Research On The Causes And Countermeasures Of Non-performing Loans Of Small And Micro Enterprises

As my country’s inclusive finance practice entered the fast lane in 2018,as the practice of inclusive finance in China entered the fast lane in 2018 my country’s inclusive financial service system the service system of inclusive finance in China has been gradually improved.Since 2021,All commercial banks implement the decisions and arrangements of the Party Central Committee and the State Council,and implement the decisions and arrangements of the Party Central Committee and the State Council,all commercial banks adapted to changes in the economic situation,continuously increased financial support,promoted more capital flow to the field of inclusive finance,such as technology and manufacturing enterprises,and promoted the rapid growth of loans in the field of inclusive finance.The balance of loans in the field of inclusive finance.The loan balance of inclusive finance of 18 national commercial banks increased by more than 13% year-on-year,and the balance of loans in the field of inclusive finance.The loan balance of inclusive of 5 large state-owned commercial banks increased by more than 30% year-on-year.With the growth of the balance of inclusive finance loans of commercial banks,As the loan balance of inclusive finance of commercial banks increases the latest data from the fourth quarter of 2018 to the end of 2021 shows that the amount of non-performing loans of small and micro enterprises has generally shown an upward trend is on the rise year by year,which will inevitably affect bound to affect the stable and safe development of inclusive finance.In the face of the increased credit risk of inclusive finance business,how to effectively control the credit risk of commercial banks and maintain the safe,stable,high-quality and sustainable development of inclusive finance is an issue worth pondering.Based on domestic and foreign research,this paper select 10 characteristic factors such as the basic situation of the borrowing enterprise,the cooperation with the borrower,and the settlement information from the preloan and post-loan dimensions,and uses the card-side test to study the correlation of the independent variable to the dependent variable,and analyzes the importance of the factors and the cross-influence relationship between the factors through the classification of the decision tree.Finally,the logistic regression model is used to analyze the settlement data,analyze the data characteristics before the occurrence of non-performing loans,and provide effective prediction support for post-loan early warning.The empirical results show that in the pre-loan stage of bank loans,the factors such as the operating life,place of registration,and credit rating analyzed by the model will affect the probability of non-performing loan customers,which can be used as the key factors in the credit business access stage of commercial banks.In the post-loan process of the bank,the model results show that loan customers who work with enterprises for the first three years and whose mortgage ratio is less than 1 need to pay attention.Commercial banks should prevent credit risks in a timely manner by increasing the frequency of post-loan management and adjusting their strategies.At the same time,commercial banks must regularly conduct logistic regression analysis of loan customer settlement data,and enterprises with model output flags as non-performing loan customers should trigger early warning signals in a timely manner,and at the same time include them in the list of strengthened management for special attention.Through the analysis of the research results of the influencing factors of non-performing loans of commercial banks,it is beneficial for commercial banks to predict the customers of non-performing loans.Improve their asset quality,and reduce the level of non-performing loan ratios,thereby promoting the highquality and stable development of inclusive financial services.