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In the latest episode of Napier AI’s podcast series, Paysafe’s former MLRO and Napier AI’s data scientist delve into the integration of machine learning (ML) in combating financial crimes within the FinTech sector.
This insightful discussion not only connects trending FinTech topics with financial crime compliance but also equips financial institutions with crucial strategies to disrupt these activities.
The episode features Marcus Markland, Data Scientist at Napier AI, and Giacomo Austin, VP Strategic Initiatives at Paysafe, who discuss the pragmatic steps necessary for implementing machine learning in compliance teams. They explore both supervised and unsupervised ML models, providing practical examples of their use in detecting illegal transactions designed to mimic legal ones.
Financial crime compliance teams face immense challenges, particularly in the payments sector, which is under tight regulatory scrutiny. Advanced ML systems offer a beacon of hope by significantly enhancing decision-making and operational efficiency. However, the risk of biases in ML models and their potential consequences are also addressed, highlighting the need for careful implementation and continuous monitoring.
This discussion provides invaluable insights into the future of machine learning within payments organisations and the ongoing battle against financial crime. As these technologies evolve, so too does the landscape of regulatory compliance, making these insights essential for anyone involved in FinTech compliance.