Authors: Dr. Abhijit Chakraborty, Bharath K N, Shriram, Yogeesha L C
Abstract: The integration of Artificial Intelligence (AI) into sustainable and ethical investing (ESG) is transforming financial markets, aligning them with global sustainability goals. While the exponential growth of ESG practices is challenged by the complexity and scale of environmental, social, and governance (ESG) data, AI offers a powerful solution. AI technologies, including machine learning and natural language processing (NLP), significantly advance ESG integration. They process vast, unstructured datasets—like corporate disclosures, media reports, and regulatory filings—to provide a nuanced and real-time understanding of a firm's ESG performance. NLP, for example, deciphers qualitative information and identifies reputational risks that conventional methods might miss. AI helps overcome key issues such as data inconsistency and subjectivity in ESG ratings, enhancing transparency and accountability. It facilitates scenario analysis to stress-test portfolios against climate or social risks, building more resilient and ethically sound portfolios. However, challenges exist, notably algorithmic bias, data privacy, and the "black box" nature of some models. Responsible deployment requires robust governance, transparency standards, and regulatory oversight. Ultimately, AI is a key enabler for informed, principled financial decisions, maximizing sustainable development through ethical investing.
