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.

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?

Engineering

Your systemInputs & context
OpenSanctionsChecks & signals
Your controlsDecision & review
Illustrative integration boundary. Confirm the actual interfaces and decision authority.
Inputs
Query-by-example person or organization attributes · Entity properties, selected algorithm, feature weights, and threshold
Outputs
Ranked candidate entities from the selected data collection · Ranked candidate entities and matching scores
Webhooks
Not verified in public documentation.
Decision timing
No measured latency or contracted response time verified.
Deployment
Hosted API · On-premises
Dependencies
Commercial data license for business use · Explicit dataset, algorithm, and threshold policy · Pin the algorithm when changes in matching behavior require validation · Business use requires a commercial license unless the provider grants an applicable exemption
Verified details 10
  • Inputs

    Query-by-example person or organization attributes

    Source Checked 2026-09-18
  • Outputs

    Ranked candidate entities from the selected data collection

    Source Checked 2026-09-18
  • Deployment

    Hosted API

    Source Checked 2026-09-18
  • Deployment

    On-premises

    Source Checked 2026-09-18
  • Dependency

    Commercial data license for business use

    Source Checked 2026-09-18
  • Inputs

    Entity properties, selected algorithm, feature weights, and threshold

    Source Checked 2026-09-18
  • Outputs

    Ranked candidate entities and matching scores

    Source Checked 2026-09-18
  • Dependency

    Explicit dataset, algorithm, and threshold policy

    Source Checked 2026-09-18
  • Dependency

    Pin the algorithm when changes in matching behavior require validation

    Source Checked 2026-09-18
  • Dependency

    Business use requires a commercial license unless the provider grants an applicable exemption

    Source Checked 2026-09-18
Vendor example

Published vendor example. Confirm the current version and required credentials.

json
{
  "schema": "Person",
  "properties": {
    "firstName": [
      "Arkadii"
    ],
    "fatherName": [
      "Romanovich"
    ],
    "lastName": [
      "Rotenberg",
      "Ротенберг"
    ],
    "birthDate": [
      "1951"
    ],
    "nationality": [
      "Russia"
    ]
  }
}
Example source
Integration limits
  • Published vendor payload example, linked to its source. It is not a complete integration or a tested production request.
  • Empty country, deployment, or provider lists mean not verified in this review. A documented country refers to the specific product noted in its source, not universal platform coverage.
  • The matcher supplies evidence for a screening process. The client must implement review, rescreening, audit retention, and operational decisions.
  • The vendor example is the published entity object, not a complete HTTP request. The source's trailing comma was removed to make valid JSON; field values are unchanged.
  • Pin an algorithm for reproducible behavior. Selecting best can change the model and scores as the publisher updates its default.
  • The recommended logic-v2 matcher and older regression algorithms have different behavior. Do not interpret a score as a calibrated sanction probability.
  • Open-source hosting software and licensed data are separate rights.

Sources 5

Source review dates are shown above. Product claims come from public sources. Fit, limits, and evaluation questions are our analysis. This is not a hands-on performance test. Methodology · Changelog