The Influence of AI-Driven Bookkeeping Systems on Accuracy, Fraud Detection, and Auditor Workload in Emerging Markets

Yustina Hiola

doi:10.55927/fjst.v4i12.336

Authors

Yustina Hiola Universitas Negeri Gorontalo

DOI:

https://doi.org/10.55927/fjst.v4i12.336

Keywords:

AI-Driven Bookkeeping, Accuracy, Fraud Detection, Auditor Workload, Emerging Markets

Abstract

This study analyzes the impact of AI-based bookkeeping systems on accuracy, fraud detection, and auditor workload in medium-sized companies in Indonesia, focusing on regions with growing technological maturity—North Sulawesi, Central Sulawesi, and Gorontalo. Using a quantitative survey of 85 accountants, finance staff, and auditors who actively use AI-driven bookkeeping applications, perceptions were measured using a five-point Likert scale and analyzed through multiple linear regression. The findings show that AI significantly improves record-keeping accuracy by reducing manual errors, enhances fraud detection through anomaly identification, and decreases auditor workload by automating routine tasks, although system-based verification remains necessary. The study concludes that AI adoption can enhance financial reporting quality and audit efficiency in emerging markets, providing theoretical contributions to digital accounting literature and practical insights for improving financial process effectiveness.

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