Property Insurance Model in Growing Extreme Weather Events Summary

Abstract

In the context of global climate change and frequent natural disasters, the protection and insurance decisions for cultural heritage have become increasingly important. In this paper, we first assessed the conservation value of historic buildings, used the McKinsey Logic Tree Model to select four indicators of cultural, historical, economic, and community significance, and computed the weights of each indicator through Analytic Hierarchy Process (AHP), and Entropy weight method to provide a decision-making model for community leaders to determine whether a particular building should be conserved. Additionally, a decision-making model for insurance companies was constructed, to calculate the combined weights of the disaster risk indicators, applying K-means clustering to categorize the risks, and predicting the probability of an insurance company's insolvency through a multivariate linear regression equation to help determine the insurance decision and the amount to be underwritten. Further optimization of the model considered key variables such as the probability of insolvency, underwriting risk, and the number of potential insured, and the insurance model was adjusted and optimized to assess whether, where, and how to establish an insurance mechanism. Finally, the Asakusa Temple in Japan is used as a case study to analyze its conservation value and corresponding underwriting measures.