Analysis of Insurance Anti-fraud Game Based on Random Forest and XGBoost Model

Abstract

With the rapid development of China's health insurance industry, cases of health insurance fraud are also on the rise year by year, which has had a negative impact on the development of the health insurance industry and social stability. This article analyzes the insurance anti fraud game based on the random forest and XGBoost model. The purpose of game analysis is to use game theory to analyze the occurrence process of health insurance fraud behavior, and then identify the main factors that affect moral hazard and insurance agency expenditure costs. And an insurance anti fraud game model was constructed in the article. Game theory can be used to analyze the process of health insurance fraud and identify the main factors that affect moral hazard. The most common type of health insurance fraud in China is doctor-patient collusion fraud. We will only discuss this type of fraud and not analyze other types. And through research, it has been shown that the XUBoost model has significant advantages in accuracy and recall, while the random forest has a higher accuracy. Obviously, the XUBoost model has good performance.