Assessing Distress in S&P Private Banks in India: A Comparative Study of the Altman and Fuzzy Logic with Decision Tree Variable Analysis

Predicting bankruptcy at early stage is crucial. Early recognition of solvency issues allows firms to take preventative measures, potentially avoiding severe financial crises in the future. This study aims to evaluate the effectiveness of distress prediction models for S&P Private Banks over a period of 7 years from 2018–2024, with a focus on identifying and predicting financial distress in the context of the emerging banking sector. Recently, there has been a sustained focus on predicting corporate bankruptcy, prompting a comparison between the Altman Z-Score and Fuzzy Logic with decision treebased variable analysis. The research provides a robust framework for distress evaluation, revealing the predictive capabilities of each model and the adaptability of decision trees in identifying crucial financial ratios. These models provide early predictions, enabling investors to prevent potential losses before making investment decisions.