Credit rating has long been a topic of interest in academic research. There are lots of studies about credit rating methods for large and listed companies. However, due to the lack of financial data and information asymmetry, developing credit ratings for small and medium-sized enterprises (SMEs) is difficult. To alleviate this problem, this paper adopts a novel approach, using SMEs' cash flow data to make bankruptcy predictions and improve the accuracy of bankruptcy prediction for SMEs through feature extraction of cash flow data. We validate the prediction performance after adding features extracted from cash flow data on six supervised learning algorithms. The results show that using cash flow data can improve the performance of bankruptcy prediction for SMEs.
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