SYSTEMATIC LITERATURE REVIEW : DAMPAK TEKNOLOGI BIG DATA ANALYTICS DALAM MENDETEKSI FRAUD PADA BIDANG AUDIT

Abstract

This study aims to analyze previous research on the impact of adopting big data analytics technology in detecting fraud in the audit field. This study also perpetuates empirical research related to BDA and finds out the differences, so that this research can serve as a guide for future empirical studies.

This research uses the systematic literature review (SLR) method to analyze various articles published on the Scopus database with a range of publication years from 2019 to 2023. The article screening process was carried out by referring to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. Twenty articles were obtained which will be synthesized to answer the research questions.

The results of the analysis in this study state the conclusion that technological developments have had a positive impact on the audit profession, the environment and efficiency and optimization of performance processes. The adoption of big data analytics technology can assist auditors in fraud detection efforts. One way that can be done is by integrating BDA in forensic accounting. Global technological innovation factors generally encourage audit firms to adopt BDA technology. However, factors such as size, quality of human resources, scope of operations, international affiliations and technological capabilities of the firm determine the level of adoption of big data analytics technology.