Bibliometric analysis identifies research gaps and trends in financial technology studies, suggesting future directions.
This study aims to map the research methodology gaps, in the field of Financial Technology (Fin Tech) and propose some trending topic opportunities for the future. Data collection uses the keyword "Financial Technology" applied to article titles, abstracts, and keywords from the Elsevier Scopus database from early 2014 to April 2023. We map academic contributions and research gaps, focused on the most influential research streams and trends by conducting bibliometric analysis with the help of R software studio, then propose some themes for future research. The results show that there has been an increase in the number of proceedings papers and journal articles on Financia technology. Research on Fin-Tech is dominated by quantitative methods, compared to qualitative and hybrid methods, the use of analytical tools such as Artificial Intelligence, machine learning, and Generalized Moment Methods has increased in the scope of statistical methods. Quantitative research is dominated by China and Indonesia. The UK produces the most research on qualitative methods, while mixed-method research is highly developed in the UK, the United States, and South Africa. The results of this study identify the most influential articles on fintech, a map that is different from previous studies; visualize focus areas and trends; and determine areas for further research. These findings will help academics focus their research, based on under-researched scientific areas in this heterogeneous niche.
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Salahudin et al. (2025) studied this question.
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