Recalibration and Application of Springate, Zmijewski and Grover Bankruptcy Models in Indian Banking Sector

Objectives: Banks’ failure is a significant concern to the economy as it creates high cost and heavy losses to the individual banks and society. To avoid the risk of bank failure, banks need to find reliable ways to predict bankruptcy. Certain bankruptcy models are not working in the current economic environment. Therefore, the objective of the present paper is to recalibrate and apply Springate, Zmijewski and Grover models to assess the Indian banks’ bankruptcy. Method the current study tries to recalibrate the said models by considering the fact of models criticism in past studies with respect to their predictive power, selection of variables, time factor, accuracy rate, change in the economic environment, etc. Models are recalibrated by changing coefficients of the original models using current data through multiple regression technique. Further, this study applies the recalibrated bankruptcy models such as Springate, Zmijewski and Grover to assess the banks’ bankruptcy. Results the result shows that the recalibrated Grover model outperforms the original model; however in case of Springate and Zmijewski model, original model performs better than the recalibrated model. Conclusion the implications of the study direct the Reserve Bank of India to make a policy of using advanced modes such as Multiple Discriminant Analysis technique, logit, Probit models along with the CAMEL model for the financial health assessment of banks.