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| Research on Construction and Implementation of a Corporate Bankruptcy Prediction System Model |
| Tang Xiaobo1,2, Tan Mingliang1, Li Shixuan1, Zheng Du1 |
1.School of Information Management, Wuhan University, Wuhan 430072
2.Center for Studies of Information System of Wuhan University, Wuhan 430072 |
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Abstract As an important research topic in the field of finance and management science, corporate bankruptcy prediction plays a significant role in financial decision-making. This study proposes a corporate bankruptcy prediction system model from the perspective of knowledge engineering. The system constructs a bankruptcy prediction ontology by acquiring domain knowledge from domain experts and the literature, and it exploits sentiment analysis and knowledge discovery to mine interpretable rules for bankruptcy prediction from quantitative and qualitative information. Consequently, a corporate bankruptcy prediction ontological knowledge base can be constructed in a semi-automatic way. The system utilizes an inference engine to reason over the ontological knowledge base to predict corporate bankruptcy and interpret the prediction results. We validated the constructed system model by using the data of U.S. companies that had been listed as bankrupt in the past decade, and we implemented a corporate bankruptcy prediction prototype system. This system can not only improve the accuracy of predictions, but also support corporate stakeholders in predicting bankruptcy effectively.
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Received: 08 November 2018
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