SUSTAINABLE FINANCE AND ESG INVESTING: EMERGING TRENDS AND TECHNIQUES IN AI ERA

Abstract

The integration of Environmental, Social, and Governance (ESG) factors into financial decision-making has become a cornerstone of sustainable finance, especially in the context of growing global challenges such as climate change, social inequality, and corporate governance. In the era of artificial intelligence (AI), the methodologies and tools supporting ESG investing are rapidly evolving. This paper explores emerging trends and techniques at the intersection of sustainable finance and AI, highlighting how machine learning, natural language processing, and big data analytics are being leveraged to enhance ESG data accuracy, portfolio optimization, risk assessment, and impact measurement. It also examines the role of regulatory frameworks, investor preferences, and ethical considerations in shaping AI-driven ESG strategies. The findings suggest that while AI has the potential to improve transparency and efficiency in sustainable investing, it also presents challenges related to data quality, algorithmic bias, and accountability. This study contributes to a deeper understanding of how AI is transforming ESG investing and provides a roadmap for responsible and effective integration of technology in sustainable finance.