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This framework demonstrates how AI and ML enhance fraud detection in banking, suggesting new defenses against various threats.
Banking fraud is a persistent threat that undermines customer trust and financial system integrity. With the rise in digital banking and online transactions, traditional rule-based fraud detection systems are proving insufficient. This article explores how Artificial Intelligence (AI) and Machine Learning (ML) are transforming fraud prevention strategies in the banking sector. It proposes a strategic AI/ML fraud prevention framework, outlines the architecture of modern fraud detection systems, and provides real-world case studies demonstrating the efficacy of predictive analytics, anomaly detection, and real-time transaction monitoring. This new paradigm offers a scalable, intelligent, and adaptive defense against evolving fraud tactics.
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Amit Prakash Jha (2025) studied this question.
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