Integrating the Altman Z-Score, Beneish M-Score, and Granular Financial Ratios at PT Tiga Pilar Sejahtera Food Tbk for Early Fraud Detection
DOI:
https://doi.org/10.33830/jfba.v6i1.14703.2026Keywords:
Financial Statement Fraud, Altman Z-Score, Beneish M-Score, Financial Ratio, Early DetectionAbstract
This research investigates the early detection of financial statement fraud at PT Tiga Pilar Sejahtera Food Tbk (AISA) by identifying quantitative traces of manipulation years before public exposure. Although accounting-based fraud screening models are well established, prior evidence provides limited insight into how fraud risk accumulates over time at the account level, particularly in emerging markets where high-quality fraud labels are scarce. Employing a quantitative case study approach, the study investigates the early detection of financial statement fraud at AISA using secondary audited data from 2012 to 2016. Data analysis integrates the Altman Z-Score model for financial distress, the Beneish M-Score model for earnings manipulation, and granular financial ratios. Results show that while the composite manipulation score remained in the non-manipulator range, several M-Score indices exhibit red-flag classifications, the Z-score declined to 1.806 in 2015, accounts receivable-to-sales increased to 0.366 by 2016, and inventory days rose to 153. The practical implication is that aggregate manipulation scores may mask subtle but material account-level anomalies. Therefore, auditors and market participants should adopt integrated monitoring that combines distress screening with targeted forensic attention to receivables, inventory, and depreciation-related accounts to improve early detection of potential misstatements.
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