Research On Credit Risk Of Green Credit Assessment Based On Logistic Regression

Since the 21st century,the economies of all countries are improving,while people enjoy the fruits of increased wealth and technological progress,the contradiction between economic growth and environmental pollution has become increasingly severe.A series of ecological imbalances such as global warming,ocean pollution,and reduction of biological species have received widespread attention from all world,and sustainable development has become an inevitable trend.my country has always emphasized the construction of ecological civilization,and actively takes the world lead in vigorously advocating the development of green economy.At present,a green financial system has been initially established,in which green credit is an effective financial tool to optimize capital allocation,restrict the development of high-pollution enterprises and the major financial products that encourage the green economy.Commercial banks need to manage credit risk if they want to achieve steady profitability or expand their scale,while the credit risks of green credit are more complex due to its particularity.Therefore,the research on the credit risks of green credit is conductive to banks more accurate assessment credit risks,and improve prevention and control mechanism to make green credit business develop better.This article mainly starts from the perspective of credit risk assessment,based on existing research and chooses to conduct empirical research on credit risk of green credit assessment based on the Logistic regression model to identify and prevent credit risk of green credit for commercial banks provide new ideas.The main research content include:(1)At first,introduce green credit status of my country about policy support,product structure,scale development,and support for energy conservation and environmental protection industries.(2)Based on the traditional concept of credit risk,analyze the connotation,manifestation,characteristics and credit risk of green credit reasons.(3)Compare various credit risk assessment methods and analyze the applicability of the Logistic mode.Finally,selecting energy-saving and environmental protection enterprises as the research sample,choosing credit risk assessment from three aspects of financial factors,non-financial factors and environmental factors,and using the principal component factors extracted by principal component analysis to construct the Logistic regression model and testing its effect on predicting the credit risk of green credit.(4)According to the theoretical and empirical analysis results,in order to strengthen the prevention of credit risk of green credit and improve the development of green credit,relevant suggestions are made from the two levels of banks and the government.The main research conclusions include:(1)Analyzing my country's status of green credit development,it is found that the policy system is still in the preliminary stage of establishment,but the scale of development is relatively fast,among which there is a large degree of support for energy conservation and environmental protection industries.(2)Compared with traditional credit,the credit risk of green credit is more complicated,and the imperfect internal management mechanism and related policies of commercial banks are also the reasons for increasing the credit risk of green credit.(2)Through the empirical analysis of the credit risk assessment of green credit,it is found that the Logistic regression model can effectively determine whether energy-saving and environmental protection enterprises are in default,and the prediction accuracy rate is over 80%,which has certain practical guiding significance for green credit credit risk assessment.In addition,according to the remaining explanatory variables in the model equations,it is found that F1(profitability),F3(environmental responsibility status),and F4(development capacity)have a greater impact on credit risk than other factors.