Workspace/OpenSanctions
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OpenSanctions

Open data and screening infrastructure

OpenSanctions aggregates entity and watchlist data and exposes matching through a hosted API or the self-hosted yente service. It is a data and matching foundation, not a complete compliance department workflow. Commercial use requires the appropriate data license even when the software is self-hosted.

Our assessment

A transparent screening foundation. Budget for the operating system around it.

Best fit and limitations

A strong infrastructure candidate for teams able to build or already operating screening review, case management, and audit controls. Transparency and deployment control are the main evaluation advantages.

  • Open-source software does not make commercial data use free.
  • No complete native case management, report filing, or AML transaction monitoring is established here.
  • Do not assume broad commercial adverse-media coverage from the presence of crime-related public records.

Tools 5

OpenSanctions datasetsRisk data
+
  • Select individual sources or combined collections
  • Inspect entities and source-linked properties
Source 1
/match APIEntity screening
+
  • Query by example with names and additional identifiers
  • Return ranked candidate matches for review
Source 1
yenteSelf-hosted matching
+
  • Run the matching API on your own infrastructure
  • Use selected OpenSanctions and internal data
Source 2
Matching configurationPrecision and recall control
+
  • Choose algorithms and feature weights
  • Separate candidate retrieval from match scoring
Source 3
/search APIAnalyst search
+
  • Full-text exploration of entities
  • The provider explicitly recommends /match for screening
Source 4

AI capabilities

Transparent matching, not an AI investigator

The recommended logic-v2 matcher uses deterministic rules, culturally aware name matching, and identifier checks. It returns candidates and similarity scores; it is not an AML investigator or a predictive fraud model.

Find candidate entitiesScore attribute similaritySupport source-level investigation
What to validate

Version datasets and algorithm settings. Validate thresholds and keep analyst decisions independent from raw similarity scores.

Source 3

Implementation

Integration checklist
  • Use /match for screening and /search for human exploration.
  • Implement rescreening, evidence snapshots, decisions, audit logs, and update monitoring.
  • For self-hosting, operate data refresh, indexing, backup, monitoring, and capacity.
Commercial scope

Commercial data license required. Hosted API and self-hosted operation have different costs; verify current pricing and data rights directly.

Estimate total cost
Questions for the demo
  1. Which datasets and refresh schedules satisfy our specific screening scope?
  2. What commercial rights cover hosted, self-hosted, and derived use?
  3. How will we prove a past decision against the exact data and matching version?

Sources 5

Reviewed September 17, 2026. Product claims come from public sources. Fit, limits, and evaluation questions are our analysis. This is not a hands-on performance test. Methodology