Credit Line Models for Supply Chain Enterprises with Channel Background and Soft Information

Abstract

Credit lines have been widely adopted by banks to grant credit to small and medium-sized enterprises (SMEs). However, there often exists a gap between the credit lines granted by banks and the actual funding needs of SMEs. In addition, existing credit line models treat each SME as a stand-alone entity instead of considering it within its supply chain system. But an SME’s supply chain relations have a significant impact on its credit-worthiness. To offer banks a holistic assessment, this paper first constructs a base credit line model for SMEs by considering their supply chain background. Next, by accounting for the unique advantage of soft information processing in a supply chain context, we put forward an extended credit line model for supply chain enterprises with soft information. The base and extended credit line models proposed in this paper aim to reduce information asymmetry between banks and SMEs via the core enterprise in the supply chain, thereby helping banks to secure a sustainable source of profit at a lower risk level and SMEs to obtain more credit to support their sustainable growth. A case study is furnished to illustrate how the proposed models can be applied in practice and an empirical analysis further verifies their validity.