PEP and sanctions screening has always been noisy.
Most systems flag matches, but stop short of giving users the context and control to make confident calls.
We’ve taken that foundation and built something better.
Context, clarity, and confidence in screening
Strise’s upgraded dispositioning gives teams complete control over each hit:
- See what a hit is, why it’s flagged, and what to do next
- Review fuzzy matches with transparent scoring (name similarity, date of birth, country, and more)
- Confirm or reject a hit with a full audit trail
- Document your decision and export for regulators
- Track system-suggested vs. user-confirmed outcomes at a glance
This is more than flagging. It’s verification with context.
From augmented to autonomous
Since launching the new dispositioning feature, AML teams have:
- Reduced false positives
- Structured decision-making
- Documented actions for audit-readiness
But as alert volumes grow and pressure on L1 teams increases, a new question keeps surfacing: Can Agentic AI do this for me?
That’s the challenge we’ve taken on in the Strise Product Lab, testing a new way to handle PEP and sanctions alerts using Agentic AI (Beta).
Why agentic AI is different
There’s a lot of hype around AI in compliance right now. But here’s the thing:
Not all AI is built the same.
Most tools are passive. They offer:
- Suggestions
- Summaries
- Scores
Agentic AI acts.
AI that executes, not just assists
Agentic AI doesn’t just assist, it autonomously executes decisions using:
- Predefined logic
- Real-time data
- Risk context
It behaves more like a digital team member than a tool.
Where traditional AI says,
“Here’s a score.”
Agentic AI says,
“Here’s what I did—and why.”
What Strise agentic AI does (Beta)
- Automatically reviews and dispositions PEP and sanctions alerts
- Justifies each decision with human-readable reasoning
- Updates outcomes, logs actions, and escalates edge cases to humans
This creates a new layer that handles high-volume alerts quickly and consistently—while your team focuses on the edge cases that require human insight
Currently in beta with a small group of early testers, this feature is designed to:
- Reduce manual workloads
- Ensure transparent audit trails
- Enable faster, consistent remediation
Adrian Trzeciak, Head of Engineering at Strise
“Our goal with autonomous dispositioning is to let compliance teams focus on judgement calls, while the system handles the rest with speed and reliability.”
