A Comprehensive Workflow for Enhancing Business Bankruptcy Prediction

A Comprehensive Workflow for Enhancing Business Bankruptcy Prediction

Rui Sarmento (LIAAD-INESC TEC, Portugal), Luís Trigo (LIAAD-INESC TEC, Portugal) and Liliana Fonseca (University of Porto, Portugal)
Copyright: © 2015 |Pages: 23
DOI: 10.4018/978-1-4666-6477-7.ch011
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Abstract

Forecasting enterprise bankruptcy is a critical area for Business Intelligence. It is a major concern for investors and credit institutions on risk analysis. It may also enable the sustainability assessment of critical suppliers and clients, as well as competitors and the business environment. Data Mining may deliver a faster and more precise insight about this issue. Widespread software tools offer a broad spectrum of Artificial Intelligence algorithms and the most difficult task may be the decision of selecting that algorithm. Trying to find an answer for this decision in the relatively large amount of available literature in this area with so many options, advantages, and pitfalls may be as informative as distracting. In this chapter, the authors present an empirical study with a comprehensive Knowledge Discovery and Data Mining (KDD) workflow. The proposed classifier selection automation selects an algorithm that has better prediction performance than the most widely documented in the literature.
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Background

Empirical models to predict corporate bankruptcy and bankruptcy theories have been different strands of research. However, different paths have a substantial amount of overlap (Scott, 1981).

The literature in the field dates back to the 1930's with the analysis of single financial ratios for specific purposes and industry (Bellovary et al., 2007). With no advanced statistical methods, analysts only compared failed and non-failed companies and noticed that failed companies had worst ratio performances.

Beaver (1966) introduced a statistical perspective in univariate ratio analysis. From the 30 selected ratios, only six were significant:

  • Cash flow / total debt

  • Net income / total assets

  • (Current + long-term liabilities) / total assets

  • Working capital / total assets,

  • Current ratio

  • No-credit interval

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