JT Bank Wenzhou Branch Personal Housing Loan Default Risk Identification And Prevention Research

Since the implementation of housing commercialization reform in China,the real estate industry has developed rapidly.At the same time,benefiting from the prosperity of the real estate market,the personal housing mortgage market has also developed by leaps and bounds.However,with the continuous growth of loan volume and scale and the complex and changeable economic situation at home and abroad,the risks brought by personal housing mortgage loans are becoming more and more prominent.Especially at present,when China is in the economic downturn cycle,the economy has entered the new normal,the macro-control policies are tightening,the real estate market tends to be rational,and the risk of personal housing loans is gradually exposed,it has become an urgent task to improve the bank’s ability to identify and manage the default risk of personal housing loans.In this regard,this paper takes the personal housing loan business of Wenzhou Branch of JT bank as the research object.Based on the analysis of the current situation of risk management,this paper uses the logistic measurement model to explore the factors affecting the default of personal housing mortgage loan and analyze the mechanism behind it,in order to improve the risk identification and control ability of personal housing loan of Wenzhou Branch of JT bank through research.The main research process and conclusions of this paper are as follows:(1)Through combing the operation data and management process of JT bank Wenzhou Branch,it is found that Wenzhou Branch’s personal housing loans account for76.1% of the total personal credit,which is beyond the reasonable range.At the same time,in terms of risk management,there are still many problems.(2)Select variables from the four dimensions of borrower characteristics,real estate characteristics,loan characteristics and regional characteristics to establish a logistic model for regression analysis of default behavior.The results show that: the borrower’s age,education,the borrower is a local,the repayment method of equal principal and house price index have a significant negative impact on the occurrence of default behavior;The default probability of borrowers working in national units is higher than that of ordinary enterprise employees,individual merchants or business owners and other occupations.(3)The prediction accuracy is obtained by logistic model.The results show that the overall prediction accuracy of the model is 94.7%,and the overall prediction accuracy is high,which can be used for risk identification and early warning.Among them,the class I error rate is 3.5%,and the class II error rate is 18.4%,which still has room for further improvement.(4)Based on the existing problems and the results of empirical regression,the corresponding risk prevention countermeasures are put forward,including: broadening the information acquisition channels,strengthening the information audit,building a scientific risk quantitative evaluation system,strengthening the construction of risk management professionals,implementing the post-loan work,and clarifying the post responsibility system.Among them,each point of the countermeasure contains the corresponding specific implementation measures.