Machine Learning Models for Life Insurance Risk Assessment: Techniques, Applications, and Case Studies
Keywords:
Machine Learning, Life Insurance, Risk AssessmentAbstract
Risk assessment is key to life insurance pricing and financial stability. Despite their popularity, standard actuarial methods struggle with massive data sets and complex variable connections. Advanced machine learning (ML) algorithms examine several data sources to predict mortality and morbidity. This article examines life insurance risk assessment ML models, their applications, and successful implementations using case studies.
Article starts with life insurance risk assessment principles. Mortality impacts premiums and policies. Risk assessment uses statistical and historical actuarial models. The models' pre-defined variables and lack of non-linear interactions are highlighted.
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