Integrating Generative AI and Large Language Models in Financial Sector Risk Management: Regulatory Frameworks and Practical Applications

The rapid advancement of artificial intelligence (AI) technologies, particularly generative AI and large language models (LLMs), has ushered in a new era of possibilities for the financial sector. This paper explores the integration of these cutting-edge technologies into financial sector risk management, examining both the potential applications and the necessary regulatory frameworks. We provide a comprehensive analysis of how generative AI and LLMs can revolutionize risk assessment, fraud detection, market analysis, and regulatory compliance. The study delves into the technical aspects of these AI models, their implementation challenges, and the implications for existing risk management practices. Furthermore, we propose a novel framework for the responsible adoption of AI in financial risk management, addressing concerns related to model interpretability, data privacy, and algorithmic bias. Our findings suggest that while generative AI and LLMs offer unprecedented opportunities for enhancing risk management capabilities, they also necessitate a recalibration of regulatory approaches to ensure financial stability and consumer protection. This research contributes to the growing body of literature on AI in finance and provides actionable insights for practitioners, policymakers, and researchers in the field.