Research on Extreme Weather Risk Assessment and Underwriting Decision Based on PCA-AHP Algorithm and ARIMA Modeling

Meijia Guo; Shurui Zhao

doi:10.54097/455nfdzh

Authors

Meijia Guo
Shurui Zhao

DOI:

https://doi.org/10.54097/455nfdzh

Keywords:

ARIMA, PCA-AHP Algorithm, Nonlinear Programming

Abstract

In this study, the disaster frequency prediction model and underwriting risk assessment model based on ARIMA are established by combining principal component analysis-hierarchical analysis method in China and the United States. Considering the personal factors of owners, the weights of subjective factors are incorporated into the risk assessment index system. A pricing model is developed through nonlinear optimal programming to help insurance companies decide underwriting strategies under extreme weather conditions. This study provides insurance companies with an effective decision-making tool to develop appropriate insurance policies in high-risk areas and to achieve a balance between benefits and costs in order to enhance their ability to cope with the challenges posed by extreme weather events.

References

Gasper R, Blohm A, Ruth M. Social and economic impacts of climate change on the urban environment[J]. Current opinion in environmental sustainability, 2011, 3(3): 150-157.

Mohamed J. Time series modeling and forecasting of Somaliland consumer price index: a comparison of ARIMA and regression with ARIMA errors[J]. American Journal of Theoretical and Applied Statistics, 2020, 9(4): 143-53.

Xue D, Hua Z. ARIMA based time series forecasting model[J]. Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering), 2016, 9(2): 93-98.

Khameneh A H, Taheri A, Ershadi M. Offering a framework for evaluating the performance of project risk management system[J]. Procedia-Social and Behavioral Sciences, 2016, 226: 82-90.

Zhao B, Liu Q, Zhu J. Risk Assessment and Zonation of Roof Water Inrush Based on the Analytic Hierarchy Process, Principle Component Analysis, and Improved Game Theory (AHP–PCA–IGT) Method[J]. Sustainability, 2023, 15(14): 11375.

Pantelous A A, Passalidou E. Optimal strategies for a non-linear premium-reserve model in a competitive insurance market[J]. Annals of Actuarial Science, 2017, 11(1): 1-19.