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Beaver, W.H., Mcnichols, M.F. and Rhie, J.W. (2005) Have Financial Statements Become Less Informative? Evidence from the Ability of Financial Ratios to Predict Bankruptcy. Review of Accounting Studies, 10, 93-122. https://doi.org/10.1007/s11142-004-6341-9

has been cited by the following article:

• TITLE: Machine Learning Methods of Bankruptcy Prediction Using Accounting Ratios

  AUTHORS: Yachao Li, Yufa Wang

  KEYWORDS: Bankruptcy Prediction, Statistical Method, Machine Learning, Accounting Ratios

  JOURNAL NAME: Open Journal of Business and Management, Vol.6 No.1, November 21, 2017

  ABSTRACT: The aim of bankruptcy prediction is to help the enterprise stakeholders to get the comprehensive information of the enterprise. Much bankruptcy prediction has relied on statistical models and got low prediction accuracy. However, with the advent of the AI (Artificial Intelligence), machine learning methods have been extensively used in many industries (e.g., medical, archaeological and so on). In this paper we compare the statistical method and machine learning method to predict bankruptcy with utilizing China listed companies. Firstly, we use statistical method to choose the most appropriate indicators. Different indicators may have different characteristics and not all indicators can be analyzed. After the data filtering, the indicators are more persuasive. Secondly, unlike previous research methods, we use the same sample set to conduct our experiment. The final result can prove the effectiveness of the machine learning method. Thirdly, the accuracy of our experiment is higher than existing studies with 95.9%.