From black box to bottom line: the role of AI disclosure in bank performance in Malaysia

PurposeThe study examines the role of AI disclosure in the Malaysian banking sector by investigating its effects on profitability and operational efficiency. Grounded in signalling and stakeholder theories, it considers how AI transparency relates to financial performance within an evolving banking environment.Design/methodology/approachUsing panel data from 32 Malaysian commercial banks over the period 2019 to 2023, the study applies the two-step GMM estimator and quantile regression to examine both the overall and distributional effects of AI disclosure.FindingsThe findings show that AI disclosure is positively linked with profitability, as shown in ROA and ROE, and negatively connected with CTI, indicating better cost efficiency. The quantile regression further shows that the cost-saving effects of AI disclosure are more visible among both efficient banks and banks facing higher cost pressures.Research limitations/implicationsThe study is based on quantitative analysis within a single-country context and does not include cross-market comparisons. Its five-year period may also limit the ability to observe the longer-term financial effects of AI disclosure.Practical implicationsThe findings suggest that banks should treat AI disclosure as a strategic practice that can strengthen investor confidence, improve cost efficiency, and build stakeholder trust. For policymakers, the results highlight the importance of developing a balanced regulatory framework that encourages innovation while preserving financial stability, transparency, and inclusiveness.Originality/valueThe study contributes to the literature by applying signalling and stakeholder theories to explain the financial implications of AI disclosure in banking. It also introduces a structured and measurable approach to measuring AI transparency, showing how disclosure may strengthen financial resilience, operational efficiency, and investor confidence in a developing economy setting.