Insurance company underwriting model against extreme weather

Abstract

This paper provides a corresponding coping strategy for developing the insurance industry under extreme weather by establishing an insurance company underwriting model. An insurance model (ICU model) for assessing catastrophe risk is proposed based on the results of some international databases and disaster resilience studies. The ICP coefficient is obtained by multiplying the regional vulnerability index with the regional risk index, where our innovatively proposed ARIMA-LSTM coupling algorithm predicts the risk index. The inverse proportionality function of the ICU coefficient is constructed based on the fact that the risk of insurance companies is positively correlated with the regional risk (ICP coefficient) and negatively correlated with the regional purchasing power (CBP coefficient). The CBP coefficients were computed by K-means clustering, and the derived ICP coefficients were used to derive the ICU coefficients for each region. Finally, the coefficients were categorized into three intervals to give the insurance companys coverage model.