A Study on the Assessment of the Impact of Extreme Weather on the Insurance Industry and Response Strategies Based on SEIR Modeling

Abstract

This paper investigates the impact of extreme weather on the insurance industry and proposes a new model for assessing the value of insurance underwriting. The study first collected data on nine indicators from 50 regions, categorized these indicators into three categories: extreme weather, insurance, and region, and then used the hierarchical analysis method (AHP), entropy weighting method (EWM), and CRITIC method to calculate the composite weights to derive the Underwriting Value Index (UVI). In addition, underwriting values for St. Louis and Kingman were evaluated using the ALARP criteria and the EIR model. In order to help communities and real estate developers to carry out rational development, the EIR model was improved to form the SEIR model, which was applied to score the development value of nine municipalities in Fujian Province, which showed that Xiamen scored the highest and was recommended to be developed and built in Xiamen. The methodological validation of this study shows that there is a significant correlation between the UVI score and the insurance coverage gap (Pearson correlation coefficient R=0.869), which indicates that the model has good rationality and practicality.