Artificial intelligence in green finance: Insights from a PRISMA-driven bibliometric analysis in R

Abstract

Sustainable finance has become an essential area of research as environmental and social challenges increasingly shape financial decision making. In this context, artificial intelligence (AI) has emerged as a catalyst for innovation and forecasting processes. However, its integration into sustainable finance, particularly in the context of green finance, is still not fully understood. This study examines how research at the intersection of artificial intelligence and sustainable finance, green finance  had evolved over time through a bibliometric analysis of 301 publications indexed in Web of science and Scopus between 1986 and 2025, Using the bibliometrix package in R and following PRISMA guidelines, this study examines publication trends, influential contributors, emerging research themes, and additional bibliometric indicators, including co-authorship networks, citation patterns, and keyword co-occurrence analyses.. The results reveal a strong growth rate of 29,39% with approximately 99% of publications produced between 2021 and 2025, highlighting the highly emergent and rapidly evolving nature of this research field, with particular attention to ESG assessment, risk analysis, and green finance applications. China, India, the United Kingdom, Malaysia, and the United States lead scientific production. The analysis further reveals a strongly collaborative research landscape, structured around distinct international co-authorship networks dominated by Asian and Western research hubs. Influential journals such as Sustainability, Energy Economics, and the International Review of Financial Analysis play a central role in shaping academic discussions. These findings point to important implications for financial institutions and policymakers, showing that artificial intelligence has the potential to improve transparency, enhance the credibility of green finance practices, and support more informed sustainability-oriented decision making.

Classification JEL: B41, Q56, O33

Paper type: Theoretical Research