The integration of Artificial Intelligence (AI) into regulatory compliance frameworks has transformed the financial services sector by enabling more adaptive, predictive, and proactive governance systems. This review examines the current landscape of AI-driven regulatory technologies (RegTech), emphasizing how machine learning, natural language processing, and anomaly detection algorithms are being leveraged to monitor compliance, assess risk, and prevent fraud in real-time. The paper explores the evolution of regulatory requirements, such as Basel III, GDPR, and AML directives, and evaluates how AI tools can streamline compliance reporting and enhance audit readiness. It also assesses the challenges of algorithmic accountability, regulatory uncertainty, data privacy, and explainability in deploying AI for compliance management. Case studies from leading financial institutions and fintech firms illustrate practical applications and emerging best practices. This study concludes by identifying strategic frameworks that integrate AI ethics, legal compliance, and real-time fraud analytics to support resilient and transparent financial ecosystems.
Essien et al. (Thu,) studied this question.
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