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Despite Successes, AML Professionals Still Wary of Artificial Intelligence

By Daniel Bethencourt

Fear of regulatory disapproval and data integrity concerns have kept some U.S. financial institutions from more fully incorporating machine learning and other artificial intelligence-based monitoring tools into their anti-money laundering programs, say sources. Machine-learning software in the AML space often uses "decision trees" and other easily auditable methods to process and review banking data. Other AI tools, such as "deep learning" and "neural networks," feature systems designed to notice transactional patterns and adjust their monitoring rules accordingly. Vendors promoting software based on artificial intelligence, which normally refers to any program that emulates human cognition, often promise bankers that the tool...

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