This research analyzes how artificial intelligence helps life insurance companies evaluate risks while showing its strengths and weaknesses in underwriting work. Machine learning now handles life insurance underwriting tasks by processing medical and behavioral records, plus internet data to evaluate potential clients faster. Although AI helps underwriting become faster and more tailored, businesses still need to manage the problems AI creates with inequitable processes, unclear operations, and official oversight. This research analyzes existing AI underwriting applications and examines both their better performance and ethical problems. The system demands AI algorithms that viewers can understand plus fair models, plus good leadership structures to run AI systems safely. We share rules for both insurers and regulators to apply when they create new AI systems. Our analysis adds new information to research on ethical artificial intelligence and how it changes insurance risk handling systems.
Keywords: AI-driven life insurance underwriting, Algorithmic bias in underwriting models, Explainable AI in insurance, Regulatory compliance for AI underwriting., Risk assessment in insurance AI
