AI-Driven Regulatory Compliance in Finance: Automating Governance and Risk Controls
Abstract
The increasing complexity of financial regulations poses significant challenges for institutions striving to maintain compliance while ensuring operational efficiency. Artificial Intelligence (AI) offers transformative solutions by automating compliance monitoring, risk assessment, and reporting processes. This paper examines the role of machine learning, natural language processing, and rule-based AI systems in interpreting regulatory texts, detecting anomalies, and generating real-time compliance alerts. Case studies from banking and insurance demonstrate how AI reduces manual effort, minimizes compliance costs, and improves accuracy in risk management. The research also explores ethical considerations and regulatory concerns surrounding the use of opaque AI models in sensitive compliance functions. Findings indicate that AI not only enhances governance and transparency but also positions financial institutions to proactively adapt to evolving regulatory landscapes.
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