Money Laundering Bulletin: Less is More – AI Tackles False Positives
Sifting false positives out of transaction monitoring alerts and due diligence hits is a consistent struggle for financial institutions. To help better solve these challenges, financial institutions are looking to adopt technology solutions – powered by artificial intelligence.
Sandra Leon, Vice President of Cognitive Computing at Exiger, spoke to Money Laundering Bulletin, explaining that false positives are “a constant drain on resources” and that they “may also cost a financial institution real business – as it may be too slow to review or unable to handle the onboarding process.”
Instead, financial institutions would be better served by investing in technology to help them “stop throwing bodies at the problem.”
DDIQ, Exiger’s AI-powered automated due diligence tool, helps address this challenge of false positives by deploying AI and natural language processing (NLP) to “decipher relevant information like a due diligence researcher and [it] can aggregate, understand and review more information faster than human AML officers, helping them focus on the real issues.”
This process can be enhanced by providing additional contextual information and closer integration to onboarding systems, which enable “filtering through the noise to find that specific ‘John Smith’ you’re researching. For example, providing the subject’s age, previous employers or places of residence can negate many false positives before they even arise.”