AI-Powered Tools for Screening Green Bonds in Emerging Markets: Opportunities for Indian SMEs

Abstract

Green bonds play an important role in facilitating financial support in achieving sustainable development in emerging economies, particularly in enabling Small and Medium Enterprises in India, who contribute 30% to GDP, to raise funds for low-carbon projects. This paper seeks to explore the potential impact that AI technologies, including machine learning and NLP, can have on improving the screening process. This study was conducted with reference to financial innovation theory and the triple bottom line approach. This study has utilized secondary data from RBI, SIDBI, S&P Green Bond Indices (2021-2026), and 20 case studies on anonymized SME data. From these findings, it was concluded that AI technologies have the potential to revolutionize the screening process, overcoming issues faced in manual screening, including high costs and time required. Contrary to these issues, AI technologies have shown superior results in comparison, achieving 92-95% accuracy, reducing costs by 70%, and saving 80% in time, from 4-6 weeks to 2-3 days. This study has shown that AI technologies have the potential to ensure that green capital reaches SMEs, thereby supporting India in achieving its target of becoming net-zero by 2070 and achieving SDGs 7, 9, and 13. This study has provided important implications on how RBI can ensure AI technologies are integrated into the green bond market, how Skill India can play an important role in enabling SMEs, and how refinements can be made in taxonomy in AI-verified issuances.