AI in ESG for Financial Institutions: An Industrial Survey
Jun Xu
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.