AI-Driven Sustainable Finance Models for Green Lending Decision-making in Commercial Banks: A Review

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DOI: https://doi.org/10.5281/zenodo.21357331

Shafali¹ and Neeru Pharia² (Department of Commerce, Guru Jambheshwar University of Science & Technology, Hisar, Haryana¹ and JCDV Memorial College, Sirsa, Haryana²)

This research is conducted to investigate the impact of Artificial Intelligence (AI) on the process of the sustainable finance transformation process, specifically on making green lending decisions in commercial banks. By using a qualitative research approach and secondary data sources for the literature analysis, this paper discusses the use of AI technologies, including machine learning and expert systems, in assessing ESG indicators and promoting the development of climate-oriented financial activities. Based on frameworks, such as the EU taxonomy and Green Bond Principles, this study explains the positive effect of AI in enhancing the efficiency of the green lending decision-making process by finding out sustainable projects, detecting greenwashing, performing risk assessments, determining loan prices, and promoting regulatory compliance and transparency. Moreover, the study focuses on the use of AI in clean energy finance and fintechs. The findings prove that AI improves practices in sustainability, helps to perform risk assessments, informs green lending decision-making process, and supports policy-makers in developing regulations according to the latest technologies. Despite some limitations related to the absence of empirical data and secondary data sources, the research presents a comprehensive overview of AI-based green lending models. Future research should be focused on quantitative analyses and cases studies.