An intelligent method for supply chain finance selection using supplier segmentation: A payment risk portfolio approach

Abstract

The COVID-19 pandemic-driven financial crisis grew significant interest among firms to adopt supply chain finance (SCF) to optimize working capital for the financial stability of the supply chain. However, it is impractical for firms with a diverse and extensive supplier base to strategize the SCF solutions for individual suppliers by assessing their financial risk. Hence, this study conceptualizes an intelligent method to demonstrate how supplier segmentation based on suppliers’ payment risk portfolios helps supply chain practitioners to assess suppliers’ financial risk and strategize manageable supply chain finance solutions for them. This method employs a stochastic optimization model to compute suppliers’ optimum payment risk portfolios and generate a supplier segmentation matrix to offer supply chain practitioners the cognitive ability to select appropriate SCF solutions for their suppliers. The proposed method can be implemented into an AI-driven explainable recommendation system to aid supply chain practitioners in applying smart strategic thinking in supply chain finance decision-making.

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