Alon Kaufmann

Alon Kaufmann

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One of the prominent potential applications for federated machine learning is in detecting financial crime risks across multiple institutions which cannot share data with each other due to confidentiality and other regulatory restrictions. This article delves into the recent growth of financial crime in congruence with failing financial crime compliance and monitoring systems. The author describes how privacy enhancing technologies such as federated machine learning could help to overcome information sharing restrictions in relation to financial crime compliance and monitoring.