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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
