Study on the Adaptive Dynamic Risk Assessment Based on the Gray Prediction Model

This paper focuses on the dynamic risk threshold adjustment strategy based on grey prediction and the Analytic Hierarchy Process (AHP), presenting an effective risk management approach under complex and uncertain risk environments. The study considers data related to extreme weather events, natural disasters, and economic conditions from 1950 to 2021, collected from the United States, the United Kingdom, and Japan, to establish a global policy resilience risk indicator system. Weights for disaster-causing factors, disaster-pregnant factors, and disaster-carrying body factors were derived using the AHP method. The grey prediction model was employed to forecast insurance risk factors for the U.S. and the U.K. over the next seven years. The U.S. insurance risk factor is projected to continue rising, while the risk factor for the U.K. was found to be zero in 2021. Therefore, it is concluded that insurance companies should make dynamic underwriting decisions based on these risk factors, to better cope with the intensification of global climate change and the associated increase in underwriting risks.