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September 10, 2025International Journal of Social Impact0 citations

Forensic Accounting in the Age of AI: Detecting Fraud with Data Anomalies

Key Points

AI enhances fraud detection using anomaly detection algorithms in forensic accounting, transforming financial investigations.
Data anomalies serve as critical indicators in identifying fraudulent patterns that traditional methods may miss.
Machine learning techniques significantly boost the efficiency and accuracy of forensic accounting practices.
The integration of AI tools simplifies the detection of complex financial irregularities, indicating a future shift in forensic analysis.

Abstract

The integration of Artificial Intelligence (AI) into forensic accounting is transforming the landscape of fraud detection and financial investigation. Traditional forensic accounting methods often rely on manual scrutiny, which can be time-consuming, error-prone, and insufficient to detect complex or subtle financial irregularities. This paper explores how AI, particularly machine learning and anomaly detection algorithms, enhances the ability to identify fraudulent patterns hidden within vast and complex financial datasets. By focusing on data anomalies—irregularities or deviations from expected patterns—AI-driven forensic tools can uncover indicators of fraud that may elude conventional analysis.

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