Predicting Distress in Indian Banks Using Discrete Time Hazard Model

Prior to the onset of Covid-19 pandemic, Indian banks had witnessed worsening asset quality, reduced capital level and declining profits. In this respect, we try to develop an early warning model to assess the riskiness of a bank well in advance in order to prevent the bank falling into financially distressed conditions in near future. Discrete time hazard model has been employed to predict the distress for each bank, with time horizon estimates set at four and six quarters. We found that declining profits, reduced capital level and worsening asset quality increases the likelihood of bank distress. Furthermore, lower credit growth in and around the asset quality review (AQR) period had also contributed towards distress. The empirical analysis suggests that early warning model seems to be robust and identifies the banks which were under Prompt Corrective Action (PCA) framework, as the distressed banks