Procurement Anomalies
Benford's Law Anomaly Scan
Tests payment first-digit distributions against Benford's Law expectations.
Why First-Digit Patterns Reveal Fraud
Genuine financial populations follow a predictable first-digit distribution known as Benford's Law, where ones occur far more often than nines. Fabricated or manipulated amounts tend to deviate from this pattern, making the test a long-standing forensic and ISSAI-aligned analytical tool. AuditPro Core applies Benford analysis to payment populations so statistically improbable clusters are flagged for targeted investigation rather than blanket sampling.
The Numbers
AuditPro Core renders this view from your tenant's live, tamper-evident records. The figures below are illustrative sample data.
Transactions Tested
184,902
12-month window
Chi-Square Variance
High
3 depts flagged
Digit-1 Deviation
+4.1pp
above expected
Suspect Population
R 67m
for review
Observed vs Expected First-Digit Frequency (%)
Departments by Deviation
| Department | Deviation (pp) | Transactions | Flag |
|---|---|---|---|
| Dept B | 6.3 | 24180 | High |
| Dept D | 5.1 | 18920 | High |
| Dept A | 4 | 31240 | Medium |
| Dept C | 2.2 | 27600 | Low |
| Dept E | 1.4 | 19840 | Low |
Figures shown are illustrative sample data for demonstration. AuditPro Core renders these views from your own tenant's live, tamper-evident records.
The Expected Distribution
Benford's Law predicts that the leading digit one appears in about 30 percent of values and nine in under 5 percent. Many naturally occurring financial datasets conform closely to this curve.
What Deviation Suggests
A spike in particular leading digits can indicate amounts engineered to sit just under approval thresholds, invented invoices, or duplicated values. Deviation is a signal to investigate, not proof of fraud.
Conditions for Validity
The test needs a sufficiently large population spanning several orders of magnitude. Capped, sequential or narrowly ranged amounts can deviate for innocent reasons, so context matters.
How AuditPro Core Bridges the Gap
- Distribution testing: payment first digits are compared against Benford expectations across the full population.
- Anomaly isolation: over-represented digit bands are drilled into to expose the underlying transactions.
- Exception workflow: flagged clusters route to investigators with the contributing payments attached.
- Traceability to source: every anomaly links back to the source transactions for follow-up.
Key Takeaways
- Benford deviation is an investigative signal, never proof on its own.
- Spikes often point to threshold-gaming or fabricated amounts.
- The test needs a large, wide-ranging population to be meaningful.
- Use it to target effort, replacing blanket sampling with risk-led review.
See This on Your Own Data
AuditPro Core renders this dashboard from your tenant's live, tamper-evident records — every figure traceable to source.