Regulatory Frameworks and AI-Powered Risk Assessment in Global Insurance Markets

Abstract

This paper focuses on the complex interdependence of regulatory regimes and risk assessment practices, using AI in the insurance industry across the world. Regulatory bodies face new mandates to promote transparency, fairness, and consumer protection as AI tools are increasingly integrated into risk modeling, underwriting, and fraud detection. The quantitative, descriptive-correlational research design that will be used in the research is based on the use of data on 100 respondents belonging to non-homogeneous age and experience groups. Statistical analyses indicate that despite the growing popularity of AI implementation, existing regulatory frameworks demonstrate significant gaps in terms of sufficiency and uniformity. The descriptive statistics show that there is a significant difference in the experience and gender participation of the respondents. The results  show that there is a low negative relationship between regulatory compliance and AI risk tools, and the regression outcomes suggest that the current frameworks have a low predictive power of providing effective customer protection. The results highlight the need to establish stronger, dynamic regulations that will be in line with the developing capabilities of AI and risk models in the insurance sector across the globe.