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SUMMARY:Fighting AI-Powered Financial Crime in the Payments Ecosystem
DESCRIPTION:Financial crime has entered a new era.  \nFraudsters increasingly use automation\, generative AI\, synthetic identities\, mule networks\, and highly coordinated attack models that operate at a speed traditional controls were never designed to match. While many organisations continue to treat fraud prevention\, AML\, and mule account detection as separate disciplines\, criminals see them as a single end-to-end process.  \nThis webinar will explore how financial institutions and payment providers can shift from reactive compliance towards proactive\, intelligent prevention. Drawing on practical experience and emerging technology trends\, the session will examine how AI can help identify suspicious behaviour in real time\, connect hidden relationships across networks\, reduce false positives\, and improve operational effectiveness while maintaining governance and explainability.  \nParticipants will gain practical insights into how AI is reshaping both sides of the financial crime battlefield and what payment organisations must do to remain ahead.  \nKey takeaways: \n\nWhy fraud\, mule activity\, and money laundering should be addressed as a single risk chain. \n\n\nHow criminals are leveraging AI and automation. \n\n\nWhy traditional rule-based controls are becoming less effective. \n\n\nHow behavioural AI models strengthen fraud prevention. \n\n\nThe importance of adaptative models to quickly response to new attacks \n\n\nThe role of transaction flow analysis in identifying mule accounts. \n\n\nHow AI can improve AML monitoring and alert prioritisation. \n\n\nThe governance\, explainability and accountability required for trusted AI. \n\n\nPractical steps organisations can take to move towards real-time prevention. 
URL:https://thepaymentsassociation.org/event/fighting-ai-powered-financial-crime-in-the-payments-ecosystem/
CATEGORIES:Webinar
ATTACH;FMTTYPE=image/png:https://thepaymentsassociation.org/wp-content/uploads/2026/11/Lynx-webinar-Jan-27-listing-1.png
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