Operational
Operational Loss Event Database
Frequency and rand value of recorded operational loss events by Basel-style event category.
Why a Loss Event Database Matters
Operational losses that go unrecorded cannot be analysed, provisioned for or prevented from recurring, which is precisely the gap AGSA findings on irregular and fruitless expenditure repeatedly expose. A disciplined loss event database gives the accounting officer and audit committee an evidence base for the risk register required under the PFMA and MFMA, and aligns the entity with COSO's call for actual-loss data to validate control design. AuditPro Core captures each event once, categorises it Basel-style and links it to the control that failed.
The Numbers
AuditPro Core renders this view from your tenant's live, tamper-evident records. The figures below are illustrative sample data.
Events logged (YTD)
214
▲ 18
Gross loss value
R 86.3 m
▲ R 12 m
Recovered
R 21.4 m
25% recovery
Near-misses
67
Loss value by event category
Top loss events this year
| Event | Category | Loss (R m) | Status |
|---|---|---|---|
| Payroll ghost employees | Fraud & theft | 9.1 | Under recovery |
| Billing system corruption | System outage | 6.4 | Resolved |
| Fleet fuel leakage | Process failure | 5.2 | Investigating |
| Litigation award | Legal & penalties | 4.8 | Settled |
Figures shown are illustrative sample data for demonstration. AuditPro Core renders these views from your own tenant's live, tamper-evident records.
Basel Event Taxonomy
The Basel framework sorts operational losses into seven categories such as internal fraud, external fraud, and execution and process failure. Applying a consistent taxonomy lets you compare losses across departments and over time rather than treating every incident as unique.
Frequency versus Severity
Two distinct risk signals live in the same data: how often losses occur and how large they are. A category with many small losses points to a broken routine control, while rare high-value losses point to a catastrophic exposure that scenario analysis must address.
Near-Miss and Recovery Capture
A mature database records not only realised losses but near-misses and amounts recovered. Near-misses are free lessons about where controls almost failed, and recoveries reveal whether the entity's response and legal processes actually claw value back.
From Loss Data to Control Action
Loss data only earns its keep when each entry is tied to the control or process that failed. That linkage turns a passive log into a feedback loop that drives control redesign and informs the combined assurance plan.
How AuditPro Core Bridges the Gap
- Single point of capture: every loss event is logged once against a Basel category, owner and root cause, eliminating the parallel spreadsheets auditors so often find.
- Control traceability: each event links to the specific control that failed, so remediation targets the breakdown rather than the symptom.
- Exception workflow: high-value or repeat-category losses trigger escalation to the risk owner and audit committee with a tracked resolution trail.
- Audit-ready export: generate a tamper-evident loss schedule for working papers and the irregular-expenditure register in one step.
Key Takeaways
- A consistent Basel-style taxonomy makes losses comparable across departments and financial years.
- Track frequency and severity separately — they point to different control weaknesses.
- Capturing near-misses and recoveries gives a fuller picture than realised losses alone.
- Linking each loss to a failed control turns the database into a control-improvement engine.
See This on Your Own Data
AuditPro Core renders this dashboard from your tenant's live, tamper-evident records — every figure traceable to source.