AUDIT PERFORMANCE, PROCESS AND QUALITY: EVIDENCE FROM BIG DATA ANALYTICS-DRIVEN AUDITS
DOI:
https://doi.org/10.21512/jafa.v13i1.15395Keywords:
Audit Quality, Big Data Analytics, Audit Perfomance, Audit Process, PLS-SEMAbstract
This study provides empirical evidence on the pathways of digital transformation in auditing, examining how Big Data Analytics (BDA) adoption influences audit quality through audit performance and the audit process within the highly regulated environment of Big Four firms in an emerging economy. Using a quantitative approach, survey data were collected from 254 active external auditors at Big Four accounting firms in Indonesia who have active involvement with BDA platforms. The empirical data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) to test both direct relationships and dual-pathway mediations. The results reveal that Big Data Analytics has a positive and significant direct effect on audit performance and audit quality. Audit performance is also proven to significantly enhance audit quality and serve as a vital mediator between BDA and audit quality. However, BDA does not have a significant effect on the audit process, and the audit process does not influence audit quality or act as a mediator. Procedural automation without corresponding cognitive competency enhancement fails to deliver superior audit quality. Public accounting firms should avoid the "technological fallacy" of over-investing in rigid procedural workflows. Instead, strategic resources must be directed toward data-literacy training and cognitive upskilling to maximize auditor performance and successfully safeguard financial reporting credibility.
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