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⇱ US Consolidated Sanctions Screener β€” Name Matching Β· Apify


πŸ‘ OFAC SDN Sanctions Screener β€” Name Matching avatar

OFAC SDN Sanctions Screener β€” Name Matching

Pricing

$20.00 / 1,000 sdn match returneds

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OFAC SDN Sanctions Screener β€” Name Matching

Screen names against OFAC SDN (Specially Designated Nationals) β€” the primary US sanctions list. Joins sdn.csv + alt.csv + add.csv for full names, aliases, addresses. Returns matches with similarity score, programs, type, addresses. Daily-refreshed from treasury.gov. No auth.

Pricing

$20.00 / 1,000 sdn match returneds

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0.0

(0)

Developer

πŸ‘ vΓΈiddo

vΓΈiddo

Maintained by Community

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2

Total users

1

Monthly active users

17 days ago

Last modified

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Screen any list of names against the OFAC SDN list β€” Specially Designated Nationals and Blocked Persons, the primary US sanctions list maintained by Treasury. ~13,000 entities. Joins sdn.csv + alt.csv + add.csv for full names, aliases, addresses.

Built for KYC / compliance / AML / sanctions screening workflows. No login, no API key β€” pulls fresh files from treasury.gov on each run.

Two modes

screen (default) β€” name matching

{
"mode":"screen",
"names":["John Smith","Acme Trading Co"],
"minScore":60
}

Output: one row per match per input name. Includes match score (0-100) for downstream thresholding.

dump β€” full list export

{"mode":"dump"}

Output: one row per SDN entity. Use for ETL or building your own screening logic.

Inputs

inputdefaultnotes
modescreenscreen or dump.
names[]Required when mode=screen.
minScore60Drop matches below this. 100 = exact only.
typesFilterallRestrict by entity type: Individual, Entity, Vessel, Aircraft.
programsFilterallRestrict to specific OFAC programs: IRAN, RUSSIA-EO14024, SDGT, NARCOTICS, CUBA, etc.

Output schema

fieldexample
inputNameJohn Smith (screen mode only)
matchScore82 (screen mode only)
matchKindalt_name_substring
matchedNameJohnny Smith (screen mode only)
entityNumber12345
namecanonical SDN name
typeIndividual
programs["IRAN", "SDGT"]
title(when present)
altNames[{"type": "aka", "name": "..."}, ...]
addresses[{"address": "...", "cityState": "...", "country": "..."}]
remarks(when present)
vesselTypeTanker (when type=Vessel)
callSign(when applicable)
tonnage(when applicable)
vesselFlag(when applicable)
vesselOwner(when applicable)

Scoring

Deterministic, no ML:

  • Exact normalized name β†’ 100
  • Exact alt-name β†’ 95
  • Input is substring of name β†’ 90
  • Name is substring of input β†’ 80
  • Token overlap (Jaccard) β†’ up to 75

Normalization: lowercase, strip punctuation, collapse whitespace.

What it doesn't do

  • No EU / UN / UK / Canada / OFSI lists β€” OFAC SDN only. Other US lists (SSI, Entity List, MEU, ...) and EU/UN will be separate actors.
  • No fuzzy / phonetic / NLP matching β€” deterministic scoring only.
  • No "false positive flag" β€” that's your analyst's call.

Maintained by

vΓΈiddo studio β€” small independent shop.

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