Author(s): Sayan Banerjee, Sarbjit Singh Oberoi
In this study, the authors have developed a bankruptcy prediction model by using machine learning techniques, namely logistic regression, random forest, and AdaBoost, and compare these models with those developed using deep learning techniques, namely the Artificial Neural Network. ANN results in the highest accuracy and the most favorable prediction model for bankruptcy. Data used in this study are collected from survived and failed private and public sector banks from India from 2001 to 2018. For bankruptcy prediction, the authors have used macroeconomic and market structure-related features. The feature selection technique ‘Relief algorithm’ is used to select useful features for the bankruptcy prediction model.