AI Disclosure, ESG Performance, and Tobin’s Q in Southeast Asian Banking

Hugo Prasetyo Winotoatmojo; Meiryani Meiryani; Bambang Leo Handoko; Antonius Ary Setyawan

doi:10.59261/inkubis.v8i4.494

Authors

Hugo Prasetyo Winotoatmojo Universitas Bina Nusantara
Meiryani Meiryani Universitas Bina Nusantara
Bambang Leo Handoko Universitas Bina Nusantara
Antonius Ary Setyawan Sekolah Tinggi Ilmu Komputer (STIK) Yos Sudarso

DOI:

https://doi.org/10.59261/inkubis.v8i4.494

Keywords:

Artificial Intelligence Disclosure, Banking, ESG Performance, Signaling Theory, Tobin's Q, Southeast Asia

Abstract

Background: Banks increasingly disclose AI-related activities, but disclosure does not establish actual implementation or realized outcomes. Evidence remains limited regarding whether AI disclosure is associated with ESG performance and whether ESG performance subsequently has valuation relevance in Southeast Asian banking.

Objective: This study examines the associations among AI disclosure, ESG performance, and Tobin’s Q.

Methods: A balanced panel of 1,230 bank-year observations covering 205 banking entities in 10 Southeast Asian countries from 2020 to 2025 was analyzed using bank and country-year fixed effects with bank-clustered standard errors. Robustness checks included lagged specifications, alternative variable definitions, ESG-pillar models, country exclusions, and cluster bootstrap analysis of the indirect association.

Results: AI disclosure was positively associated with contemporaneous ESG performance (β = 0.0139, p = 0.006; within R² = 0.007), with significant associations for social (β = 0.0181, p = 0.004) and governance (β = 0.0096, p = 0.018) performance. However, the disclosure–ESG association was not significant in lagged or one-year-ahead specifications. AI disclosure was not consistently associated with Tobin’s Q, and the bootstrap confidence interval for the indirect association included zero.

Conclusion: AI disclosure is associated with ESG performance only contemporaneously and does not provide consistent evidence of valuation relevance through ESG. The findings support a cautious interpretation of AI disclosure as a potential signal and underscore the need for verifiable, outcome-linked reporting.

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