Author(s)

BinHao Guo, ShuJie Shi^*, GuoLiang Wen, XingPeng Zhuo

Affiliation(s)

School of Electronic Countermeasures, National University of Defense Technology, Hefei 230000, Anhui, China.

Corresponding Author

ShuJie Shi

ABSTRACT

With the increasing frequency of extreme weather events, dynamic risk assessment has emerged as a crucial research topic for the sustainable development of the insurance industry. To address the underwriting decision-making challenges faced by insurers in high-risk areas, this study develops a risk assessment model that integrates historical data to predict property loss ratios in such regions for the coming year. By considering the perspectives of both insurers and policyholders, we propose a utility value model that evaluates the utility values of risk-free and risk-exposed properties separately. This framework derives the conditions for insurance underwriting and identifies a reasonable range for premium rates, thereby determining the optimal underwriting strategy for insurers. Finally, the model is applied to two regions in China—Fujian and Guizhou—for validation. Simulation results demonstrate that the proposed model exhibits high predictive accuracy and sensitivity in risk assessment, confirming the feasibility of the proposed underwriting strategy.

KEYWORDS

Extreme weather; Insurance industry; Risk assessment; Grey time series prediction; Utility value

CITE THIS PAPER

BinHao Guo, ShuJie Shi, GuoLiang Wen, XingPeng Zhuo. Dynamic risk assessment in the insurance industry based on a high-risk underwriting decision model. World Journal of Economics and Business Research. 2025, 3(2): 43-49. DOI: https://doi.org/10.61784/wjebr3045.

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