Exploring the Pricing Strategy of Insurance in China Based on the TOPSIS Method

  • Yangchen Sun Business School, Xian International Studies University, China
DOI: https://doi.org/10.30560/jems.v8n2p182
Keywords: property insurance, TOPSIS, Break-even analysis, sensitivity analysis

Abstract

This paper is based on the panel data of extreme weather in China from 2000 to 2023. Firstly, the TOPSIS method is adopted to determine the weights of various indicators affecting the underwriting of insurance companies and establish a risk assessment system. Secondly, the break-even method is used to formulate the premium pricing strategy, and sensitivity analysis is conducted to test the sensitivity of each indicator. Further analysis is carried out to determine when and where the insurance company's underwriting risk is the lowest and the return is the highest. Finally, from the perspective of developers, the model is optimized. Based on the exploration of the influencing factors of building disaster resistance, the disaster resistance coefficient of disaster-resistant buildings is considered to establish a community disaster resistance capacity system model. Developers can determine whether to develop based on the local disaster resistance capacity indicators and the disaster resistance coefficient of disaster-resistant buildings.

References

[1] Zhang, Y. (2012). A Review of Research on Climate Risk Insurance and Response Strategies. Journal of Insurance Vocational College, 26(5), 25-31.
[2] Yang, S. T., & Li, S. W. (2023). Research on the Impact of Climate Risk on Insurance Demand in China. Financial Review, 15(2), 91-117, 126.
[3] Yu, X. F., & Fu, D. (2004). An overview of multi-indicator comprehensive evaluation methods. Statistics and Decision Making, (11), 119-121.
[4] Ma, Z. Y., & Song, Y. J. (2023). Impact of climate change on financial stability: a theoretical explanation. Southern Finance, (3), 19-36.
Refinement of sensitivity analysis results
Published
2025-04-16
Issue
Vol 8 No 2 (2025)
Section
Articles
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