Executive summary
Flagged transactions
10,077
10.1% of total volume
Revenue at risk
£6.81M
of £25.04M total (27.1%)
Critical risk
5,146
risk score ≥ 75 · auto-block
High risk
4,911
risk score 55–74 · manual review
Fraud pattern breakdown
Fraud type distribution
High-Risk Segment
Velocity Fraud
Off-Hours
Large Amount
Other
Hourly risk heatmap
Fraud rate by hour of day — off-hours (00:00–04:59) flag at 100%
Low risk
High risk
Risk segmentation & amount exposure
Fraud rate by customer segment
| Segment |
Transactions |
Flagged |
Risk rate |
| High-Risk | 9,846 | 3,680 | 37.4% |
| Premium | 19,995 | 1,438 | 7.2% |
| Regular | 54,868 | 3,886 | 7.1% |
| New | 15,291 | 1,073 | 7.0% |
Fraud rate by transaction amount band
Channel & merchant analysis
Top suspicious merchants (flagged count)
Category & geographic exposure
Fraud rate by merchant category
Flagged transactions & fraud rate by city
Loss prevention thresholds
Rule-based detection logic & recommended actions
| Action |
Risk tier |
Trigger conditions |
| Auto-block |
Critical (score ≥ 75) |
risk_score ≥ 90 OR amount > £5,000 OR hour in [0–4] |
| Manual review |
High (score 55–74) |
risk_score 55–89 OR segment = 'High-Risk' OR amount > £1,000 |
| Monitor |
Medium (score 35–54) |
risk_score 35–54 OR velocity flag OR channel = 'Phone' |
| Pass |
Low (score < 35) |
risk_score < 35 AND no rule triggers |
Key findings & insights
Off-hours transactions (00:00–04:59) show a 100% fraud rate — the strongest single rule-based signal. Immediate auto-blocking of this window is recommended.
High-Risk segment customers are 5.3× more likely to be flagged than Regular customers (37.4% vs 7.1%). Segment-based thresholds should differ substantially.
Transactions above £5,000 carry an 89.6% fraud rate. An amount-based hard ceiling should trigger automatic blocking pending manual review.
Risk scores separate fraudulent from clean transactions by a 5× margin (avg 75.2 vs 15.0), confirming the scoring model as a reliable real-time filter.