Research On Financial Credit Risk Evaluation Of Agricultural Supply Chain Based On Logistic Model

Since the reform and opening up,agriculture as the foundation of the national economy,has achieved tremendous development in China and achieving a historic leap from eating too much to eating well.However,compared with the development of the secondary and tertiary industries,due to the long-term implementation of the agricultural back-feeding industry and the urban-rural "dual structure" policy system,agricultural development still lags behind the development of other industries.In addition,agriculture is greatly affected by natural disasters,which increases the risk of agricultural production and further leads to a serious shortage of investment in agriculture.This paper studies the financial credit risk of agricultural supply chain through the Logistic model.Select the financial data of the relevant agricultural listed companies of the three years from 2014 to 2016 and the agricultural supply chain financial operation indicators to analysis.Because not all of the above-mentioned agricultural listed companies' bad debts rate of receivables of the three years from 2014 to 2016 can be found.Some agricultural listed companies only have one or two years of the relevant data.Therefore,this paper finally forms unbalanced panel data with 91 sample.The number of samples has been expanded compared with previous studies.The binary logistic regression and principal component analysis are mainly used to accurately calculate the probability of compliance of cooperative customers in agricultural supply chain financial products.Different from the existing literature,ST is used to define whether the enterprise defaults.This paper uses Z value to define the default risk of agricultural supply chain financial listed companies.In terms of the company's default risk value,Z value has high accuracy value and also has advantages in accurate forecasting.The research on existing supply chain finance has been effectively supplemented and improved.This paper first introduces the literature review and theoretical basis of agricultural supply chain finance and selects representative indicators and introduces specific cases to conduct empirical research about agricultural supply chain finance.Finally,it concludes that compared to traditional financing models,in the agricultural supply chain financial financing environment,the compliance rate of related enterprises can be significantly improved,which helps to improve the credibility of agricultural enterprises and enable them to obtain more financing services from banks.The validity of the model is measured by the classification table.The results show that the accuracy of the model for high default and low default sample prediction is 84.2%and 95.8%respectively and the total prediction accurate rate of the regression model is 93.4%.Which indicates that the model has a better accuracy for predicting credit risk.This study helps to reduce the credit risk of bank loans and improve the operational efficiency of the entire agricultural supply chain finance.