Insights from Artificial Intelligence and Green Finance: A Bibliometric Analysis

The recent rise of artificial intelligence is significantly reshaping almost every avenue of human life including the economic environment. The potential of these models in mitigating problems and crises is still unraveling. One such vital avenue is the heightened climatic irregularities that have brought the search for sustainable green solutions to the global forefront of financial research. Consequently, this study endeavors to explore the existing literature on the infusion of artificial intelligence through research in green finance. The study has employed a well-established bibliometric methodology to search the SCOPUS database through relevant Boolean operators. Subsequently, the acquired dataset of 23 articles underwent an analysis through RStudio to obtain pertinent information highlighting recent trends and gaps in the existing literature. The study also employed the Linguistic Inquiry and Word Count (LIWC) tool to extract the underlying tones and expectations from AI's implication in green finance. The study's results identified significant gaps and a huge potential for future researchers. The descriptive statistics of the bibliometric assessment indicate a lack of focus from researchers, journals, institutions, and economies. The majority of the literature primarily only focused on the Asian Pacific region. The linguistic assessment summarized and identified that the avenue has significant positive potential and implications. This study covers a significant undertaking addressing the existing situation in the avenue. Furthermore, the value of the investigation is to identify the shortcomings and future directions for the upcoming studies.