← All case studiesIllustrative example
Industry
Banking
Focus
AML compliance
Screening transactions for suspicious patterns
Flagged transactions arrive with the reason for each flag, ready for an analyst to clear or escalate.
01
The challenge
- —Rule-based alerts produce large queues with little context.
- —Analysts rebuild the story behind each alert by hand.
- —Links between related accounts are hard to see.
02
What the system does
- —Scores transactions against configurable typologies.
- —Shows the network of related accounts and counterparties.
- —Writes a plain-language reason for every flag.
03
What the team sees
- —A prioritised review queue.
- —The evidence behind each alert in one view.
- —A draft note an analyst can edit before escalation.
04
Next steps
- —Walk through the demo on synthetic transactions.
- —Map your current alert rules and typologies.
- —Run side by side with your existing process before any change.
Based on the Sentinel demo.
This is an illustrative example built on synthetic data. It does not describe a real client, and no results are claimed.
