Artificial Intelligence and Machine Learning for Fraud Detection in the U.S. Banking Industry: Regulatory Frameworks, Implementation, and Challenges

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AI and machine learning enhance real-time fraud detection, improving response to sophisticated cyber threats.
Implementation of AI/ML within strict regulatory frameworks is essential for compliance and risk management.
Data privacy concerns and algorithmic bias are significant challenges in deploying effective AI/ML systems in banking.
The study provides a framework to balance technological progress with legal and financial system soundness.

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Observational analysis demonstrates improved fraud detection through AI and ML in U.S. banking, highlighting regulatory challenges.

Amoako et al. (2025) studied this question.

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