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In this study, the disaster frequency prediction model and underwriting risk assessment model based on ARIMA are established by combining principal component analysis-hierarchical analysis method in China and the United States. Considering the personal factors of owners, the weights of subjective factors are incorporated into the risk assessment index system. A pricing model is developed through nonlinear optimal programming to help insurance companies decide underwriting strategies under extreme weather conditions. This study provides insurance companies with an effective decision-making tool to develop appropriate insurance policies in high-risk areas and to achieve a balance between benefits and costs in order to enhance their ability to cope with the challenges posed by extreme weather events.
Guo et al. (Fri,) studied this question.