The Research On Prevention Of Commercial Health Insurance Fraud Risk In China

In the past 30 years,Chinese commercial health insurance market has developed rapidly.However,with the rapid development of commercial health insurance,the risk of insurance fraud is also increasing.Insurance fraud will not only cause significant economic losses to the country,increase the operating costs of insurance companies,distort the insurance pricing mechanism,but also damage the contract foundation and the principle of integrity of the insurance industry.Therefore,based on the increasing risk of insurance fraud and great harm,it is of great significance to study the prevention of commercial health insurance fraud risk in China.This thesis first summarizes the current situation of commercial health insurance fraud risk in China,and analyses its causes and effects.Secondly,this thesis constructs a RBF neural network model embedded with logistic regression to quantify the fraud risk.Binary Logistic regression analysis was used to extract eight refined identification factors,which were used as input data to train the constructed RBF neural network,and test samples were selected to test the validity of the model.The results show that RBF neural network model embedded with logistic regression can effectively identify the fraud risk of health insurance,and the mean square error of the identification results is only 0.039304,Finally,this thesis combined with the quantitative analysis results of the commercial health insurance fraud risk,appropriate foreign health insurance fraud risk prevention experience of the market,on the basis of the following four perspectives:construction of law and credit system,construction of information platform,promoting cooperation and communication,and internal construction of insurance companies,put forward the countermeasures and suggestions to prevent the risk of commercial health insurance fraud in China.