7. Artificial Intelligence-Driven Effective Financial Transaction Monitoring

Financial transactions monitoring is one of the most voluminous aspect in financial crime monitoring for any financial institutions. There are millions of transactions that every financial institution executes. They need to ensure that the transactions that have been authorized are not facilitating any form of financial crime. The chapter provides overview of real-time transaction monitoring and the necessity of ensuring that the counterparty to the transaction is not a watchlisted entity. Another important aspect is monitoring the financial transactions in non-real-time basis through scenarios. Concept of scenario finetuning through thresholds is discussed. The chapter also delves into definition of dynamic segments which are behavioral as compared to demographics that can further help finetuning the thresholds as the thresholds can be adjusted based on the past behavior of the segment, rather than painting all members of a demography-based segment with the same color. Threshold finetuning through ATL and BTL testing is also discussed. Last portion of the chapter explains possible overlaps that exists across scenario. A mathematical approach to optimize the overlaps is also discussed.