Research On Credit Risk Management And Evaluation Of Supply Chain Finance Empowered By Blockchain For SMEs

Small and medium-sized enterprises(SMEs)are an important part of China’s economy and an important force for economic growth and employment stability.However,the development of SMEs is still very slow,and most studies have concluded that the primary factor hindering the development of SMEs is the difficulty and cost of financing.The supply chain finance model has emerged to alleviate SMEs’ financing difficulties,but the diversity of participants and the complexity of the process make it more difficult to identify and assess the credit risk of SMEs,which seriously hinders their development.The introduction of emerging blockchain technology has brought innovative solutions to the painful problems faced by supply chain finance in credit risk management and evaluation.Therefore,this thesis establishes a logistic regression model to examine the impact of blockchain technology on the credit risk of supply chain finance of SMEs,and constructs a credit risk evaluation model for supply chain finance of SMEs using MLP neural network considering blockchain technology factors.The article takes GEM listed manufacturing companies with supply chain finance business as the research sample and selects a series of credit risk influencing factors indicators from five dimensions: SMEs’ own condition,core enterprise condition,asset condition under financing,supply chain stability and blockchain utility.The nine common factors with eigenvalues greater than one were extracted through factor analysis,namely SME debt service factor,core enterprise debt service factor,core enterprise profitability factor,SME profitability factor,SME growth factor,SME credit factor,supply chain finance factor,SME operation factor and blockchain utility factor.Based on the extracted public factors,a logistic regression model was constructed,and the regression results showed that the blockchain utility factor was significantly negatively correlated with the probability of default,which means the use of blockchain technology can significantly reduce the credit risk of SMEs in supply chain finance,confirming that blockchain technology can empower the credit sharing in the supply chain finance chain,thus reducing its credit risk.On this basis,this thesis considers the influence of blockchain technology factors and uses MLP neural network to build a credit risk assessment model to predict the credit risk of SME supply chain finance and conducts a case study.The results show that the blockchain utility factor is a key indicator for evaluating their credit risk,and that the probability of SME credit risk is significantly reduced after considering the influence of the blockchain technology factor.