Using payments data, privacy-enhancing technologies, AI and enhanced cooperation for a behavioural-based analysis approach to detecting money laundering networks is more effective than the current rules-based approach, concludes new research from the BIS Innovation Hub.


According to the Financial Action Task Force, almost all large money laundering schemes are cross-border and involve different business sectors. Meanwhile, financial institutions often face limitations in detecting potential suspicious networks and transactions due to their reliance on fragmented data and systems.

Today's Headline in NewsHours
0:00 Intro
3:00 #Amazon fined $25 mn for violating children's privacy law
3:32 #Google leads $36 mn funding in California, B'luru-based startup Pixxel
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Can tech and collaboration combat money laundering ?.