CREDIT RISK MEASUREMENT: The case study of Mongolian Small and Medium sized firms

Abstract

This thesis presents credit risk measurement approaches and some empirical results of predicting firm's failure by using various financial ratios. It aims to re-examine Altman's Z-score model and build a comparable method by logistic regression, a credit scoring model technique. The small and medium sized enterprises' empirical data used in the research work is provided from a Mongolian commercial bank. We analyzed forty two firms' financial statements, including bankrupted and non-bankrupted firms, for the period of 2007-2008. At first, financial ratios of selected sample have been analyzed through Altman's Z-score model. Overall, prediction accuracy of Altman Z-score model was significantly high, 71 percent. In terms of logistic regression method, we estimated fifteen financial ratios through the model and come to conclusion that two ratios, namely cash to total asset ratio and retained earning to total asset ratio, are significant predictor for firm's bankruptcy in Mongolian SMEs. If we compare the prediction power of the two methods, model derived from logistic regression is slightly lower than in Altman Z score model. Keywords: Credit Risk measurement, bankruptcy, Altman Z score, logistic regression