| Under the background of Internet technology developing fast,traditional consumer finance has been changing and innovating by using “Internet plus”.Internet consumer finance has born at the right moment,and it has covered the market of university students in short time.More and more university students start using Internet consumer finance in all aspects of life.Although Internet consumer finance is popular in the market of university students,the defaults of university students after using Internet consumer finance having rising.Because university students are easy to have impulsive consuming behavior and weak in personal financial management,and universities haven’t popularize finance knowledge among students,and information asymmetry occurs between Internet consumer finance institution and university students,and other reasons.So Internet consumer finance credit risk of university students has caused widespread public concern strongly.In order to find the way to reduce the credit risk of university students’ Internet consumer finance,the paper makes a survey on Xi’an university students and makes a statistical descriptive analysis on the survey results.The conclusion reveals that numbers of university students to use Internet consumer finance are increasing,and that using frequency is also increasing.However,Internet consumer finance institutions are bearing rather high risk in the business of university students’ consumer finance.In order to analyze factors that affect university students’ credit risk of Internet consumer finance,the paper uses Logistic model to assess the risk.The results show that,among all the factors that affect university students’ credit risk of Internet consumer finance,comprehension degree of Internet consumer finance,the frequency of use,monthly sum of consumption,age,education background,politics status,academic record,and return of library books are the factors that count most.Combining the description statistics results and empirical test results,the paper has proposed the following suggestions: first,to establish a credit risk monitoring system of university students faster;second,to strengthen finance knowledge reserve and credit education of university students;third,to set up a credit reference system of university students’ Internet consumer finance with the usage of big data;fourth,to promote personal ability of anticipating credit risk of university students. |