Author(s)

Chenyu Zhang

Corresponding Author

Chenyu Zhang

Abstract

In the context of climate change, the impact of extreme weather events on the insurance industry has become increasingly significant, causing economic losses of more than one trillion US dollars, seriously threatening the sound operation of insurance companies. In order to optimize the risk management strategy of property insurance, this study focuses on the impact mechanism of extreme weather and constructs a multi-dimensional analysis model system, including an underwriting multi-factor assessment model, a community building protection assessment model, and a disaster resistance comprehensive decision-making model. By analyzing the spatiotemporal distribution characteristics and intensity evolution of extreme weather, combined with the dynamic underwriting behavior of insurance companies, we identified key risk areas. Model 1 uses actuarial analysis of catastrophe risk losses to quantify risk assessment; Model 2 generates community building protection priorities through hierarchical analysis and deep learning algorithms; Model 3 uses linear programming and scatter plot visualization technology to propose real estate development optimization strategies. Sensitivity analysis shows that the constructed model is about 15%-20% higher than the traditional model in terms of prediction accuracy and anti-interference ability. The community extreme weather risk notice formed in this study provides theoretical and practical tools for the insurance industry to cope with climate change, and has important reference value to promote urban resilience construction.

Keywords

Extreme Weather, Insurance Industry, Risk Assessment, Model Building