What is sanctions screening?
Sanctions screening compares people and organizations with official restricted-party lists at onboarding and before funds move. Naiza screens 1,100+ global sources in one request, returns classified results with source details and match evidence, and connects potential matches to investigation cases.
Updated 5 October 2026
How sanctions screening differs from generic AML screening
Sanctions lists are issued by governments and international bodies. A true sanctions hit usually has a higher urgency than a PEP or adverse-media signal. Teams still need match context: which list, which aliases, and which identifiers supported the result.
Where it sits in a product flow
Most teams screen at customer onboarding and again on payment counterparties. Continuous monitoring matters because lists change. The product should store the screening identifier so operations can reconstruct why a hold or review happened.
How Naiza applies sanctions screening
Naiza screens global sanctions, PEP, and watchlist data in one request across 1,100+ sources. Source details, aliases, confidence scores, and screening identifiers support investigation and case review.
How a sanctions screening check works
Behind a single API call, a screening engine goes through the same steps every time:
- Collect the identifiers you have: full legal name, date of birth, nationality, and for companies the registration country and number.
- Normalize the name: remove titles and punctuation, split it into parts, and generate spelling and transliteration variants.
- Compare it with each list using exact, fuzzy, and phonetic matching, including the aliases recorded on each entry.
- Score every candidate on name similarity and on whether the supporting identifiers agree.
- Return a decision: clear, review, or confirmed, with the matched entry and its source list.
- Keep the screening ID and the evidence so the decision can be reconstructed later.
- Re-screen automatically when the lists change.
The main sanctions lists
Most screening programs cover these lists at a minimum. Each one is published and updated by its issuing authority.
| List | Issued by | Notes |
|---|---|---|
| UN Security Council Consolidated List | United Nations Security Council | The baseline. Member states apply these designations in their own law. |
| Specially Designated Nationals (SDN) and other OFAC lists | US Treasury, Office of Foreign Assets Control | Relevant to anyone touching US dollars or US-linked banks and card schemes. |
| EU consolidated financial sanctions list | European Union | Applies to EU businesses and is expected by European partners. |
| UK sanctions list | UK government | Applies to UK businesses and UK-linked banking partners. |
| National and regional designations | Individual governments, including Saudi Arabia and other GCC states | Local names that do not always appear on the international lists. |
Sanctions, PEP, and adverse media compared
All three run in the same screening request, but each answers a different question and leads to a different action.
| Check | Question it answers | Typical action on a match |
|---|---|---|
| Sanctions | Is this party restricted by a government or the UN? | Hold and escalate. A confirmed match ends the relationship or the payment. |
| PEP | Does this person hold, or are they close to, a prominent public role? | Enhanced due diligence and closer monitoring. Not an automatic block. |
| Adverse media | Is there credible negative news linking them to financial crime? | Review the source and relevance, then decide on due diligence. |
Why false positives happen, and how to cut them
Most sanctions alerts are not real matches. A screening program that alerts on everything is as risky as one that alerts on nothing, because analysts start clearing alerts without reading them.
- Common names: a popular name matches dozens of entries. Send date of birth and nationality so they can rule candidates out.
- Partial names: screening only a first and last name throws away the father's and grandfather's names that would separate two people.
- Transliteration: matching that cannot connect Arabic script to its Latin spellings either misses matches or compensates by matching too loosely.
- Thresholds set once and never revisited: review your true-match rate monthly and tune from evidence.
Sanctions screening in Saudi Arabia
Saudi businesses screen three layers: UN Security Council designations, Saudi and regional designations, and the foreign lists that apply through dollar payments and international partners. The guide to sanctions lists for Saudi businesses covers each layer and how to handle a possible match.
Frequently asked questions
Answers about screening, risk signals, and Naiza integration.
What is a sanctions screening API?
A sanctions screening API accepts a name or entity and returns structured matches against restricted-party lists so your application can allow, review, or stop a workflow.
Is OFAC screening the same as sanctions screening?
OFAC screening checks U.S. sanctions. Broader sanctions screening covers restricted-party lists from other jurisdictions. Naiza combines global sanctions, PEP, and watchlist screening across 1,100+ sources in one workflow.
Can sanctions screening run in real time?
Yes. Onboarding and payment flows typically need a synchronous result. Naiza is designed for that request-and-decide pattern, with review routing when the match is uncertain.
What happens when a customer matches a sanctions list?
The product holds the account or payment and an analyst compares the customer's identifiers with the list entry. If they rule the match out, it is cleared and the reason recorded. If they agree, the case goes to compliance and the relationship or payment stops.
How often should sanctions screening run?
At onboarding, before payments to new counterparties, on changes to customer details, and every time the lists update. Automatic re-screening on list updates is safer than a fixed monthly batch.
What is fuzzy matching in sanctions screening?
Fuzzy matching finds names that are similar but not identical, such as spelling variants, typos, and transliterations. It catches true matches that exact matching misses, and supporting identifiers then filter out namesakes.