AI in payments fraud detection expands but needs strong regulatory oversight

The process will test the use of secure data collaboration, while the anomaly detection model will be able to identify potential fraud patterns in the data. Manish Kohli, head of global payments solutions at HSBC, says the bank has found several applicable uses for AI: "AI in predictive analyti...

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Bibliographic Details
Published in:The Banker 2024-10, p.40
Main Author: Long, Kimberley
Format: Article
Language:English
Subjects:
Artificial intelligence
Collaboration
Fraud prevention
Machine learning
Market planning
Payments
Predictive analytics
Regulation
Online Access:Get full text
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Summary:The process will test the use of secure data collaboration, while the anomaly detection model will be able to identify potential fraud patterns in the data. Manish Kohli, head of global payments solutions at HSBC, says the bank has found several applicable uses for AI: "AI in predictive analytics identifies future needs based on transaction signals, which can include predicting currency preferences in cross-border payments or anticipating client requirements based on historical behaviour." Federated machine learning, where multiple parties can train a model while keeping their proprietary data decentralised, is another system which will enable greater collaboration without comprising customer details or falling foul of rules on holding data domestically.
ISSN:0005-5395