Predictions of Corporate Financial Distress of Loan Applicant Companies in Sri Lanka: with Special Reference to Altman’s z Score Model

Abstract

The quest of finding a simple and accurate bankruptcy prediction system or model is in high demand by Commercial Banks to detect the present and future financial health of companies. One of their main tasks is to reduce the Non - Performing Loan ratio as much as possible expeditiously. Many researchers depend on different kind of models to predict the financial distress, but Altman’s Z-score model is being used significantly all around the world in different kind of organizations, due to the level of accuracy and simplicity of calculations. The purpose of this research is to determine the accuracy and predictability of Altman’s Z”-score model for non-performing loans in Sri Lankan context. This Research examined 41 currently non-performing loans and performing loans granted for private limited companies by a Commercial Bank in Sri Lanka. The study identifies that the Altman’s Emerging Market Scoring model (Z’’) has the ability to predict non-performing loans accurately by 85.4% and 80.49% for the loan disbursement year and one year prior to the loan disbursement respectively. When comparing the Altman’s model results with the existing credit evaluation system of the selected bank, Altman’s model shows a better prediction accuracy. As a consequence of the high accuracy rate and simplicity, the respective bank can use the Altman’s Emerging Market Scoring model to predict the loan performance of the customers as a supporting tool to their main credit evaluation system.