Strategic Models for Enhancing Insurance Resilience in the Face of Climate-Induced Natural Disasters
DOI:
https://doi.org/10.54097/ps4eb067Keywords:
Property Insurance, SHAP Value Algorithm, Grey Prediction.Abstract
As global climate change increases the frequency and intensity of natural disasters, the insurance industry faces significant challenges in risk management and policy affordability. This research develops three models to fortify the resilience of the insurance sector against the intensifying threats posed by climate-induced natural disasters. The Disaster-Affected Model quantifies the immediate impacts of diverse weather extremes, enabling precise risk assessments. The Insurance Bankruptcy Factor Model forecasts the financial sustainability of insurers, factoring in the frequency and severity of these events. The Underwriting Risk Prediction Model utilizes region-specific data to predict underwriting risks accurately, allowing for tailored insurance strategies. Together, these models enhance risk management, optimize underwriting practices, and ensure the financial stability of the insurance industry in a changing climate landscape, thereby promoting the sector's long-term sustainability.
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