Bankruptcy Forecasting for Small and Medium-Sized Enterprises Using Cash Flow Data

  • Yong Xu
  • Gang KouEmail author
  • Yi Peng
  • Fawaz E. Alsaadi
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1179)


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.


Bankruptcy prediction SMEs Cash flow data 



This research has been partially supported by grants from the National Natural Science Foundation of China (#U1811462 and #71471149).


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.School of Business AdministrationSouthwestern University of Finance and EconomicsChengduChina
  2. 2.School of Management and EconomicsUniversity of Electronic Science and Technology of ChinaChengduChina
  3. 3.Department of Information Technology, Faculty of Computing and ITKing Abdulaziz UniversityJeddahSaudi Arabia

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