Regulatory Screening: False Positives and Their Customer Experience Impact

False positives in AML and sanctions screening cause headaches for bank customers, and banks can take simple steps to fix it.

Often when banks talk about the impact of false positives in their AML and sanctions screening programs, they talk about the bottom line. That bottom line is this: banks lose money with the manual work involved in dealing with false positives, but if they process transactions that they shouldn’t have, then they have to pay much more. Lost in this focus on the bottom line is how these false positives impact customers, their banking experiences and their lives.

A couple of months ago Stephen Law, a British university professor who lectures internationally on philosophy, illustrated the negative impact of his banks’ sanctions screening miscues on his bottom line in an open letter to the U.S. Office of Foreign Assets Control. Law had been unable to receive payments from the U.S., or even receive items mailed to him from the U.S., because there is a major Burmese drug dealer who goes by the alias of “Steven Law” on the U.S. sanctions list. Professor Law said that his bank told him that they couldn’t explain why his payments were blocked, and at one point had to switch accounts because so many were being blocked.

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This is obviously no way to treat customers, but banks are willing to lose a customer if it means avoiding big regulatory fine, says Micah Willibrand, global director risk at Accuity, a provider of compliance and screening solutions. “Everything now is a risk-based decision… if you’re looking at customers who are only opening a checking or savings account, banks don’t want those customers because they aren’t profitable. They don’t care about their customer experience because they’re not worth the risk,” he explains. “With customers who make them money, you don’t see this. You wouldn’t see this with a customer who is a millionaire. The relationship manager wouldn’t allow it.”

Most of the hits in sanction screening are false positives though, says Willibrand, and banks rarely make the effort to match up different data points to rule out many of their false positives. “There usually aren’t rules around using date of birth and geographic data. They’re just matching names, and that can create big problems for common names like ‘Muhammad,’” he observes.

Using geographic data would have solved Professor Law’s problems, as the Burmese Steven Law’s known activities and addresses are all in South Asia.

Banks should also go the extra mile to utilize other data sources like public records and also leverage the work their doing in cleaning and managing their own data, Willibrand advises. Many banks are working on breaking their data silos and matching up data across the organization. When someone gets hit with a false positive, the bank needs to update their data not to suppress their next transaction, Willibrand notes.

The false positives problem is probably at its apex right now, Willibrand says. Banks have collected huge amounts of data on their customers to start building their digital strategies, and the more data they have, the more false positives they will get when screening for sanctioned entities or money laundering. “But those digital strategies that are being implemented will eventually improve false positive ratios for banks as they learn to better manage their data,” Willibrand comments. The sooner banks can get there, the better for any Steven or Stephen Law’s in the world.

Jonathan Camhi has been an associate editor with Bank Systems & Technology since 2012. He previously worked as a freelance journalist in New York City covering politics, health and immigration, and has a master's degree from the City University of New York's Graduate School ... View Full Bio