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How AI and Machine Learning Are Redefining Anti-Money Laundering

Published by SAS

AI and machine learning are redefining anti-money laundering (AML) by automating tasks, improving risk detection, and enhancing transaction monitoring. The technology allows financial institutions to detect suspicious activities more accurately by analyzing vast data sets and uncovering hidden patterns. Machine learning supports key AML functions, including anomaly detection, customer segmentation, and risk ranking, making it easier to identify and prioritize high-risk cases. While these technologies offer significant advantages, challenges such as data preparation, talent shortages, and the complexity of black-box models must be addressed for effective implementation.

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Related Categories Artificial Intelligence, Generative AI, Deep Learning, Computer Vision, Threat detection, Intrusion prevention, Security Analytics, Data encryption, Identity management, Risk Assessment, Cyber threat intelligence, Network security, Endpoint protection