Predicting Non-performing Loans by Financial Ratios for Small and Medium Entities in Lebanon

Abstract

This study examines the ability of financial ratios in predicting the financial state of small and medium entities (SME) in Lebanon. This financial state can be either one of well-performing loans or one of non-performing loans. An empirical study is conducted using a data analysis of the financial statements of 222 SMEs in Lebanon for the years 2011 and 2012, of which 187 have currently well-performing loans and 35 have currently non-performing loans. Altman Z-scores are calculated, independent samples t-tests are performed, and models are developed using the binary logistic regression. Empirical evidence shows that the Altman Z-scores are able to predict well the solvent state of SMEs having well-performing loans, but are unable to predict accurately the bankruptcy state of the SMEs having non-performing loans. The independent samples t-tests revealed that five financial ratios are statistically significantly different between SMEs having well-performing loans and those having non-performing loans. Finally, a logistic regression model is developed for each year under study with limited success. In all cases accuracy results are inferred showing the percentage of companies that are accurately classified for being solvent and bankrupt, in addition to the two standard measures of error: the Type I errors and the Type II errors. Although a high accuracy is achieved in correctly classifying non-distressed and distressed firms, the Type I errors are in general relatively large. By contrast the Type II errors are in general relatively low.