Period:
18%
₱8.2M
Fraud Prevented
Year to date · demo data
24%
₱2.46M
Current Exposure
vs ₱3.2M last month
2.3%
99.2%
Detection Rate
Model precision
15%
4.2min
MTTD
Mean time to detect
141
Closed with Feedback
Outcomes fed back to models
Fraud Trend (30 Days)
Detection vs Prevention Rate
By Fraud Category
By Channel
By Region
ML Model Performance
99.2%
Precision
+0.3%
97.8%
Recall
+1.2%
98.5%
F1 Score
+0.8%
0.994
AUC-ROC
+0.002
OODA Pipeline Metrics
| Stage | Cases | Avg Time | SLA % | Automation % | Trend |
|---|---|---|---|---|---|
| Observe | 47 | 2.4 min | 98.5% | 95% | -12% |
| Orient | 32 | 8.7 min | 94.2% | 72% | -8% |
| Decide | 28 | 15.3 min | 91.8% | 45% | 0% |
| Act | 15 | 4.1 min | 99.1% | 88% | -18% |
| Feedback | 141 | N/A | 100% | 100% | +23% |
Top Fraud Vectors by Volume
| Vector | Cases | % | Trend |
|---|---|---|---|
| Account Takeover | 86 | 32.7% | |
| Rewards Fraud | 65 | 24.7% | |
| Behavioral Anomaly | 36 | 13.7% | |
| SIM Box | 22 | 8.4% | |
| IMEI Cloning | 20 | 7.6% |
Top Fraud Vectors by Exposure
| Vector | Exposure | % | Trend |
|---|---|---|---|
| Account Takeover | ₱2.2M | 89.4% | |
| SIM Box | ₱129K | 5.3% | |
| Wangiri | ₱44K | 1.8% | |
| IRSF | ₱27K | 1.1% | |
| Behavioral | ₱25K | 1.0% |