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There is an increasing AI use in insurance—50% in non-life, 24% in life. To address emerging risks, undertakings must clarify supervisory responsibilities, maintain full accountability, and implement proportionate governance. Risk managers should conduct impact-based assessments, emphasizing data sensitivity, consumer impact, and financial exposure. Strong governance includes fairness, data quality, transparency, cybersecurity, and human oversight. Oversight extends to third-party providers, with contractual safeguards required. AI systems must align with existing frameworks like ERM and POG, ensuring traceability, explainability, and resilience throughout their lifecycle. Supervisory convergence across the sector remains a key regulatory goal.

Generative AI (GAI) is transforming banking risk management, improving fraud detection by 37%, credit risk accuracy by 28%, and regulatory compliance efficiency by 42%. GAI enhances stress testing but faces challenges in privacy, explainability, and skills gaps. Its adoption, led by larger banks, demands holistic strategies for equitable industry impact.

The paper analyzes the EU's Artificial Intelligence Act and its impact on AI regulation in banking and finance. It highlights the Act's potential to enhance governance, address high-risk applications, and the need for better coordination among regulators. Findings suggest challenges remain, including the necessity for adaptive frameworks to ensure ethical AI deployment.