Enhancing Life Insurance Risk Models with AI: Predictive Analytics, Data Integration, and Real-World Applications
Keywords:
Artificial Intelligence (AI), Life InsuranceAbstract
Actuarial science and statistical modeling direct risk pricing for life insurance. Artificial intelligence might help to considerably improve the accuracy and efficiency of life insurance risk models. Predictive analytics, data integration, and practical applications—AI might transform life insurance risk assessment. Coverage for Life: Artificial Intelligence and Predictive Analytics Models of life insurance risk rely on mortality assumptions and past data. Although useful, these models lack the flexibility and granularity required to specify dynamic and complex risk profiles. Artificial intelligence-driven predictive analytics might find in vast data sets from many sources weak patterns and linkages missed by more conventional approaches.
AI-based machine learning systems might improve risk assessments by using insurance, medical, lifestyle, and social media data. Machine learning models may predict lifespan and health outcomes by means of health patterns, drug adherence, and socioeconomic factors. Improved reflection of policyholder risk profiles in insurance pricing can assist to lower unfair selection and advance fairness.
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