Machine learning-based insurance risk assessment pipeline for natural disaster prediction and claims estimation

IntroductionThis study develops a machine learning-based framework for disaster risk assessment, economic loss estimation, and insurance claims prediction using multi-source environmental, socioeconomic, and temporal data. The aim is to improve predictive accuracy and decision-making in insurance and disaster management systems.MethodsA dataset of 68,485 disaster records (1953–2025) covering 10 disaster types and 49 engineered features was used. The methodology includes correlation analysis, syn