Real risk only. No noise.
Real risk reaches your analyst. Everything else is cleared before it arrives.
Sound familiar?
01Nine in ten alerts are false positives. Your team confirms every one before moving on
The genuine risk that screening is designed to catch is buried under a flood of irrelevant matches. The ratio gets worse with common names and global client bases.
02The sanctions list updated overnight. Re-screening the whole portfolio starts now. Manually
List updates should trigger automatic re-screening. Instead they trigger a team briefing, a task allocation meeting, and a queue that takes weeks to clear.
03Adverse media from seven years ago still fires every quarter. Someone checks it every time
Screening without date and relevance filters treats a decade-old minor press mention the same as a recent financial crime conviction. The volume is unmanageable.
04Your analyst cleared the same false positive on three different clients this week
No institutional memory. The same name match that was investigated and dismissed last month is investigated and dismissed again — by a different analyst who has no record of it.
05Re-screening was supposed to happen quarterly. The backlog is already three months behind
Periodic re-screening at scale only works if it’s automated. When it is manual, it is always the thing that slips when something more urgent arrives.
06The name matched. Is it actually your client? Someone has to confirm every single one
Name matching without context is a noise machine. Date of birth, nationality, entity type, none of it checked automatically, so every hit lands on a human to investigate.
The difference Strise makes.
30%fewer false positives reaching your analysts.
100%of alerts reach analysts pre-assessed.
11.5Mentities screened by a single European payments customer.
What customers say.
“With Strise, AI can take on much of the time-consuming routine work.”
Anne Reisch BrusetHead of KYC at BDO 
Gavin BerginDirector of Governance at British Land 
Silke OeverbyChief Risk & Compliance Officer at Vipps MobilePay 
Endre Jo ReiteDirector of personal markets 
Rebecca RobinsonChief Risk and Compliance Officer at Tenora 
Niri Kvammen ForbergAML Specialist at SpareBank 1 SMN 
Ragnhild GeorgsenHead of AML & Sanctions at Sparebanken Norge 
Alan PatersonFounder and Chief Innovation Officer at Plenitude 
Separate real risk from noise.
Entity in. Screening begins
The screening check begins the moment an entity enters the workflow. Nothing waits.
Context matched. Not noise
Date of birth, nationality, jurisdiction, and entity type used together to reduce false positives.
All signals. At once
Sanctions lists, PEP databases, and adverse media checked and scored at the same time.
Risk confirmed. Alert raised
Confirmed PEP, sanctions, and adverse media hits escalated with full context and recommended action.
Automate screening.
Alerts triaged. Only real matches reach your analyst.
For every PEP, sanctions, and adverse media alert, AI assesses match confidence and separates confirmed hits from false positives. Analysts confirm, dismiss, or escalate, they don’t investigate from scratch.
Your screening policy applied automatically.
Define how PEP, sanctions, and adverse media matches should be treated. Set risk weights, escalation rules, and review thresholds once, then the same policy applies consistently across every entity and every alert, without anyone needing to enforce it.
Re-screening runs without anyone starting it.
When a sanctions list updates or new adverse media appears, re-screening triggers automatically across your portfolio. No manual trigger. No briefing to get it started. Your portfolio is always screened against current data, not last month’s.
Alerts arrive with the investigation already prepared.
Each alert includes the matched watchlist record, the contextual attributes used for verification, the source list, and the reason the match triggered. Your analyst reviews the evidence and makes the decision, they don’t assemble it.
Screening results in your case system. No context switching.
Alerts and review outcomes sync directly with your CRM, TMS, or CLM. Your team reviews screening results without switching systems, re-entering data, or rebuilding context from scratch.
Every screening decision logged. Including the ones that said no.
Every check, every closure, every alert dismissed as a false positive, logged automatically with source, timestamp, and rationale. When your regulator asks why an entity was cleared, the answer is already written. Nothing to recall. Nothing to reconstruct.
See how much of your alert queue disappears.
Most alert volume is noise. Let us show you what your team’s workload looks like when false positives are cleared before they arrive.
Things we get asked. Answered.
How does Strise identify PEPs, and what counts as one?
Strise screens against major global PEP datasets. Coverage includes family members and close associates according to your policy. What qualifies as a PEP is configurable. Your policy defines the scope. Strise applies it consistently across every entity.
Which screening lists and data sources does Strise use?
Dow Jones is the primary data source — covering OFAC, EU, UN, HMT, and dozens of other sanctions and watchlists. Lists are updated in real time, so your team never screens against yesterday’s data. When a list updates, re-screening triggers automatically across your portfolio.
How does the AI decide what’s a false positive?
It does not guess. Each match is verified against additional attributes such as date of birth, nationality, jurisdiction, and entity type. When those attributes do not align with the watchlist record, the match is cleared automatically and the rationale is recorded in the audit trail. Only matches where the attributes remain consistent are escalated to your team for review.
How often does Strise re-screen our portfolio?
Sanctions and PEP lists are monitored continuously. When a list updates or a new designation is added, re-screening triggers automatically — no manual trigger, no team briefing required. Your portfolio is always screened against current data, not a snapshot from last quarter.
Does Strise include adverse media screening?
Yes. Global news sources are scanned and scored for date, severity, and topic relevance. A recent financial crime conviction surfaces. An unrelated article from seven years ago doesn’t. The result is a curated set of genuinely material hits — not a flood of noise to sift through.
What does the audit trail look like for screening decisions?
Every match — cleared or escalated — is logged automatically with its rationale, data source, and outcome. When your regulator asks how screening decisions were made, you show them the trail. You don’t reconstruct it from emails or case notes.
Running a formal evaluation?
Send us your RFP. We’ll come back with real numbers for your setup.