Bibliometric Analysis Of Anticipating Digital Financial Report Fraud Using Vosviewer

Purpose: The purpose of this study was to determine the development of research on anticipating digital financial reporting fraud using bibliometric analysis on the VOSviewer application version 1.6.20. Methodology/approach: The research method used is a qualitative method with a thematic analysis approach. Findings: The results of the study showed that the development of research on anticipating digital financial reporting fraud from 2019-2024 experienced significant annual fluctuations. In the last year, there has been a marked increase in the number of publications. The most publications in 2024 and the smallest in 2020, consisting of 11 clusters with 173 keyword items with the most publications in Heliyon and Procedia Computer Science. Technologies such as blockchain, big data analytics, and artificial intelligence are identified as important tools in detecting and preventing fraud. Practical implications: The results of this study can be used as a guide for companies and academics in developing digital strategies to improve financial monitoring and transparency systems. Originality/value: To the best of the researcher's knowledge, this study is the first study to examine the development of digital financial reporting fraud anticipation research with bibliometric analysis of Scopus indexed publications in 2019–2024