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%.