Development of the best investment strategy for insurance companies based on ARIMA-SVM

Abstract

The purpose of this article is to develop the best investment strategy for insurance companies in the context of extreme weather, aiming to improve the profitability of insurance companies and reduce investment risks. This research focuses on Asia and North America, and constructs an ARIMA model to accurately predict the frequency of extreme weather in the next decade. At the same time, a comprehensive evaluation model was constructed by combining the entropy weight method to quantitatively evaluate the payment ability of local residents. On this basis, the SVM classification model was established to predict whether the insurance company should be insured in a certain place, and the performance of the model was deeply analyzed, and the recall rate and accuracy of the classification model were 0.93 and 0.94, respectively, indicating that the model had good reliability. After a series of rigorous model analysis and data validation, it was finally concluded that China in Asia is the best choice for insurance companies. This strategy not only helps insurers optimize resource allocation, but also achieves stable and sustainable development in the context of complex and volatile extreme weather.