with the Federal Reserve to make sure I could access the discount window as opposed to waiting until the middle of a crisis. 

    (22:45)

    I would figure out what my Fed funds lines were with correspondent and other banks to ensure I had access to that kind of funding. And I’d be thinking about the structure of my deposit offerings, pricing and terms and everything else to maximize my ability to manage my liquidity risks. God forbid such should something happen. So I think that’s really, really important. The third thing I do is we talked a minute ago, penny, about how time scales have just been compressed dramatically by technology. I think you got to do some scenario planning here. I think you’ve got to do something that’s analogous to what we do in the systems world of business continuity planning and phone trees and who calls who and can work from home and access their accounts and all that kind of stuff that we’ve done for years. On the system side of things, I think we need to do some of that on the liquidity and asset liability management side of things to more this when it’s not a crisis so that we are prepared and we know who’s supposed to do what in order, who’s supposed to call home when God forbid a crisis does emerge if it does. 

    Penny Crosman (24:08):

    Yeah, and in conversations I’ve had with fintechs, I’ve gotten the sense that any FinTech that didn’t have a CFO is now getting one and really trying to make sure they’ve got the basic accounting principles all covered, so, well this has been really helpful. So Brian Graham, thanks so much for joining us today for all of us. Thank you for listening to the American Banker Podcast. I produced this episode with audio production by Kevin Parise. Special thanks this week to Brian Graham at Klaris Group. Rate us, review us and subscribe to our content at www.americanbanker.com/subscribe. For American Banker, I’m Penny Crosman and thanks for listening.

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    Penny Crosman

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  • State Street Global Advisors’ bid to speed up client onboarding

    State Street Global Advisors’ bid to speed up client onboarding

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    State Street Global Advisors aims to cut the average time it takes to sign up new customers by 10% in the next year through a partnership with Appian, a software company that uses automation to enhance workflows.

    The investment arm of Boston-based State Street Corp. has been using low-code technology from Appian, which analyzes the companies’ workflows to find where actions can be automated or streamlined, since 2011. Automating processes and incorporating artificial intelligence is a high priority for financial institutions, said Joe Davey, a partner at the technology consulting firm West Monroe.

    “Banks and financial institutions are interested in low-code solutions, like automation, that allow them to deploy in a framework that can be managed, has standard tools people can be trained on, and doesn’t really require engineering time and investment,” said Davey, who isn’t involved in the State Street-Appian effort.

    State Street Global Advisors, which has $3.48 trillion of assets under management, has already shaved the average customer onboarding time by 20% since 2016 with Appian. Dennis Mackey, who heads business process management, reference data and data governance at State Street Global Advisors, said the software company has been “integral” to its current data-population process.

    “Appian has been able to build with us a dynamic workflow where we can pull in the right people and get the right data at the right time so we can implement these products in a timely manner,” Mackey said. “Given the breadth of offerings that we have, you can’t do one size fits all. It has to be very dynamic in the way that the workflow responds to the questions that you’re asking stakeholders.”

    Now, State Street Global Advisors will utilize a technology feature that McLean, Virginia-based Appian rolled out last year, called process mining, to find other bottlenecks in its customer onboarding workflow and trim down the process even further by the first quarter of 2024.

    Here’s how process mining works. Appian extracts data collected during the onboarding process, which includes attributes like time stamps and product types, from the logs of underlying systems that State Street Global Advisors operates, such as Salesforce. The software company then applies machine-learning algorithms to find the causes of slowdowns in processes, offer solutions and monitor progress.

    Appian co-founder and Chief Technology Officer Mike Beckley said the software company’s goal is to delegate work to the most efficient actor, whether that’s a robotic process automation bot, AI algorithm or a human. He added that he’s seen a rise in demand for automated processes, like straight-through processing, at financial institutions.

    “People are demanding that efficiency, and they’re demanding more automation,” Beckley said. “There’s enthusiasm for process mining so that [Appian clients] can prioritize their investments because you can’t automate everything. You have to find those most beneficial opportunities. People are being forced to do more with less. …Every CIO or CTO is looking for ways to save to cut costs.”

    Mackey said customer onboarding is an iterative process, in which the firm collects a series of information points, like the type of strategy or asset class of the customer. He said he wants State Street Global Advisors to increase automation use to gather and populate customer data fields in its records, which would also free up employees’ time to have conversations with clients.

    State Street Global Advisors has developed 18 applications with Appian, used by more than 900 employees. Mackey added that the firm is planning on integrating another Appian feature, intelligent document processing, to extract key information from contacts and putting that data in its records. 

    West Monroe’s Davey also said that banks are eager to incorporate AI in their systems, which can improve operating efficiency, service more customers and offer additional business lines, but not mandate changing existing infrastructure.

    “Automation is how you plug those interfaces in to realize your operational efficiency,” Davey said. “Banks are super excited about this because they want to offload more mundane tasks, standardize those tasks.”

    Davey said Appian is a strong offering for automation solutions, but not the only option. UiPath, another software company, also offers low-code workflow automation software. Microsoft PowerToys can provide similar products, though primarily to clients who operate Microsoft products across platforms. Low-code software, like Appian’s, also increases accessibility and time to market on application development.

    Beckley said Appian’s differentiators are its ability to pull data for clients from different systems, and its longevity, with nearly 24 years in the market.

    In 2021, Appian launched its data fabric, which can effectively merge data from different sources, like customer growth and compliance metrics, into one dashboard. For example, In State Street’s customer onboarding process, Mackey said Appian helps unite data from Salesforce and the firm’s product master into one record. Beckley said the data fabric is an alternative to migrating data to a public cloud or single provider.

    “Banks today are not like banks 25 years ago. They’re full of engineers who are building very complex systems,” Beckley said. “They’re also very useful to us in providing very specific requirements for how they want to manage their data, how they want their systems to work together, how security needs to work and how demanding their users are going to be. That translates into a very specific set of requirements that we have to build into our new product launch process.”

    Beckley said Appian’s products also need to be agile, because the best fit for State Street won’t align with the software company’s other clients, which include National Westminster Bank, Citibank, Goldman Sachs and the Securities and Exchange Commission. London-based NatWest recently announced that it wanted to use Appian to trim its risk governance process from 73 days to 73 minutes by the end of the year.

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    Catherine Leffert

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  • Neobank for Latino immigrants raises $4.5 million in seed funding

    Neobank for Latino immigrants raises $4.5 million in seed funding

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    A challenger bank for Latino immigrants has closed its seed round.

    Comun in New York announced Tuesday that it has raised $4.5 million in seed funding led by Costanoa Ventures with participation from South Park Commons and FJ Labs. Its digital banking app became available to consumers in September. 

    The company was co-founded by two immigrants to the United States from Mexico. Spanish is the default language for the app — which is linked to a no-fee checking account and a debit card — but users can switch to English. Applicants do not need a Social Security number to sign up for an account; instead, they can use an individual taxpayer identification number (ITIN), a foreign passport or another form of official foreign identification and must supply proof of address.

    “We built Comun to make it easier to thrive as an immigrant family in the U.S.,” said Andres Santos, co-founder and CEO of Comun. “My co-founder [Abiel Gutierrez] and I both experienced how challenging it can be to navigate the banking system as immigrants.” 

    Comun’s website defines the adjective “comun” as belonging to, or affecting, the whole of a community. Piermont Bank in New York, which has $448.9 million of assets, provides the underlying banking services for Comun. 

    Santos and Gutierrez will use the funding to expand Comun’s offerings and add more educational content, especially related to financial literacy. Comun makes money via interchange fees. 

    The number of neobanks that are bilingual or Spanish-first has ebbed and flowed in recent years. Dora, a challenger bank developed by the Rye, New York-based credit union USAlliance Financial and three other credit unions, offer bilingual services. It launched in September 2021. Viva First in Lubbock, Texas, bills itself as a Latino-first banking app. Welcome Tech, which builds products and services for immigrant communities in the United States, has a digital banking service called PODERcard that, like Viva First, is bilingual. The website for Crediverso, a financial technology company for Latinos, says that it is launching a banking app for Latino families. But the website for Tend, a neobank that launched in both Mexico and the U.S. in 2021, is no longer operational. 

    Other neobanks, such as Majority, target immigrants more broadly. Of the U.S.-based neobanks reviewed, Comun appears to be the only one whose website defaults to Spanish.

    Traditional financial institutions and other financial services companies have made their own overtures to Spanish-speaking people. For example, Community First Credit Union in Santa Rosa, California, trained its conversational bot to communicate in Spanish as well as English. In September, Square announced that its entire product line would be available in Spanish as well as English.

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    Miriam Cross

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  • Fintechs hate 36% loan rate caps. Do they have a point?

    Fintechs hate 36% loan rate caps. Do they have a point?

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    As states continue to impose 36% interest rate caps on loans, some fintechs say these blanket cutoffs do more harm than good. There’s a place for small-dollar loans that help people out in a pinch and come with a fee, they say.

    “If somebody needs $1,500 on a Friday because the brakes on their car blew out, we can facilitate getting that customer $1,500 on the same day,” said Todd Schwartz, founder and CEO of OppFi, in an interview. The loan would cost around $6 a day, an APR of 160%. “The APR may seem high but APR is calculated on an annual basis. It may seem expensive but OppFi has to cover certain costs.” There are no prepayment penalties and the loans are fully amortizing, he said.

    Small dollar lenders like OppFi provide credit to people who can’t get it elsewhere, argues Todd Schwartz, OppFi’s founder and CEO. But consumer advocates like Beverly Brown Ruggia believe short-term loans with high interest rates trap people in a recurring cycle of debt.

    “The question is, if you took that [loan] out for a month and paid $180, is it worth $180 to stabilize your financial situation, fix your car so you can go to work and take your kids to school and not derail yourself?” he said. “The APR is always looked at as a number, but it’s never looked at as, what value are you driving to your customer and are you actually solving a problem?”

    Regulators and consumer advocates think a 36% interest rate cap will protect people from predatory lenders. A growing number of states, including Illinois, Arizona, Colorado, Montana, Ohio and South Dakota, have made this view the law.

    The case against the 36% cap

    Those who object to a 36% rate cap have data to back them up: An analysis of the impact of the 36% interest-rate cap Illinois set almost two years ago found that it decreased the number of loans to subprime borrowers by 44%.

    Most borrowers said they were unable to borrow money when they needed it following the imposition of the interest-rate cap, according to the research paper, which was written by J. Brandon Bolen, assistant professor of economics at Mississippi College; Gregory Elliehausen, principal economist for the Board of Governors of the Federal Reserve; and Thomas Miller, professor of finance at Mississippi State University. They surveyed short-term, small-dollar-credit borrowers in Illinois. 

    “Only 11% of the respondents answered that their financial well-being increased following the interest-rate cap, and 79% answered that they wanted the option to return to their previous lender,” the report stated. “Thus, the Illinois interest-rate cap of 36% significantly decreased the availability of small-dollar credit, particularly to subprime borrowers, and worsened the financial well-being of many consumers.”

    Borrowers who have lost access to their lender have paid bills late, cut back on everyday expenses, coped with debt collectors, and had utilities turned off, the report said. 

    Some fintech leaders argue that the fees on small-dollar loans should not be translated into annual percentage rates. 

    “We do not believe that APR is an accurate measure anymore,” said Rodney Williams, co-founder of SoLo Funds, in a recent interview. Many fees that banks and other lenders charge, including rollover fees, instant pay fees, transaction fees, subscription fees and late fees, are not included in APR calculations but do make loans predatory, he said. 

    “APR is not what gets people in trouble,” Williams said. “I know what happens when you pay an extra $15 every two weeks to roll a loan over. Total cost is a much more accurate perspective.” 

    The case for a 36% cap

    Consumer advocates believe the 36% interest-rate cap has merit and should be applied to all loans.

    When Illinois passed its rate cap, Lisa Stifler, director of state policy at the Center for Responsible Lending, said the law will save the state’s families more than $500 million per year, “dollars that can be put back into the local economy.” 

    She and others have pointed out that people tend to get trapped by small-dollar lenders.

    “The industry likes to ignore the fact that, historically, the majority of people do not only borrow once and just pay it back; there’s a history of repeat borrowing multiple loans back to back to back to back to back,” said Beverly Brown Ruggia, financial justice program director at New Jersey Citizen Action, which has pushed for a 36% rate cap in New Jersey. “The people who enter into these loans and pay them right back have no problem. Those people exist, but what the industry makes its money on is repeat borrowers, and they know this.”

    The 36% rate cap came out of the 2006 Military Lending Act, Brown Ruggia noted. 

    “The military did a lot of research and looked at what was a reasonable number for the industry to continue to exist, but not cause the kind of harms that we’ve been seeing in repeat borrowing and people who are trapped in these loans,” she said. 

    As long as high-cost, low-dollar loans exist, people are going to use them, “as opposed to building a culture where there’s a reasonable interest rate across the country,” Brown Ruggia said. “We are still seeing this effort by the industry to sell this high-cost loan as the only solution to short-term problems. And what we see over and over again is repeat borrowers who sink themselves into endless debt. The industry’s always talking about innovating. Let’s innovate for something that gets people on their feet without usurious rates.”

    Schwartz at OppFi would like to see a federal small-dollar lending law and federal backing of these loans, similar to Federal Housing Authority-backed mortgages.

    “I think if the government was willing to talk about a small dollar lending rule where there was some type of backstop for insurance, lowering the rates would be a possibility,” Schwartz said.

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    Penny Crosman

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