Future state AML: Using advanced technology to reimagine transaction monitoring

Chris Phillips
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Chris Phillips: SVP, Director of AML Compliance, Valley National Bank, USA

Journal of Financial Compliance, 2024, vol. 7, issue 3, 256-267

Abstract: Anti-money laundering teams are increasingly looking to implement advanced technology, including machine learning and artificial intelligence, to help reduce workloads while ensuring compliance with applicable regulation. However, much of what is being implemented today sits on top of legacy systems and is aimed less at effectively detecting financial crime and more at reducing false positive alerts. This paper reimagines how AML compliance can implement advanced technology from the ground up to not only reduce the number of false positives, but to also provide more useful and timely information to law enforcement. All technology discussed in this paper is currently on the market or under development. The paper can be used as a starting point for AML teams to think about how they can implement advanced technology end to end in order to improve the transaction monitoring process and suspicious transaction filings.

Keywords: anti-money laundering; ma-chine learning; artificial intelligence; BSA; suspicious transaction filings (search for similar items in EconPapers)
JEL-codes: E5 G2 K2 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:aza:jfc000:y:2024:v:7:i:3:p:256-267

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