KYC
Secure, compliant digital customer onboarding with identity verification, liveness and periodic re-KYC.
AML
Anti-money-laundering transaction monitoring, alert triage and investigation tooling that reduces false positives.
The problem
Rules-based transaction monitoring generates large volumes of alerts, most of which are false positives. Investigation teams spend their time clearing noise while genuinely suspicious activity can be missed.
Our approach
Map typologies and risks against existing scenarios.
Calibrate thresholds with below-the-line testing.
Add explainable risk scoring to focus investigators.
Provide entity resolution and network context.
Capabilities
Typology-driven scenarios with documented calibration.
Explainable models that rank alerts by likely risk.
Linking customers, accounts and counterparties across systems.
Graph analysis to expose mule networks and layering.
Screening logic and fuzzy-matching optimisation.
Case management with evidence and narrative support.
Engagement
Standards & technology
FAQ
In most programmes ML complements rather than replaces rules: scenarios provide regulatory coverage and explainability, while models prioritise and enrich alerts.
Let’s discuss it. Tell us what you are working on and an engineer — not a sales script — will respond.