Predictive Ops
AI Insights
Model performance, emerging patterns, and forecasted risks across the banking estate.
14 signals · 2m ago
Resolution Accuracy
93%
+4.2% vs last week
Auto-Resolved Rate
68%
+8% vs last week
Prediction Confidence
86%
+3% vs last week
Anomalies Detected (7d)
142
+21 vs last week
Model Accuracy Trend
Weekly resolution accuracy · last 8 weeks
MTTR Improvement
Minutes to resolve · lower is better
Incident Forecast (next 7 days)
Predicted vs actual incident volume
Incident Categories
Distribution · last 30 days
Top Recurring Root Causes
Ranked by 30-day occurrence
DB connection pool saturation34
Downstream 429 throttling28
Config drift after deploy21
Cache stampede17
Expired TLS certificate12
Kafka rebalance storm9
Confidence Distribution
AI verdicts across confidence buckets
Incident Heatmap
Concentration by hour of day · last 7 days
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Emerging Signals
Patterns, forecasts and anomalies
Pattern
Recurring pattern detected
Payments-db saturation correlates with 09:00 IST batch job over last 4 weeks.
Confidence · 78%
Forecast
Predicted capacity breach
Core-banking-api projected to exceed 85% CPU by Fri 14:00 IST.
Confidence · 82%
Change
Change risk elevated
3 deployments queued to auth-svc — historical failure rate 22%.
Confidence · 86%
Anomaly
Anomaly cleared
Fraud-ml latency returned to baseline after model rollback.
Confidence · 90%
AI Learning Timeline
Model updates and knowledge growth
- 2h agoLearned new signature: payments-db pool exhaustion
- 6h agoRetrained anomaly model on last 30d telemetry
- 1d agoAuto-tuned severity thresholds for cards-api
- 2d agoAdded correlation rule: SWIFT + treasury-fx
- 3d agoMerged 12 duplicate incident signatures