Research On Risk Control And Optimization Of P2P Network Lending Companies

Since the emergence of P2P network lending in China,the rapid development of the industry has not only promoted the financing of SMEs,but also satisfied the investment needs of the market.At present,the growth rate of China's P2P network lending companies has stabilized,the volume of transactions has continued to increase,and the number of investors and borrowers has continued to increase.The status of the financial industry in China has also been continuously improved,but the corresponding risk issues are also more prominent.However,a series of factors make the domestic P2P network lending companies face severe challenges,such as the development is too rapid,the corresponding industry standards and legal supervision is not perfect,and risk control means are too few.Only by enhancing the company's awareness of its own risks and improving its risk control capabilities can it be possible to reduce risks and promote the healthy development of the industry,thus eliminating the occurrence of risks from the source.After reviewing the relevant literature on P2P cyber lending risk control,this paper believes that research can be conducted from the perspective of optimization of the company's internal risk control measures to ensure the normal operation of the company.This article selects Hangzhou A company as the object of the case analysis.The analysis was based on the analysis of the company's actual control process and effective data.It used the literature method,case method,and credit score card method,respectively from Hangzhou A company's different risk control points,to study and discuss,and put forward corresponding optimization suggestions.This paper suggests that Company A may choose third party credit reporting platform to increase borrower data sources,construct borrower's credit scoring system through data of project parties and credit information platform,and use its scoring system to classify borrowers with different risk levels.Then provide investors investment portfolios,and transfer risks with the asset securitization.Finally,a risk-control culture system of the whole company is built to take new risk control measures into the hearts of the employees.The innovation of this paper is to build a more complete optimization plan for the actual situation of Company A,covering most of the processes of Company A's business.The use of data boxing to calculate the WOE value and the Logistic model regression coefficient to build a customer credit scoring system is innovative,and provides a reference for risk management and control of P2P network lending companies with similar services.