The Research On The Impact Of Real Estate Enterprise Loans On The Credit Risk Of Commercial Banks

In recent years,the operation mode of high debt and high turnover of real estate development enterprises has been affected by the increasingly strict policy regulation of the state,so that the real estate industry has to face the pain of the transition period.Due to the financing restrictions under the "three red lines" and other policies,the difficulty of realizing land assets and other factors,the real estate industry is experiencing a new round of capital winter,and more and more real estate developers are facing the dilemma of difficult debt repayment.In the second half of2021,the debt default of several typical real estate enterprises such as Evergrande exacerbated the market’s concern about the real estate industry.Under the current financial market environment in China,the main financing way of real estate development enterprises is commercial bank loans.The loan quality of real estate enterprises has a great impact on the credit risk of commercial banks.Commercial banks need to pay high attention to the debt problem of real estate development enterprises and conduct more careful analysis and review of real estate enterprise loans.Based on the KMV model,this paper selects the relevant data of commercial banks from June 2011 to December 2020,combined with the previous practical experience,uses the KMV model to calculate the default distance of each sample bank,which is used as the measurement index of credit risk of commercial banks,and uses the panel data for regression on this basis,Analyze the impact of the proportion of real estate enterprise loans of various commercial banks on bank credit risk.The empirical study found that:(1)the credit risk of China’s major listed commercial banks is within a reasonable range for a long time,and the bank credit risk is positively proportional to the proportion of real estate enterprise loans.(2)The proportion of risk assets of commercial banks is mediated by the proportion of loans from real estate enterprises,which has an incomplete intermediary effect on bank credit risk.Finally,the paper mainly puts forward the following suggestions: commercial banks need to pay close attention to the changes of real estate development industry,strengthen the loan review and supervision mechanism of real estate enterprises,transfer the loan risk of real estate enterprises by means of innovative financial products,and reduce the credit risk level of real estate loans of commercial banks,And we need to pay attention to the cultivation of credit risk quantitative management talents.The innovations of this paper are as follows: firstly,in the process of empirical research,the proportion of weighted risk assets in total assets is taken as the intermediary variable of real estate enterprise loans affecting bank credit risk,and innovation is made in the selection of variables and the research of transmission mechanism;Moreover,when studying the relationship between real estate enterprise loans and bank credit risk,most of the previous relevant literatures focus on a single commercial bank in the form of cases,while the paper studies the whole group of listed banks;Finally,the paper takes the real estate enterprise loan and bank credit risk as the theme,uses the data from 2011 to 2020 for empirical research,and further improves the sample number and time span.The research deficiency of this paper is that KMV model can not be applied to non listed banks,but listed banks have larger asset scale,stronger risk management ability and relatively low credit risk,which may affect the conclusion to a certain extent.I believe that with the passage of time,more banks can be selected for followup research and more accurate results can be obtained.Secondly,because the financial data of commercial banks required for the research have not been fully published,it is difficult for the paper to divide the long-term and short-term loans of real estate enterprises of various banks and whether there are mortgages.Therefore,there is less discussion on the core explanatory variables.If the subsequent data disclosure can be more perfect,more detailed research can be carried out.