Nowadays, the insurance industry is facing increasing challenges while the number of extreme weather phenomena is increasing. This paper provides support for the insurance industry by establishing models after quantifying the risks faced by property insurance companies and so on. This paper build a risk assessment model that focuses on extreme weather factors. Through SARIMA forecasts, the frequency of extreme weather is translated into economic quantifiers. Then visual data is used to determine the decision of whether or not an insurance company should underwrite one policy. Lastly, this paper provides recommendations for property owners to reduce their risk and upgrade their insurance. Then focus on property developers, further breaking out the limitations of extreme weather factors and expanding to socio-economic and GIS factors. First, this study uses the entropy weight method and PCA to assign weights to the insurance underwriting index system of different regions, and applies the data to SVM. Then the model is validated by taking the U.S. continents as an example. This question aims to better measure the factors in the companies’ decision-making process to establish property insurance, and to ensure the self-interest of property insurance companies while providing a reference for the construction of real estate.

Xinyi Chen, Boning Zou. Research and analysis of the insurance industry based on extreme weather. Academic Journal of Business & Management (2024) Vol. 6, Issue 9: 293-298. https://doi.org/10.25236/AJBM.2024.060940.

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