The Research On The Credit Risk Management Of N Company's Network Loan

In recent years,the development of network credit loans in China is particularly rapid.Since the whole process of the network lending of all transactions on the network,The traditional risk control method can not be used to control the credit risk,Therefore,compared to the line loan,The credit risk faced by network loan is more prominent.In the traditional line of loans,college students due to their inherent lack of credit conditions,such as no collateral,there is no stable source of income,there is no guarantor and other reasons,it does not meet the conditions of the line loans.Therefore,after the emergence of network loans,just to meet the needs of a wide range of college students,but the lack of College Students' ability to repay the loan network also makes the credit risk is particularly prominent.The way of network loans and the object of college students,making the platform for college students to engage in network loans face higher credit risk than other credit institutions.Therefore,it is necessary to understand the factors that affect the performance of college students,and to reduce the risk of College Students' network loan business.Based on the data collected from college students based on the N network loan,credit risk management mode of College Students' network N lending company to conduct a comprehensive analysis,empirical analysis and logistic regression model was applied to the risk characteristics.College students as the network loan participants,their credit characteristics as a stable source of income,no mortgage property,it is difficult to use financial indicators of basic assets such as bonds rate to evaluate the students' credit,so this paper selected the academic level,the loan interest rate,credit rating and other 10 basic indicators to measure the credit risk characteristics,explanatory variables Logistic regression results through the significant inspection,model prediction accuracy.In this paper,the logistic regression model is used to measure the 10 basic indicators of college students.The results show that the evaluation of N college students' credit rating is the biggest correlation with the default rate of College Students.In order to reduce the rate of non-performing loans,it is necessary to establish a scientific and reasonable evaluation mechanism to assess the credit rating of college students,and then determine the amount of credit and credit for college students.In order to reduce the rate of non-performing loans,it is necessary to establish a scientific and reasonable evaluation mechanism to assess the credit rating of college students,and then determine the amount of credit and credit for college students.N needle network of university loan products is the empirical analysis of elite credit data sources,although the data is a P2P company's loan data,but the research methods and conclusions have universal applicability of the network of credit loans.Because of the characteristics of College Students' credit is universal,credit risk factors for college students is analyzed in this paper is suitable for the college students,therefore,the conclusion of this paper have general applicability for Internet lending platform,network lending platform can be used to strengthen risk management,credit risk prevention,ensure the safety of investors'funds.