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AI in ESG for Financial Institutions: An Industrial Survey

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  • Jun Xu

Abstract

The burgeoning integration of Artificial Intelligence (AI) into Environmental, Social, and Governance (ESG) initiatives within the financial sector represents a paradigm shift towards more sus-tainable and equitable financial practices. This paper surveys the industrial landscape to delineate the necessity and impact of AI in bolstering ESG frameworks. With the advent of stringent regulatory requirements and heightened stakeholder awareness, financial institutions (FIs) are increasingly compelled to adopt ESG criteria. AI emerges as a pivotal tool in navigating the complex in-terplay of financial activities and sustainability goals. Our survey categorizes AI applications across three main pillars of ESG, illustrating how AI enhances analytical capabilities, risk assessment, customer engagement, reporting accuracy and more. Further, we delve into the critical con-siderations surrounding the use of data and the development of models, underscoring the importance of data quality, privacy, and model robustness. The paper also addresses the imperative of responsible and sustainable AI, emphasizing the ethical dimensions of AI deployment in ESG-related banking processes. Conclusively, our findings suggest that while AI offers transformative potential for ESG in banking, it also poses significant challenges that necessitate careful consideration. The final part of the paper synthesizes the survey's insights, proposing a forward-looking stance on the adoption of AI in ESG practices. We conclude with recommendations with a reference architecture for future research and development, advocating for a balanced approach that leverages AI's strengths while mitigating its risks within the ESG domain.

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  • Jun Xu, 2024. "AI in ESG for Financial Institutions: An Industrial Survey," Papers 2403.05541, arXiv.org.
  • Handle: RePEc:arx:papers:2403.05541
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    1. Caroline D. Ditlev-Simonsen, 2022. "A Guide to Sustainable Corporate Responsibility," Springer Books, Springer, number 978-3-030-88203-7, February.
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    3. Evgeny Burnaev & Evgeny Mironov & Aleksei Shpilman & Maxim Mironenko & Dmitry Katalevsky, 2023. "Practical AI Cases for Solving ESG Challenges," Sustainability, MDPI, vol. 15(17), pages 1-15, August.
    4. Carmen Isensee & Kai-Michael Griese & Frank Teuteberg, 2021. "Sustainable artificial intelligence: A corporate culture perspective [Sustainable artificial intelligence: Eine unternehmenskulturelle Perspektive]," Sustainability Nexus Forum, Springer, vol. 29(3), pages 217-230, December.
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