The Impact of AI Tools on ESG-Based Sustainable Banking Practices: A Meta-Analysis & Conceptual Framework
Abstract
This study investigates the role of Artificial Intelligence (AI) tools in enhancing Environmental, Social, and Governance (ESG)-based sustainable banking practices. With increasing global emphasis on sustainable finance, banks are exploring AI technologies to improve ESG performance, risk management, and decision-making processes. Through a comprehensive metadata analysis of recent scholarly publications, this research identifies key trends, thematic focuses, and disciplinary contributions within the evolving landscape of AI-enabled ESG banking. Using a literature review guided by the SPAR 4 framework, the study analyzed 350 sources from 2015 to 2024, narrowing down to 70 key documents. Most research came from the United States (30%), the United Kingdom (25%), Germany (15%), and India (10%), with the remainder distributed across other countries. Additionally, the study proposes an integrated conceptual framework that elucidates the mechanisms through which AI supports ESG goals, addressing both opportunities and challenges such as data privacy, algorithmic bias, and regulatory compliance. Findings highlight the interdisciplinary nature of this domain, spanning finance, computer science, environmental science, and social sciences. The study concludes by outlining implications for financial institutions and regulators, as well as future research directions to validate and expand the conceptual model. This work contributes to bridging the knowledge gap between AI innovation and…
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