Artificial intelligence disclosure and bank performance: evidence from deposit money banks in an emerging market

Purpose Artificial intelligence (AI) is increasingly central to digital capability and competitiveness, yet little is known about how AI disclosure shapes bank performance in emerging markets. In Nigeria, where no formal AI disclosure regulation exists, transparency around digital strategy helps reduce information asymmetry and signal innovation readiness. This study examines how AI disclosure affects the profitability and market valuation of deposit money banks. Design/methodology/approach The study analyses annual reports from 12 Nigerian DMBs between 2015 and 2024, producing 120 firm-year observations. A multidimensional AI Disclosure Index was developed using summative content analysis across strategy, operations, customer engagement, risk and compliance. Performance was measured with return on assets, return on equity and Tobin's Q, while Feasible generalized least squares and the system generalised method of moments addressed heterogeneity, autocorrelation and endogeneity. Findings The results indicate that strategic and operational disclosures have a positive impact on profitability and market valuation. Customer-orientated and compliance-related disclosures show weaker or negative effects, while risk disclosures reduce short-term profitability but improve market valuation by signalling transparency. Overall, AI disclosure enhances asset efficiency but creates transitional costs that weigh on equity returns. Research limitations/implications The study is limited by reliance on content-based disclosure measures, potential subjectivity in coding and a single-country sample that restricts generalisability. Future studies should incorporate sentiment-based analytics, broader disclosure sources and multi-country comparative datasets to enhance robustness. Practical implications Standardising AI disclosure using structured frameworks can strengthen transparency, enhance comparability across banks, improve regulatory oversight and build investor confidence, supporting more consistent, credible and accountable digital transformation in Nigeria's banking sector. Originality/value This study introduces a replicable AI Disclosure Index for Nigerian banks and, using dynamic panel estimators, provides new evidence that AI disclosure functions as a governance substitute and performance signal in underregulated African markets.

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Publication Details

Journal
African Journal of Economic and Management Studies
Published
2026-02-19
DOI
https://doi.org/10.1108/ajems-07-2025-0539
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial intelligence disclosure and bank performance: evidence from deposit money banks in an emerging market

Mohammed Umar, Ovbe Simon Akpadaka, Onyinyechi Precious Edeh, Dagwom Yohanna Dang et al.
African Journal of Economic and Management Studies
FinTech, Crowdfunding, Digital Finance
article

Artificial intelligence disclosure and bank performance: evidence from deposit money banks in an emerging market

Mohammed Umar, Ovbe Simon Akpadaka, Onyinyechi Precious Edeh, Dagwom Yohanna Dang, Wabla Dahiru Onoja
article en

Abstract

Purpose Artificial intelligence (AI) is increasingly central to digital capability and competitiveness, yet little is known about how AI disclosure shapes bank performance in emerging markets. In Nigeria, where no formal AI disclosure regulation exists, transparency around digital strategy helps reduce information asymmetry and signal innovation readiness. This study examines how AI disclosure affects the profitability and market valuation of deposit money banks. Design/methodology/approach The study analyses annual reports from 12 Nigerian DMBs between 2015 and 2024, producing 120 firm-year observations. A multidimensional AI Disclosure Index was developed using summative content analysis across strategy, operations, customer engagement, risk and compliance. Performance was measured with return on assets, return on equity and Tobin's Q, while Feasible generalized least squares and the system generalised method of moments addressed heterogeneity, autocorrelation and endogeneity. Findings The results indicate that strategic and operational disclosures have a positive impact on profitability and market valuation. Customer-orientated and compliance-related disclosures show weaker or negative effects, while risk disclosures reduce short-term profitability but improve market valuation by signalling transparency. Overall, AI disclosure enhances asset efficiency but creates transitional costs that weigh on equity returns. Research limitations/implications The study is limited by reliance on content-based disclosure measures, potential subjectivity in coding and a single-country sample that restricts generalisability. Future studies should incorporate sentiment-based analytics, broader disclosure sources and multi-country comparative datasets to enhance robustness. Practical implications Standardising AI disclosure using structured frameworks can strengthen transparency, enhance comparability across banks, improve regulatory oversight and build investor confidence, supporting more consistent, credible and accountable digital transformation in Nigeria's banking sector. Originality/value This study introduces a replicable AI Disclosure Index for Nigerian banks and, using dynamic panel estimators, provides new evidence that AI disclosure functions as a governance substitute and performance signal in underregulated African markets.

African Journal of Economic and Management Studies
University of Jos (NG), Institute for Financial Research (SE), College of Accounting (SI)
Industry, innovation and infrastructure
Openalex Percentile: Top 57%
FinTech, Crowdfunding, Digital Finance
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