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“There is no kind of dishonesty into which otherwise good people more easily and frequently fall than that of defrauding the government.”
These words of wisdom from Benjamin Franklin have, unfortunately, proven timeless. People have been defrauding the government for centuries, but last month, the US hit an estimated $45 billion in COVID-19-related unemployment fraud. Now the government starts the long, costly and inefficient process of recouping the money, conducting investigations and punishing those responsible. This process is often called the “pay and chase” model.
With all that fraud, it can be challenging for government agencies and private companies to separate the wheat from the chaff (or, in this case, the fraud from the noise). For example, is a person calling your call center with a device you haven’t seen before actually an existing customer with a new phone or someone attempting to take over an account?
These issues create room for inefficiencies and cost companies huge operational sums when they cannot tell the difference. But, going too heavy with stricter verification that may dampen the customer experience is also something you have to avoid. The good news is it’s possible to identify fraudulent activity with modern technology better and thus increase efficiency.
Related: The Government Is Not Immune to Account-Takeover Fraud, and That Could Be Trouble for You and Me
Modern fraud and its noisy neighbor
At its core, the focus of fraudsters has remained on tricking people into giving access to as much money or data as possible. It’s nothing new; the term “con man” was likely coined in the 1800s. Whether it’s Bill Starbuck’s “The Rain Song” from the musical 110 in the Shade, where the charismatic con man convinces townspeople to give him money to make it rain and end a drought, or someone calling your grandmother and pretending to be a government agency, fraud has always been, and always will be.
Our ability to close fraud loopholes is improving. Still, fraudsters are constantly creating new schemes, and technology continues to enable them to get better at fooling us and covering their tracks. This requires businesses and the government to react to new trends quickly; the best defense against fraud is to be aware of the techniques, remain on guard and educate consumers to do the same. All the while, businesses and governments must walk a tightrope between restricting freedoms too much and being purely reactive to crime.
The public and private sectors utilize call centers for customer account issues and require telephonic calls for some account actions. Unfortunately, these call centers are very susceptible to fraud. The time customer service reps spend trying to distinguish between fraud and noise (i.e., the legitimate calls that get flagged as fraud) distracts from more critical business and carries high costs.
For example, in the financial services industry, the cost of fraud to businesses is $4 for every $1 of actual fraud. That means, on average, if a person defrauds $1,000 from a company, that business’s related costs will be $4,000. And this figure doesn’t include additional costs incurred if a fraudster secures enough information on their first attempt to follow up with more attempts on the same business or its clients, nor the cost of reputational damage post-attack.
One of the big problems, though, is that fraud and noise can often seem similar. For instance, imagine you broke your cell phone and got a new one. When you try to access your bank account from your new phone, your account gets flagged because it doesn’t recognize the device. Now, you have to call to unlock your account, and your bank needs to spend resources confirming your identity. This protects the consumer and the bank but introduces inefficiency for both parties.
Related: How to Identity Proof in an Increasingly Virtualized World
So, what’s an agency to do?
Is there a solution? Modern identity proofing continues to progress in leaps and bounds. The technology exists now to implement much better identity proofing that’s device-agnostic and uses powerful, behind-the-scenes algorithms to prove a customer’s identity — often without them even realizing what’s going on. Artificial intelligence (AI) helps us use data points across the web to calculate the risk associated with a person or caller and create a dynamic risk profile. Then, based on their risk level, they may be required to complete additional automated steps to log in to their account or conduct business.
There are more straightforward steps, as well. For example, impersonating the dead has long been a lucrative tactic for fraudsters. Years ago, criminals even got hold of the Social Security Administration’s (SSA) Death Master File, a restricted record with millions of people to impersonate. One of the first steps a company can take during the account creation process is to check the Death Master File. Every time a person initiates a request for money with an agency, a quick screening can be done to ensure the person requesting a payment from the government is not a dead person. That would be a sure sign something’s amiss.
Of course, there’s no end to the trickery. Recently, I watched in real-time as a phone-based scam targeted my stepmother. She received a text that appeared to be from a friend saying her email had been the target of a scam, and my stepmom should call a particular number to make sure hers hadn’t also been compromised. I had to explain that it wasn’t her friend texting but someone using her friend’s number.
Older people are especially susceptible to fraud like this, but scammers have discovered impersonating a government agency or some entity with authority is a winner. If we get a call saying we’re in trouble with a government entity, will we ignore it? Probably not — many of us will do exactly what they say.
Related: How Technology Can Improve CX for Government Services
A continuous process
We aren’t going to be able to screen out fraud completely. But we can get better at thwarting it, saving operational dollars and resources and providing good customer experiences. The greatest vulnerability in any system is usually the humans using it, so implementing more automated identity-proofing and anti-scam tools can help bridge the gap. We can build efficiency into our systems by keeping up with the latest scam trends and implementing adequate technical controls to stop them.
Scott Straub
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