RegNovaIQ combines rule-based monitoring, behavioral analytics, and streaming anomaly detection to surface suspicious activity with full audit context — then routes it straight into a governed investigation and SAR workflow.
Screening stops bad actors at the door; monitoring watches the activity that follows. RegNovaIQ evaluates transactions as they stream, builds a behavioral picture of each customer, and escalates only what genuinely deviates — keeping analyst time focused on real risk.
Streaming rules and behavioral models score activity in real time, blending static policy with adaptive anomaly detection.
Alerts are prioritized by risk tier, scenario, and SLA, with contextual timelines and linked entities for fast review.
Confirmed suspicion flows into a SAR workflow that assembles evidence and routes it through approval gates to filing.
Blend static policy rules with adaptive detection models in a single orchestration plane. Every alert carries explainability and configurable escalation paths so analysts understand why it fired.
Analysts see contextual timelines, linked entities, and customer risk profiles to accelerate investigations and cut repetitive review.
Prioritize by risk tier, scenario, and SLA with suppression logic for known-good patterns.
Cluster related alerts and entities into a unified investigation instead of disconnected single alerts.
Generate SAR-ready evidence packs with full audit trails and analyst notes.
Monitoring runs on the platform's shared engines, so the same resolved entities and unified risk scores from screening and fraud follow each customer into surveillance — no siloed, contradictory views.
The goal is fewer, better alerts. Behavioral baselines, suppression logic, and case linkage reduce false positives while preserving a complete, auditable record of every decision.
Connect your transaction rails and deploy risk policies in weeks, not quarters.