The Impact Of AI On The Anti-Money Laundering Sector

Finance Monthly Magazine

Finance Monthly Magazine recently interviewed Salvatore LaScala, managing director and co-lead of the global investigations and compliance practice at Navigant to discuss anti-money laundering (AML) in the U.S. and the impact that artificial intelligence (AI), machine learning, and robotics process automation has in financial services.  

Q. What is the current state of AML in the U.S.?
Financial institutions are quickly adapting and upgrading their technology and overall programs to maintain compliance and prevent and detect money laundering, terrorist financing and fraud. The "bad guys," however, seem to have far more payment methods and venues at their disposal to commit crimes than ever before in history.

Q. What are the current AML issues and solutions affecting American businesses?
AML is constantly undergoing transformations. Some of these are based on new and emerging AML and fraud schemes that the industry has to respond to, other transformations are due to new regulations, such as NYSDFS Part 504 regulations, which add additional layers of accountability on AML program owners.

Q. How has the introduction of Artificial Intelligence, Machine Learning, and Robotics Process Automation impacted compliance and investigative solutions?
We believe that AI/ML can help existing AML Transaction Monitoring Systems deliver enhanced detection scenario parameters by grouping behavioral patterning to cover more risk and produce fewer false positives….That said, there is a fair amount of work to do. 

 

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The AI/ML revolution won't survive if the providers that developed it and the financial institutions that use it are not completely transparent.

Salvatore LaScala
Managing Director and Co-Lead of the Global Investigations and Compliance Practice

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