An Artificial Intelligence Approach towards Investigating Corporate Bankruptcy

  •  Stefan Cristian Gherghina    


Corporate bankruptcy analysis is very important for investors, creditors, borrowing companies, as well as governments. The assessment of business failure provides tremendous information for governments, investors, shareholders, and the management based on which financial decisions are taken towards preventing potential losses. Likewise, by researching corporate downfall there could be gathered an early warning signal, together revealing the fields encountering problems. Moreover, nowadays the corporations are facing the senior staff retirement, thus being confronted by the loss of knowledge. Artificial intelligence (AI) seeks the promotion of systems related with human intelligence, comprising reasoning, learning, and problem solving. The most powerful applied field of AI is the area of expert systems (ES). However, the ES are applications that could reproduce the knowledge and experience of a human expert. This paper aims at designing and implementing an ES prototype towards corporate bankruptcy analysis. Therefore, we have considered a couple of production rules based on indebtedness ratios (e.g. General Indebtedness Ratio, Global Financial Autonomy Ratio, Financial Leverage Ratio), as well as solvency ratios (e.g. General Solvency Ratio, Patrimonial Solvency Ratio). For this purpose, Exsys Corvid® was used since it transforms expert knowledge into a structure that enables rendering of guidance and prescription to refine performance, capability, and efficiency, alongside lowering training and costly errors.

This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1918-7173
  • ISSN(Online): 1918-7181
  • Started: 2009
  • Frequency: quarterly

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