Use of financial ratios in predicting Indian corporate bankruptcy

Objectives: The objective of this work is to build a framework for assessing the bankruptcy risk for companies that is useful for banks and financial institutions to classify firms into a possible bankrupt or not-bankrupt category based on the information available in the financial statements. Predicting bankruptcy is a prominent area for research in accountancy and finance for at least a century. Corporate bankruptcy is critically influencing the economic growth of almost every country. Primarily, financial ratios are applied to the bankruptcy prediction models. However, it has been reported that financial ratios do not have the ability to predict bankruptcy in an absolute manner. Rather, the quality of information inherent in the financial ratios is necessary for accurate bankruptcy prediction. A reduced set of financial ratios that could provide a more accurate prediction has been identified from the hypothesis that the utility of accounting information is a function of the predictive power and availability of information.

Data/Methods: This study applied a linear model, generalized linear model (GLM), and a non-linear approach viz., multivariate adaptive regression spline (MARS) to capture non-linear relationships to enable achieving better bankruptcy prediction. Data for 438 not-bankrupt companies as well as for 41 companies that went bankruptcy in 2015 in India were collected from the Center for Monitoring the Indian Economy (CMIE) Prowess database to apply in the models.

Results/Expected Results: Comparing the performance of the models, it was found that the GLM model is a superior model. The study also analysed the variable importance and found that retained earnings to total assets, earnings before interest and taxes to total assets and market captitalisation to total liabilities are the three most important variables for bankruptcy prediction using the MARS model. Correct prediction of bankruptcy would help stakeholders of the companies to take preventive measures in advance and to diminish the adverse effects of bankruptcy.