Game And Econometric Analysis On Peer-to-peer Lending

As a new way of lending,P2 P lending taking its advantage of flexible,fast online lending mode makes more and more attention from individuals and small and medium-sized enterprise investment and financing.However,due to the amount of P2 P lending platforms increased explosively and its asymmetric information of online trading,there are many serious problems in P2 P lending industry.As the publishing of Interim Measures for the Administration of the Business Activities of Internet Lending,P2 P lending industry regulation has institutional basis.And in order to adapt to the new regulatory environment for platforms,the Interim Measures also provides a rectification period of twelve months.In this context,the study of network lending credit problems and platform management undoubtedly has important theoretical and practical significance.First of all,we analyzed the credit risk of the network lending and pointed out that credit risk from the adverse selection and moral hazard.Then we established a game model between platforms and regulators.Also,we made an empirical analysis of the factors that affect the success rate of network.For these research questions,innovations and conclusions are mainly embodied in the following three aspects:Firstly,we set up signaling game model before borrowing and introduce principal-agent theory in loan.The results showed that credit ratings can be an effective signal transmission for high quality and lower-quality borrowers are distinguished.High quality borrowers in order to apart themselves from lower-quality borrowers,they must pay additional cost on credit rating increasing.And using variable borrowing rate amortization method can reduce default rate of the borrowers.Secondly,we set up an Evolutionary Game Mode to analyze the interaction between regulatory authorities and P2 P lending enterprises and draw the evolutionary game dynamics on both sides.After the analysis,we found that there is no evolutionary stable strategy equilibrium.According to each other's behavior regulators and the platform would constantly adjust their strategies.It is also found that the probability of borrowing targets can enhance the audit platform by increasing penalties,reducing the cost of the audit information platform and reduce the additional revenue audit platform.Thirdly,the empirical analysis of the factors affecting the success rate of the network lending based on the Logistic model.Based on PPdai platform historical transaction data as the sample data,we made Logistic regression and found that gender,identity,borrowing credit,amount of loan,life of loan has a significant influence on the probability of borrowing success.And it is suggested that the platform should pay attention to the integrity of the identity information and credit record.Finally,we put forward the corresponding countermeasures and suggestions to improve the management of the platform itself and the landing of the regulatory measures.