Research on insurance model based on different mathematical models and algorithms

This article presents a risk assessment and prediction model for specific areas using the ARIMA model, entropy weight method, and AGNES algorithm. The model assists insurers in determining coverage and adjusting premiums based on economic losses predicted by the ARIMA model. It also aids real estate companies in deciding whether to develop in certain areas. The ERM model considers human, weather, and geographical factors to assess risks and predict potential property damage caused by extreme weather. The AGNES algorithm clusters similar samples to identify regions with higher risks. This helps real estate companies make informed decisions about development projects. The entropy weight method is used to adjust insurance premiums by calculating changes in regional risk coefficients. Continuous monitoring and analysis of risk coefficients improve risk assessment accuracy and enable reasonable premium adjustments.