Identifying and Predicting the Credit Risk of Small and Medium-Sized Enterprises in Sustainable Supply Chain Finance: Evidence from China

Abstract

COVID-19 has created a strong demand for supply chain finance (SCF) for small and medium-sized enterprises (SMEs). However, the rapid development of SCF leads to more complex credit risks. How to effectively discriminate and manage SMEs to reduce credit risk has become one of the most critical issues in SCF. In addition, sustainable SCF (SSCF) has received increasing attention, and credit risk management is important to achieve SSCF. Therefore, it is significant to identify the key factors influencing the credit risk of SMEs and construct a prediction model to promote SSCF. This study uses the lasso-logistic model to identify factors influencing the credit risk of SMEs and to predict the credit risk of SMEs. The empirical results show that (i) the key factors influencing SMEs’ credit risk include six variables—the matching degree of order data, ratio of contract enforcement, number of contract defaults, degree of business concentration, and number of administrative penalties; and (ii) the lasso-logistic model can identify the key factors influencing credit risk and have a better prediction performance. Moreover, transaction credit and reputation supervision significantly influence the credit risk of SMEs.

The Impact of the Scale of Third-Party Logistics Guaranteeing Firms on Bank Credit Willingness in Supply Chain Finance: An ERP Study

“…However, SMEs have few collaterals, lack effective “hard information,” and it is difficult to obtain “soft information” such as high corporate reputation. The characteristics of risk bundling and information sharing in supply chain finance can reduce the degree of information asymmetry between banks and SMEs and greatly reduce the risk and monitoring cost of commercial banks providing loan services for such enterprises ( Yang et al, 2021 ). However, in certain cases, banks still face the risk caused by SMEs, which reduce the willingness of banks to perform supply chain financing.…”

Selecting the Fintech Strategy for Supply Chain Finance: A Hybrid Decision Approach for Banks

“…, and each element of the i-th column could be normalized by dividing ∑ t D i . The normalized dimensional matrix T D N is shown in Equation (6).…”

“…Broadly speaking, the adoption of IT solutions to improve or strengthen financial services could be regarded as a Fintech strategy [4]. Until recently, various technologies, such as cloud computing, artificial intelligence, machine learning, and blockchain technique, have all been adopted by either technology (e.g., Amazon [5] and Alibaba [6]) or financial companies (e.g., JP Morgan [7]) in finance.…”

“…As mentioned earlier, SMEs are relatively vulnerable to securing loans. Not only because SMEs lack public financial information and high-quality guarantees but also hardto-audit transactions and longer account receivables [6]. However, they are indispensable to the competitiveness of a supply chain.…”

The Performance Evaluation of Logistics Enterprises in Online Supply Chain Finance Based on Analytic Hierarchy Process

“…At present, the logistics industry generally has problems such as backward management methods, weak funds, and low utilization of advanced technology [13][14][15]. In this context, the online SCF services of LE have added new business models, which are conducive to enhancing their competitiveness [16]. On the other hand, LE participating in SCF can have a good grasp of logistics, capital flow, and information flow, which can greatly increase their own attractiveness, thus prompting more enterprises to cooperate with them [17][18][19].…”