HR & Payroll
Payroll Benford Analysis
Benford first-digit testing surfaces fabricated or manipulated salary values across the entire population, not just a sample.
Why first-digit distributions expose manipulated payroll
Benford's Law states that in many naturally occurring financial populations the leading digit one appears about 30% of the time, with each higher digit progressively less likely. Genuine net-salary populations broadly conform; fabricated or manipulated values rarely do, which makes first-digit testing a cheap, high-coverage screen for payroll irregularity. AuditPro Core runs Benford analysis across the full net-pay population so auditors can target substantive testing on the digits that deviate most from expectation rather than sampling blind.
The Numbers
AuditPro Core renders this view from your tenant's live, tamper-evident records. The figures below are illustrative sample data.
Payments tested
184 320
Mean deviation
3.1%
▼ within tolerance
Entities flagged
5
chi-square breach
Worst digit
Digit 6
over-represented
Observed vs expected first-digit frequency
Entities by Benford deviation
| Entity | Chi-square | Status |
|---|---|---|
| Mangaung Metro | 41.2 | Breach |
| North West CoGTA | 33.8 | Breach |
| Joburg Water | 12.4 | Clear |
Figures shown are illustrative sample data for demonstration. AuditPro Core renders these views from your own tenant's live, tamper-evident records.
What Benford's Law predicts
Across large, unconstrained financial datasets, leading digits follow a logarithmic distribution: 1 leads roughly 30% of the time, 9 under 5%. Human-fabricated numbers tend to be too uniform or to cluster around psychological thresholds.
Why payroll is a good candidate
Net salaries span several orders of magnitude and are not artificially capped, so a clean population should conform closely. Material deviation points to inserted, rounded or split values worth investigating.
Reading deviation, not declaring fraud
Benford is a screening test, not proof. A spike on a particular digit narrows where to look; the auditor must then perform substantive procedures on the underlying transactions to establish whether an error or irregularity exists.
Combining digits and sub-populations
First-digit, first-two-digit and last-two-digit tests answer different questions, and running them per pay point or per cost centre isolates the unit driving an anomaly rather than masking it in the aggregate.
How AuditPro Core Bridges the Gap
- Full-population coverage: the analysis runs over every net-pay record for the period, eliminating sampling risk on this screen.
- Deviation scoring: observed versus expected frequencies are charted with a materiality threshold so the digits that matter are obvious at a glance.
- Drill-to-source: each anomalous digit band links straight to the contributing payroll transactions for substantive follow-up.
- Continuous monitoring: the test re-runs each pay cycle, building a trend that flags a population drifting away from expected conformity.
Key Takeaways
- Benford is a population-wide screen that costs little and points testing toward genuine outliers.
- Conformity is reassurance, not a clean bill of health; deviation is a lead, not a verdict.
- Running the test per pay point isolates the unit responsible for a spike.
- Pair Benford flags with substantive procedures before drawing any conclusion of irregularity.
See This on Your Own Data
AuditPro Core renders this dashboard from your tenant's live, tamper-evident records — every figure traceable to source.