DOI: 10.12688/f1000research.183836.1 ISSN: 2046-1402

Multi capital disclosure and sustainability performance in Bangladeshi financial institutions using Deep Machine Learning

Md Qamruzzaman
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Purpose This study empirically investigates the joint and independent effects of intellectual capital disclosure (ICD), human capital disclosure (HCD), and natural capital disclosure (NCD) on the sustainability performance (SUSP) of listed financial institutions in Bangladesh, a bank-centric, climate-vulnerable emerging economy. Design methodology approach Drawing from a composite theoretical framework based on the Resource-Based View, Signalling Theory and the Legitimacy/Stakeholder approaches, the study engages a balanced sample of 62 listed financial institutions, including 30 commercial banks, 22 non-bank financial institutions and 10 insurance companies, providing 1,178 firm-year observations over 2005-2023. Analysis is conducted through panel (firm- and year-fixed effects) regressions, dynamic system generalized method of moments (system-GMM) and a supplementary multi-layer perceptron deep learning model. Findings We find that ICD, HCD, and NCD have positive and substantive effects on SUSP (at the 1% significance level), with the impact of intellectual capital disclosure as the leading predictor, followed by human and natural capital disclosures. Relationships remain robust under winsorisation, lagged regressors, sub-sample data, pandemic-free data, and a non-linear deep-learning framework (out-of-sample R 2 = 0.932), thereby validating a substantive (but not nominal) disclosure act. Board independence is consistently positive, while green funding intensity demonstrates directionally positive but statistically subordinate effects, indicating that disclosure quality supersedes green-credit volume in shaping sustainability outcomes. Originality value The results contribute to the integrated reporting discourse by confirming the triadic disclosure construct and provide recommendations for policy-makers, banks and climate finance practitioners in institutionally constrained emerging-market settings.

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