Investigating the Potential Areas in Artificial Intelligence and Financial Innovation: A Bibliometric Analysis

Abstract

In recent years, there has been widespread interest in the applications of Artificial Intelligence (AI) techniques to the financial sector and in the development of new financial products and services. AI methods are widely regarded as the most important methods in the emerging market for providing not only cutting-edge financial services, but also an innovative approach to business process automation, a solution to the challenges of reducing service costs associated with managing low-income and rural customers and a method of identifying and evaluating the creditworthiness of those customers. No clear reviews are identified in the areas of AI and its contribution to Financial Innovations (FI) research in finance. To address the above gap, the present study provides a systematic literature review and bibliometric view of AI and FI research in finance. Co-citation, co-occurrence and bibliographic coupling analysis techniques are being used to make inferences about the structure of AI and FI research in finance from 1987 to 2022. The study used 237 filtered research articles from the Scopus database and processed through VOS-Viewer and Biblioshiny through “R” to justify study objectives. Through bibliometric analysis, this study unveils influential authors, journals and institutions, emphasizing top-cited research articles and unveiling six emerging thematic clusters. The novelty lies in the identification of prominent keywords linked to AI and financial innovation research, accompanied by a comprehensive analysis of globally and locally cited articles. Employing an analytical approach, the study identifies research gaps to contribute to the existing body of knowledge.