Payroll fraud remains a persistent risk for employers—and analytics is increasingly central to the response. According to the Association of Certified Fraud Examiners (ACFE), payroll fraud is among the most common forms of occupational fraud, and 64% of organizations expand their use of data monitoring and analytics after experiencing an incident. That backdrop shaped discussions during one of the programs at the 2025 PayrollOrg Leaders Conference, where attendees examined how statistical techniques can enhance payroll oversight without disrupting operations.
In a session on foundational payroll analytics, Candace White, CPP, Director of Payroll Administration and Training, highlighted Benford’s Law as a practical early-warning tool for identifying potential fraud. Long used by forensic accountants and cited in IRS analytics, the technique helps payroll teams flag anomalies in transactional data for deeper review. White emphasized that Benford’s Law is a screening method—not a conclusion—designed to guide attention toward areas that may warrant further investigation.
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