Tuesday 26th of September 2017

Cognitive computing’s smart new approach to regulation and money laundering PDF Print E-mail

Last year IBM acquired Promontory Financial Group. How does the partnership set the stage for new levels of AML performance? Alistair Rennieat of IBM and Promontory CEO-founder Gene Ludwig explain how.

BAI Banking Strategies

June 6, 2017

By Robert Stowe England

 

If regulation is by the book these days, it might as well be from the “Harry Potter” series: the lost volume where brave bankers defend the castle from fire-breathing dragons that grow stronger, fiercer and more adept by the day. Harry recites spells. The dragons spit back and recite Federal Reserve Board Regulation Z, 12 CFR Part 226. (That’s enough to scare even the Dark Lord Voldemort.)


That’s the challenge banks face with the ever-increasing crush of rules, including those that govern anti-money laundering (AML).  What’s worse: Even as the regs get more expensive to address, the bad guys get more sophisticated and learn new ways to launder without a trace.


Now: Imagine having your own Dumbledore  to wizard your way through the phalanx of regulatory and money laundering dragons. To that end, IBM’s Watson cognitive computing technology has enough firepower, if you will, to tackle regulatory challenges and cut compliance costs, all while outflanking the crooks.


But sometimes even a mighty wizard can use a hand. In November, IBM acquired Promontory Financial Group, a D.C.-based financial regulatory advisory firm. How does the partnership set the stage for new levels of AML performance? To learn more, BAI Banking Strategies talked with Alistair Rennie, general manager, solutions, analytics at IBM. Joining him was Promontory CEO-founder Gene Ludwig, who’s also a former Comptroller of the Currency.


BAI: How did this partnership come about?


Gene Ludwig: We understood the need for new cognitive technology tools because we’re so active in the risk and compliance area for banks. When a potential money laundering transaction takes place at a bank, an alert is generated. The bank uses human beings to review each alert to determine if it is potentially a real incident. If they determine it is, the bank files a report of suspicious activity to the government.


Banks use thousands of people to review alerts. However, on any given day—because one crook is especially devious or an expert reviewer at the bank is having a bad day—there will be human mistakes. Technology offers us the opportunity to put a floor under the level of mistakes it’s mechanical and can check all the alerts uniformly. That capability is very valuable.


Alistair Rennie: From IBM’s perspective, we do a tremendous amount of work with companies on a global basis and we look to the pressure points banks face to see where we might help. Not surprisingly, compliance came to the top of the list as a rapidly growing expense critical to the safety and operations of the financial institution itself.


Most approaches to handling those pressures added more and more people to handle the burden. But looking forward, that prospect was not financially sustainable. That’s when we realized cognitive computing could make a difference.

 

Read more at this link.

 

 

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