Artificial Intelligence in Finance : The Journey of Robo Advisors So Far and the Way Ahead

Purpose : This bibliometric research article aimed to provide a comprehensive overview of the academic literature on robo-advisory services in finance, identifying key trends, influential factors, and potential avenues for future research. Design/Methodology/Approach : A systematic bibliometric analysis was conducted for scholarly articles published on the topic of robo-advisory between 2016 and 2022. The metadata was sourced from two premier research databases : SCOPUS and Web of Science. The metadata of 210 documents was analyzed using the Bibliometrix package of R. Results : A substantial growth in research on robo-advisory services in finance over the past decade was found. The application of robo-advisory in terms of asset allocation and portfolio optimization was seen. While most of the research focused on the technology enablers of robo-advisory, the applications offer further areas of study. Practical Implications : The findings suggested promising avenues for future research, including the further integration of artificial intelligence and machine learning techniques in financial decision-making. Originality : The study attempted to touch upon different aspects of this topic in terms of its enablers, technology, applications, and challenges faced. This research tried to design a path for further work in this field by suggesting a few bases that have not been studied much yet.