T This study aims to analyze the influence of environmental, social, and governance (esg) disclosure and bank financial performance (return on assets/roa) on market reaction (abnormal return) of banking stocks listed on the indonesia stock exchange (idx), with credit risk (non-performing loan/npl) as a moderating variable, and capital structure (debt to equity ratio/der) and bank size (size) as control variables. the research adopts a quantitative explanatory approach based on secondary data derived from annual reports, sustainability reports, and audited financial statements of 47 banks during the 2019–2024 period. the results of the analysis show that esg disclosure has a negative effect on abnormal returns, indicating that although esg practices may reflect a company\\\'s commitment to sustainability, investors tend to view them as additional costs that can reduce a company\\\'s profit margins, particularly in the banking sector. in contrast, roa shows a significantly positive effect, reflecting investors\\\' preference for profitability performance. furthermore, credit risk (npl) is proven to weaken the positive effect of roa on abnormal return, although it does not significantly moderate the relationship between esg and abnormal return.the research methodology involves purposive sampling, resulting in a total of 204 observations after outlier removal using boxplot analysis. data were processed using eviews 9 and spss 25. classical assumption tests (normality, heteroscedasticity, multicollinearity, and autocorrelation) were conducted to ensure the validity of the regression model. the f-test results indicate that the regression model is significant as a whole (p < 0.05), while the t-test confirms that both esg (p = 0.028) and roa (p = 0.008) have partial significance in influencing abnormal return. the coefficient of determination (r²) of 9% suggests that a small portion of abnormal return variability can be explained by the model variables.the study concludes that integrating financial and non-financial factors is essential in investment strategy and managerial decision-making. banks are advised to balance esg disclosure with effective credit risk management to better capture market attention. investors, meanwhile, should consider the interaction between profitability and risk when evaluating bank stocks. the main limitation of this study lies in the fragmented and non-standardized esg data. therefore, future research is encouraged to apply machine learning methods in esg measurement and broaden the sample scope to non-banking sectors to enhance generalizability of findings