Abstract
The major objective of the study is to understand the practical compliance of the Indian banks to Business Responsibility and Sustainability Reporting (BRSR) of Securities Exchange Board of India (SEBI) and to observe the differences in the behaviour in the stock market by the banks following BRSR from those are not in the compliance of BRSR. The study has covered the period from the month of January 2022 to January 2026 and collected the daily closing prices of ten banks under Nifty Index. Of the ten banks, six were following the ESG commitments and four were conventional. The framework covers the metrics namely mean daily return, volatility, coefficient of variation, downside risk and cumulative return among the two groups and studies the pattern with machine learning techniques namely, Random Forest classifier, linear regression, and K-Means clustering. The findings reveal that the banks with ESG commitment are substantially more stable than its conventional peers with 26.6% less volatility and 22.3% less downside risk. But this also indicates a less profitability as cumulative return is 18% lower during the four-year period. The results of machine learning indicate the differences between the groups is definite in the risk profile as the observed pattern is steady across three different market regimes namely, rate-hike shock in the year 2022, recovery in 2023 and the domestic growth period of 2024-26.