Artificial intelligence in green finance: Insights from a PRISMA-driven bibliometric analysis in R
Mots-clés :
Artificial Intelligence, Green Finance, Sustainable Finance, Bibliometric Analysis, PRISMARésumé
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
Téléchargements
Publiée
Numéro
Rubrique
Licence
© Douae YOUBI, Abdessamad OUCHEN 2026

Ce travail est disponible sous licence Creative Commons Attribution - Pas d'Utilisation Commerciale - Pas de Modification 4.0 International.
Les doit d'auteurs sont détenus par les auteurs sous licence: CC-BY-NC-ND.
Tout travail soumis qui est suspecté de piratage ou de plagiat est entièrement sous la responsabilité de l'auteur qui le soumet.
Cette version est hébergée sur revue.ijafame.com dans le cadre du processus de réindexation 2025. Elle remplace l'ancienne publication sur ijafame.org, avec des ajustements techniques conformes aux exigences de Google Scholar.
Chercher l'article par nom de famille de l'auteur