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Sanctions, PEP and adverse media screening, sold on its own or wired directly into the customer risk model, CDD/EDD triggers and ongoing due diligence.
UN, EU, OFAC, HMT, national and regional lists. Two vendors screening the same name against the same sources return the same hit. That is not where a screening programme wins or loses.
Sanctions, PEP and adverse-media lists. Priced on volume, interchangeable between vendors, and identical in what they oblige you to find.
Matching and threshold tuning, fuzzy and transliteration handling, risk-scored alert triage, human review, escalation, SLA, audit trail.
A hit lands inside a risk model that decides accept, escalate or decline, not in a spreadsheet someone reviews when they get to it.
Screening everyone is expensive and screening nobody is indefensible. The first question in every engagement is which part of your book carries the obligation.
Sanctions and PEP screening at origination is standard practice for any lending activity, not a sector-specific requirement. Screening a borrower before extending credit, and re-screening on an ongoing basis, is the baseline expectation wherever a loan or financing product exists. This is the clear case: yes, recommended.
For a broad consumer base with no credit exposure, whether screening is required depends on facts specific to you: which segments carry meaningful financial exposure (large contracts, device financing, business accounts), and what your own risk policy or regulator expects. We would usually scope this as a defined subset, not the full base.
Sanctions, PEP and adverse media orchestrated through one matching and risk layer, not three separate lookups.
UN, EU, OFAC, HMT + national and regional
Global and domestic, relatives and close associates
Negative news and enforcement action
The taxonomy is not a coverage boast, it is the scoping control. Because every adverse record carries its category, "which risks are we screening for" becomes a setting your risk team owns rather than an all-or-nothing switch. Screen tax and customs violations but not disciplinary actions, pre-conviction fraud but not pre-conviction everything. See all 66 categories ↓
Your chosen sourcing model · configurable thresholds · explainable, auditable match decisions.
Auto-cleared, on file
Analyst queue, SLA-bound
Escalated, decline on record
The taxonomy behind every hit: sanctions and watchlist categories, financial crime, and the adverse-media risk indicators the engine classifies against.
66 risk categories mapped today. Coverage grows with the underlying source, not with a rebuild here.
Match quality looks like a feature until you turn monitoring on. Then it is the running cost of the whole programme.
At onboarding you look at it, dismiss it, and move on. That is the version of false positives everyone budgets for, and it is the cheap one.
Every cycle. For every subject. The rate does not add up, it multiplies by how often you re-screen and by how many people are on your book. Nothing about the match got worse. You simply meet it again, and again.
Weaker matching and a monthly full-price re-screen are the same decision seen from two sides. You pay the full screening rate every month to regenerate the same false positives your analysts dismissed last month.
Monthly monitoring, at a 2.0% and a 0.7% alert rate. The rates are a worked example, not measured figures. Your own numbers depend on your book, your thresholds and which categories you scope in.
| Month | Weaker matching | Stronger matching | Difference |
|---|---|---|---|
| 0 (onboarding only) | 20 | 7 | 13 |
| 12 | 240 | 84 | 156 |
| 24 | 480 | 168 | 312 |
| 36 | 720 | 252 | 468 |
A change to a record can arrive graded by how material it is: a subject appearing on a sanctions list at one end, a corrected middle initial at the other. Where the line falls, and what happens either side of it, is the workflow, and that is the part you are actually buying. Set it too low and your analysts read spelling corrections. Set it too high and you find out what you missed from someone else.
Whether that grading arrives with the data at all is one of the real differences between the sourcing models, not a detail. One of the three grades changes explicitly. One handles the noise its own way. One does not separate a material change from a cosmetic one, which is why its monthly re-screen returns the whole match set every time. Compare the three ↓
A confirmed sanctions match doesn't add points to a score. It overrides it outright and forces the highest risk tier, regardless of every other factor, and it is demoable live today in the Poros risk engine.
Fuzzy match, transliteration and name-variant logic, with thresholds a bank can tune to its own risk appetite.
Risk-scored alert prioritisation so reviewers work the alerts that matter first.
Approve, review or reject routing, with escalation paths and an SLA on resolution.
Every decision, escalation and review inside one case file and audit trail.
Send a name, get a scored, reviewed result back. No onboarding platform required.
Periodic and trigger-based re-screening, not a one-time onboarding gate.
Three sourcing models behind one interface. Change the model without rebuilding the screening workflow around it.
Mechanical, third-party-sourced screening sits entirely outside the EU AI Act.
One screening call, two audiences. What the developer integrates and what the compliance team sits in front of are different problems, and pretending otherwise is how screening projects stall after go-live.
Where the held cases land. Scored, categorised, with the record and the decision trail attached, so a reviewer can clear or escalate without leaving the case.
Illustration, not a screenshot
Both the Expert and World Check models come with their own case and list management interfaces, and they are good ones. Teams that already work natively in them can keep doing so, with our engine handling the screening call.
Everything on this page so far has been about false positives, because those are the ones you can see. The other kind of miss produces no alert, no queue entry and no work. Nothing tells you it happened. That is the entire problem with it.
Lands in the queue, takes an analyst's time, gets dismissed. Expensive, measurable, and on somebody's dashboard by Friday.
The name is never matched, so no alert is raised and no record of the near-miss exists. You find out when a regulator, a correspondent bank or a journalist finds out.
Most misses are not exotic. They are the same person written the way a different system, a different alphabet or a different culture writes them.
Illustrative examples of name variance, not screening results. Matching in the original script matters because a subject is recorded the way their own jurisdiction records them, and the transliteration your onboarding form captured is only one of several defensible spellings. Getting this wrong lowers your alert count, which is exactly why it is easy to mistake for good performance.
The right answer depends on your volume, your tolerance for false positives, and whether you need an immediate result or can wait for an overnight run. Everything above (matching, triage, workflow, audit trail) applies to all three.
Lowest cost per check
Cheapest per check by a wide margin. Sanctions and PEP only, and no real monitoring: the same name is re-screened monthly at full screening price each time. Name matching is the weakest of the three, and changes to a record are not graded by materiality at all.
Our experience: it finds what it is told to find, but loose matching produces noticeably more false positives, and with nothing separating a material change from a cosmetic one, every monthly re-screen hands you the whole match set again.
Priced on request
Our default recommendation
Screening and monitoring priced separately, with a year of monitoring costing roughly two screenings. Strong false-positive reduction with its own built-in noise handling, list management and maintenance included, fully configurable via API, adverse media a small optional surcharge. PEP coverage runs down to level 4.
Our experience: the best of the three at keeping analyst workload down. Source snippets stay in the original language and additionally carry an English translation and summary, so nothing is lost or gated behind the source text when a decision has to be defended.
Priced below, our default recommendation
LSEG, flat licence band
One price per person, no screening/monitoring split: check once a year or a hundred times for the same cost. Covers sanctions, crime and adverse media, plus ownership-derived indirect sanctions (OFAC 50% rule) the others do not carry. Batch upload, ongoing screening and adverse media are separately licensed modules.
Our experience: stronger crime lists and better close-relative coverage than the premium alternative, weaker adverse media, and no PEP level 4. It grades record changes by materiality explicitly, which is the cleanest control over monitoring alert volume of the three.
Priced on request, flat licence band
Budget and World Check Co-sell are quoted against your actual volume. Tell us roughly how many checks a year and whether you need results in real time, and we will come back with both.
The rates below are the Expert model, our default recommendation and the one most clients end up on. Budget and World Check Co-sell are priced on request: both depend on annual volume and, in World Check's case, on a committed licence band rather than a per-check rate.
| Expert model, list price | Price | Setup |
|---|---|---|
| Sanctions & PEP screening (core) | €0.24 / check | none |
| Adverse media (add-on) | +€0.04 / check | n/a |
| Ongoing monitoring, sanctions & PEP | €0.48 / subject / year | n/a |
| Ongoing monitoring, adverse media (add-on) | +€0.08 / subject / year | n/a |
Either way, the conversation starts the same place: what sources, what thresholds, what review workflow and what evidence trail your risk and compliance teams need to sign off on.
