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Modelling Credit Risk for SMEs: Evidence from the U.S. Market

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  • Edward I. Altman
  • Gabriele Sabato

Abstract

Considering the fundamental role played by small and medium sized enterprises (SMEs) in the economy of many countries and the considerable attention placed on SMEs in the new Basel Capital Accord, we develop a distress prediction model specifically for the SME sector and to analyse its effectiveness compared to a generic corporate model. The behaviour of financial measures for SMEs is analysed and the most significant variables in predicting the entities’ credit worthiness are selected in order to construct a default prediction model. Using a logit regression technique on panel data of over 2,000 U.S. firms (with sales less than $65 million) over the period 1994–2002, we develop a one‐year default prediction model. This model has an out‐of‐sample prediction power which is almost 30 per cent higher than a generic corporate model. An associated objective is to observe our model's ability to lower bank capital requirements considering the new Basel Capital Accord's rules for SMEs.

Suggested Citation

  • Edward I. Altman & Gabriele Sabato, 2007. "Modelling Credit Risk for SMEs: Evidence from the U.S. Market," Abacus, Accounting Foundation, University of Sydney, vol. 43(3), pages 332-357, September.
  • Handle: RePEc:bla:abacus:v:43:y:2007:i:3:p:332-357
    DOI: 10.1111/j.1467-6281.2007.00234.x
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    1. Eisenbeis, Robert A, 1977. "Pitfalls in the Application of Discriminant Analysis in Business, Finance, and Economics," Journal of Finance, American Finance Association, vol. 32(3), pages 875-900, June.
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