Maintaining both effective and efficient AML programs has proven elusive for financial institutions due to a reliance on legacy technology solutions and a seemingly ever-increasing investigator case workload. Artificial intelligence (AI) and machine learning, however, hold the key to helping institutions reduce regulatory risk, and improve the AML investigation process. This paper explains how transaction monitoring systems (TMS) can be enhanced with AI and machine learning to reduce risk and drive down AML costs.

Recent Posts

What’s Driving AML Compliance Transformation in 2022 and Beyond?

A new report by Aite-Novarica (Aite) examines what’s driving transformation in anti-money laundering (AML) compliance. Specifically, the impact report examines the current AML ecosystem, key trends impacting financial institutions (FIs) and their AML compliance functions, and how they invest in technology and innovation to tackle today’s ever-evolving risk landscape.

read more