Research On Risk Evaluation Of P2P Lending Platform

In June 2007,the first P2P lending platform called ppdai was formally established in Shanghai,which ushered in a new era of P2P lending industry in China.With this lending mode is gradually accepted by the general public,the number of P2P lending platforms in our country started the development by leaps and bounds.When people are enjoying the fast and convenient service of this new lending pattern,they also faces the problem of risk in the process of P2P lending development at the same time.Therefore,this paper focuses on the risk evaluation research of P2P lending platforms,aiming at the effective risk assessment and classification of them.On the one hand,this paper can obtain a scientific P2P lending platform risk rating index system,which is beneficial to the healthy and sustainable development of the P2P lending platforms.On the other hand,this paper can study the comprehensive risk of P2P lending platforms,and also contribute to the stability and economic development of China's Internet financial system.Firstly,this paper introduces the situation and development status of P2P lending platforms in China by using descriptive statistical analysis methods.Then this paper studies the various risks and comprehensive risk quantification of P2P lending platforms.And the P2P lending platforms risks in our country are divided into the operation risk,credit risk,operating liquidity risk,information technology risk,legal policy risk and market risk,a total of six risks,and get one of the most influential risk is operating liquidity risk.Then the construction of P2P lending platform risk rating index is obtained in this paper by using the canonical correlation analysis and factor analysis method.The index system obtained in this paper is made up of the qualitative and quantitative index,and 50 samples integrated scoring and sorting of risk is got in the factor analysis.In this paper,the risk level of P2P lending platforms is divided into AAA,AA and A.Based on this,this paper makes an empirical study on the judgment of risk level of P2P lending platforms by using random forest algorithm,and the overall misjudgment rate of the optimized random forest model based on OOB data is 15%.