Artificial Intelligence (AI) of Financial in the VUCA Era: A Systematic Mapping Study


  • Iryani Iryani Sekolah Tinggi Ilmu Ekonomi Wira Bhakti Makassar, Indonesia
  • Harry Yulianto Sekolah Tinggi Ilmu Ekonomi YPUP Makassar, Indonesia




mapping, systematic, artificial intelligence, financial, fintech.

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The purpose of the study was to systematically map Artificial Intelligence (AI) in the financial sector in the VUCA era. The research design employed a quantitative approach with a descriptive method. The study utilized a systematic literature review with bibliometric analysis techniques. Researchers collected the data from the Google Scholar database, technique analysis using VOSviewer, and descriptive statistics as data analysis techniques. The results indicated the following: (RQ1) 539 articles met the criteria for research; (RQ2) Springer was the publisher with the highest number of AI in Financial articles (58 articles); (RQ3) Karina Kasztelnik authored the most papers on AI in financial (3 documents); (RQ4) an article written by David Mhlanga titled "Industry 4.0 in Finance: The Impact of Artificial Intelligence (AI) on Digital Financial Inclusion" had the most citations (145 citations); and (RQ5) the systematic mapping results identified 8 clusters as research gaps, suggesting potential themes for future studies related to AI in the financial domain. The findings indicate a research gap and highlight the potential for further research on AI in the financial sector in the VUCA era. The role of AI in the financial industry in the VUCA era was to enhance efficiency, speed, accuracy, and security. AI can assist in addressing rapidly emerging complex challenges, providing competitive advantages for FinTech companies to navigate dynamic changes and uncertain business environments.


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Submitted Date: 2023-03-24
Accepted Date: 2023-04-30
Published Date: 2023-06-30

How to Cite

Iryani, I., & Yulianto, H. . (2023). Artificial Intelligence (AI) of Financial in the VUCA Era: A Systematic Mapping Study. Journal of Computer Networks, Architecture and High Performance Computing, 5(2), 398-413.