International Journal of Scientific Research and Engineering Development

Artificial intelligence (AI) is quickly reshaping the financial services industry, such as the up-andcoming and rapidly expanding field of sustainable finance. AI will help to multiply the positive impacts on the environment and the social sector by automating the assessment of the risks, improving ESG data analysis, and allowing a dynamic and sustainability-linked decision-making process. Nonetheless, applying AI to sustainable finance presents urgent ethical and governance risks: algorithmic discrimination and biases, obscurity and lack of explainability, quality and provenance of data, undermined accountability in the decision-making process, and increased greenwashing and perverse incentive risks. In this paper, the critical assessment of these issues is made, and technical, organizational, and policy-level solutions are suggested. Based on the recent regulatory initiatives and scholarly sources, we suggest that to close the disconnect in between AI capability and ethical governance, (a) strong data governance and model audits, (b) explicit legal and board-level accountability, (c) explainability and contestability strategies, specific to financial and ESG circumstances, and (d) policy coordination between financial regulation and the principles of AI governance are needed. The outcome is a list of recommendations in practice that institutions, regulators, and researchers wishing to implement AI should follow to implement it in a manner that actually contributes to sustainable finance and does not cause social harm disproportionately.