Research On Anti Fraud Of Consumer Finance Based On Complex Network

In recent years,the balance of consumer credit loans in China has increased significantly.Consumer credit loans have penetrated into all aspects of life.Young people have a strong willingness to consume.Consumer finance is welcomed by young people because of its convenience.By the end of 2020,the asset scale of consumer finance companies had reached 524.649 billion yuan,exceeding 500 billion yuan for the first time.With the expansion of the industry scale,the fraud risk of consumer finance is also gradually accumulating,and the scale of fraud is also developing from personalization to collectivization.In particular,the black production gangs with the Internet as the carrier began to evolve from the traditional attack means of "attacking the system to steal information" to the mode of "using the loopholes in the risk control rules of financial institutions for mass arbitrage".Black industry gangs have the characteristics of advanced technology,large number,wide attack range and huge amount involved.If consumer finance companies do not conduct targeted research and prevention and control of black industry gangs,it will cause a lot of capital losses,affect the operation of enterprises and bring systematic financial risks.This paper mainly focuses on the scenario analysis and research on the fraud prevention and control of consumer finance,and puts forward the corresponding measures to prevent the risk of consumer finance fraud according to the characteristics and causes of fraud.According to the operating characteristics of consumer finance companies,the main measures focus on the design and optimization of anti fraud model.At present,most consumer finance companies still take the scorecard model as the main model basis of risk management.This paper mainly studies the design of the relevant model of machine learning and the model of complex network based on the existing scorecard model.Through the comparison of models,this paper puts forward the research direction of anti fraud model of "based on complex network,scorecard model combined with community mining algorithm to identify fraud".By introducing the successful application case of "complex network system of bank of hangzhou consumer finance company",this paper aims to illustrate that consumer finance institutions can effectively improve the anti fraud effect of consumer finance companies by expanding customer credit investigation data,third-party Internet behavior data and customer behavior variables to form a complete user portrait,and forming a complex network of user information through association.Finally,this paper looks forward to the anti fraud research of consumer finance based on complex network.On the basis of the further development of consumer finance industry,it can realize the industry data sharing,and apply more artificial intelligence algorithm models,which can further improve the ability of consumer finance industry to deal with the fraud of black industry gangs and realize the orderly and benign operation of consumer finance industry.