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A Structural Analytical Framework for Technology-Driven Fraud Detection and Audit Outcomes

International Journal of Analysis and Applications | 2026

Paper Details

Authors: Thuy L.T.T.

DOI: 10.28924/2291-8639-24-2026-130

Journal: International Journal of Analysis and Applications

Year: 2026

Publisher: Etamaths Publishing

Document Type: Article

Open Access: All Open Access; Gold Open Access

Cited by: 0

Abstract

This paper develops a structural analytical model to examine the relationships between technology-related capabilities and audit outcomes through an intermediate analytical mechanism. Within a quantitative structural analysis framework, the study investigates the effects of artificial intelligence adoption, data analytics capability, and auditor IT competence on fraud detection effectiveness, and examines the mediating role of fraud detection effectiveness in determining audit quality. The empirical model is estimated using survey data from 298 external auditors in Vietnam and analysed via Partial Least Squares–based structural equation modelling. The results show that artificial intelligence adoption, data analytics capability, and auditor IT competence have positive and statistically significant structural effects on fraud detection effectiveness, with artificial intelligence adoption exhibiting the largest standardized coefficient. In addition, fraud detection effectiveness exerts a strong positive effect on audit quality and fully mediates the relationships between technology-related capabilities and audit outcomes. The proposed structural framework provides an applied analytical interpretation of how technology-driven mechanisms influence audit performance and offers implications for the design of technology-enabled audit systems in emerging markets. © 2026 the author(s).

Keywords

applied statistical analysis; mediation analysis; partial least squares modelling; quantitative modelling; structural analysis