Abstract
This article develops two models for predicting the default of Russian Small and Medium-sized Enterprises (SMEs). The most general questions that the article attempts to answer are ‘Can the default risk of Russian SMEs be assessed with a statistical model?’ and ‘Would it sufficiently demonstrate high predictive accuracy?’ The article uses a relatively large data set of financial statements and employs discriminant analysis as a statistical methodology. Default is defined as legal bankruptcy. The basic model contains only financial ratios; it is extended by adding size and age variables. Liquidity and profitability turned out to be the key factors in predicting default. The resulting models have high predictive accuracy and have the potential to be of practical use in Russian SME lending.
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1recently completed her PhD in Small Business Finance at the University of Cambridge. Her research interests include credit scoring and other modern lending technologies, entrepreneurship, institutional theory and emerging markets.
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Lugovskaya, L. Predicting default of Russian SMEs on the basis of financial and non-financial variables. J Financ Serv Mark 14, 301–313 (2010). https://doi.org/10.1057/fsm.2009.28
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DOI: https://doi.org/10.1057/fsm.2009.28