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Do ESG Disclosure Scores Enhance Bank Stability and Financial Performance? Evidence From Explainable Artificial Intelligence Models

ESG開示スコアは銀行の安定性と財務パフォーマンスを向上させるか？説明可能な人工知能モデルからの証拠 (AI 翻訳)

Buthiena Kharabsheh, Syed Mubarak Billah

Corporate Social Responsibility and Environmental Management📚 査読済 / ジャーナル2026-04-25#ESG
DOI: 10.1002/csr.70590
原典: https://doi.org/10.1002/csr.70590

🤖 gxceed AI 要約

日本語

本論文は、GCC地域の33行のパネルデータを用いて、ESG開示スコアが銀行の安定性と財務パフォーマンスに与える影響を調査した。一般化最小二乗法と機械学習モデルにより、ESGスコアの高さが銀行の安定性と収益性を向上させることを確認。説明可能AIによりESG開示が予測因子として有効であることを示した。サステナブルファイナンスの実務に示唆を与える。

English

This paper investigates the impact of ESG disclosure scores on bank stability and financial performance using panel data from 33 banks in the GCC region (2017-2024). Using generalized least squares and machine learning models, it finds that higher ESG scores lead to higher stability and performance. Explainable AI confirms ESG disclosure as a predictor. Findings have implications for sustainable finance practice.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本ではSSBJや有報でのESG開示が進んでおり、本論文の手法（特に説明可能AIを用いた開示スコアと業績の関連分析）は、国内銀行の開示戦略や投資家対応に示唆を与える。ただし、GCC地域のデータに基づくため、日本の規制・市場環境への適用には注意が必要。

In the global GX context

Globally, this paper contributes to the growing literature on ESG disclosure and financial stability, especially in emerging banking markets. The use of explainable AI offers a novel methodological approach that could be applied in other regions. Regulators and investors can leverage such models to assess the value-relevance of ESG disclosures.

👥 読者別の含意

🔬研究者:The use of explainable AI to link ESG disclosure to bank stability provides a methodological advancement that can be replicated in other contexts.

🏢実務担当者:Bank managers can use these findings to justify enhancing ESG disclosure as a strategy to improve both stability and financial performance.

🏛政策担当者:Policymakers in banking regulation can consider the positive impact of ESG disclosure on stability when designing disclosure requirements.

📄 Abstract（原文）

This paper investigates the impact of environmental, social, and governance (ESG) disclosure score on the stability and financial performance of banking firms within the Gulf Cooperation Council region. With the increased public awareness regarding ESG initiatives, banks are under pressure to show more disclosure and compliance. Our study employs annual panel data from 2017 to 2024, using 33 banks operating in Gulf Cooperation Council region. Bank stability is measured by Z ‐score and the standard deviation of return on assets, while bank financial performance is measured using the return on assets and the return on equity. The Generalized Least Squares random effects model shows that higher ESG score leads to higher bank stability and financial performance. Our results are confirmed using advanced machine learning models. The explainable artificial intelligence model provides evidence that ESG disclosure can predict both bank stability and financial performance. The findings of this study have important practical implications. We contribute to the literature on sustainable finance, providing insights to policymakers, bank managers, and investors seeking to deal with the dynamic challenges in the banking industry.

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