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Recognizing Financial Distress Patterns Using a Neural Network Tool

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  • Pamela K. Coats
  • L. Franklin Fant

Abstract

This study builds neural networks (NNs) which estimate the future financial health of firms. A neural network is a relatively new mathematical approach for recognizing discriminating patterns in data. We use NNs here to identify financial data patterns which consistently distinguish generally healthy firms from distressed ones. The purpose is to detect early warning signals of distressful conditions in currently viable firms. Being able to form highly reliable early forecasts of the future health of firms is critical to bank lending officers, investors, market analysts, portfolio managers, insurers, and many others in the field of finance.

Suggested Citation

  • Pamela K. Coats & L. Franklin Fant, 1993. "Recognizing Financial Distress Patterns Using a Neural Network Tool," Financial Management, Financial Management Association, vol. 22(3), Fall.
    • Handle: RePEc:fma:fmanag:coats93
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