Research on extreme weather insurance and real estate decision model based on AHP-EWM-CVM and K-Means clustering technology

Abstract

Aiming at the challenge of extreme weather to insurance industries and real estate industries, this paper constructs an insurance model and a real estate decision model. The insurance model uses analytic hierarchy Process (AHP), entropy weight method (EWM), coefficient of variation method (CVM) and K-Means clustering algorithm to evaluate the risk level in different regions and predict the values of risk indicators up to the year 2035, and then calculate future insurance premiums. At the same time, multiple constraints are used to determine the future risk safety interval, which provides the basis for insurance companies to make decisions. In the case application, this paper finds that China is currently medium risk region and will be a medium risk region in the future, and obtains the time point when insurance companies can underwrite policies in this region. In addition, this paper also constructs a real estate decision model, which comprehensively considers three factors: risk, development potential and risk cost, and provides decision making basis for real estate developers through GE matrix. In the case application, this paper predicts that in the next nearly ten years, China is a medium willingness and medium risk area, suggesting that real estate developers should be cautious in deciding whether to develop. This study provides decision support for insurance industries and real estate industries to deal with extreme weather, which is of theoretical and practical significance.