OFAC Sanctions Screener - Compliance Check

Screen companies, individuals, vessels, and aircraft against the US Treasury OFAC SDN sanctions list with intelligent fuzzy matching. Optionally cross-reference against 40+ international sanctions lists via OpenSanctions (EU, UN, UK, and more).

Built for compliance teams, fintech platforms, and AI agents that need real-time sanctions screening without maintaining their own sanctions infrastructure. Enterprise tools charge $5,000-$100,000+/year -- this does the same job at $0.01 per entity.

---

How It Works

flowchart LR
    A["Entity Names"] --> B["Download SDN List\n(US Treasury XML)"]
    B --> C["Fuzzy Match\n(Fuse.js)"]
    C --> D{OpenSanctions\nEnabled?}
    D -- Yes --> E["OpenSanctions API\n(40+ Lists)"]
    D -- No --> F["Risk Report"]
    E --> F
    style A fill:#4A90D9,color:#fff
    style B fill:#D94A4A,color:#fff
    style C fill:#D98A4A,color:#fff
    style E fill:#8A4AD9,color:#fff
    style F fill:#4AD97A,color:#fff

1. Input your entity names (person, company, vessel, or aircraft)
2. Live SDN data is downloaded directly from the US Treasury (treasury.gov) -- 18,000+ sanctioned entities
3. Fuzzy matching via Fuse.js catches misspellings, transliterations, and aliases
4. OpenSanctions (optional) extends coverage to EU, UN, UK, and 40+ other lists
5. Risk report returned with match scores, programs, and sanction details

---

Architecture

graph TB
    subgraph Input
        Q["Entity Names Array"]
        T["Match Threshold\n(40-100)"]
        ET["Entity Type Filter"]
        OPT["Options\n(aliases, OpenSanctions)"]
    end

    subgraph "OFAC SDN Pipeline"
        DL["Download SDN XML\n(treasury.gov/ofac)"]
        PARSE["fast-xml-parser\nXML to JSON"]
        STRIP["Strip Business Suffixes\n(Inc, LLC, Corp)"]
        INDEX["Build Fuse.js\nSearch Index"]
        MATCH["Fuzzy Match\nAll Entities"]
    end

    subgraph "OpenSanctions (Optional)"
        OS_API["OpenSanctions API\n(EU, UN, UK, 40+)"]
        OS_MERGE["Merge & Deduplicate\nResults"]
    end

    subgraph "Output"
        SCORE["Confidence Scores\n(0-100)"]
        RISK["Risk Level\nCRITICAL / HIGH / MEDIUM / LOW / CLEAR"]
        PROGRAMS["Sanctioned Programs\n& Entity Details"]
    end

    Q --> DL
    T --> INDEX
    ET --> MATCH
    OPT --> MATCH
    DL --> PARSE --> STRIP --> INDEX --> MATCH
    MATCH --> OS_API --> OS_MERGE --> SCORE
    MATCH --> SCORE
    SCORE --> RISK --> PROGRAMS

    style DL fill:#D94A4A,color:#fff
    style PARSE fill:#D98A4A,color:#fff
    style INDEX fill:#4A90D9,color:#fff
    style MATCH fill:#4AD97A,color:#fff
    style OS_API fill:#8A4AD9,color:#fff
    style RISK fill:#D94A6A,color:#fff

---

AI Agent Integration

Integrate sanctions screening directly into your AI agent workflows, compliance pipelines, or payment systems. Compatible with the Apify MCP Server so AI agents (Claude, GPT, CrewAI, LangChain) can discover and run it automatically.

JavaScript / Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('george.the.developer/ofac-sanctions-screener').call({
    queries: ['Sberbank of Russia', 'Kim Jong Un', 'Rosneft Oil Company'],
    matchThreshold: 70,
    entityType: 'all',
    includeOpenSanctions: true,
    maxMatchesPerQuery: 5,
    includeAliases: true,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();

for (const item of items) {
    console.log(`${item.queryName}: ${item.riskLevel} (${item.matchConfidence}% confidence)`);
}

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("george.the.developer/ofac-sanctions-screener").call(run_input={
    "queries": ["Sberbank of Russia", "Kim Jong Un", "Rosneft Oil Company"],
    "matchThreshold": 70,
    "entityType": "all",
    "includeOpenSanctions": True,
    "maxMatchesPerQuery": 5,
    "includeAliases": True,
})

items = client.dataset(run["defaultDatasetId"]).list_items().items
for item in items:
    print(f"{item['queryName']}: {item['riskLevel']} ({item['matchConfidence']}% confidence)")

cURL

# Start the screening run
curl -X POST \
  "https://api.apify.com/v2/acts/george.the.developer~ofac-sanctions-screener/runs?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "queries": ["Sberbank of Russia", "Kim Jong Un", "Bank Melli Iran"],
    "matchThreshold": 70,
    "entityType": "all",
    "includeOpenSanctions": false,
    "maxMatchesPerQuery": 5,
    "includeAliases": true
  }'

# Retrieve results from the dataset
curl "https://api.apify.com/v2/datasets/DATASET_ID/items?token=YOUR_API_TOKEN"

---

Input Schema

erDiagram
    INPUT {
        string_array queries "Entity names to screen (required)"
        integer matchThreshold "40-100, default 70"
        string entityType "all | individual | entity | vessel | aircraft"
        boolean includeOpenSanctions "Cross-ref 40+ international lists"
        integer maxMatchesPerQuery "1-25, default 5"
        boolean includeAliases "Include known aliases in matching"
    }

Parameter	Type	Required	Default	Description
queries	string[]	Yes	--	Array of entity names to screen (company, person, vessel, aircraft)
matchThreshold	integer	No	70	Fuzzy match sensitivity (40 = loose, 100 = exact). Lower values catch more transliterations.
entityType	string	No	"all"	Filter by entity type: all, individual, entity, vessel, aircraft
includeOpenSanctions	boolean	No	false	Cross-reference against 40+ international sanctions lists (EU, UN, UK, etc.)
maxMatchesPerQuery	integer	No	5	Maximum matches returned per query (1-25)
includeAliases	boolean	No	true	Include known aliases and alternate names in matching

Example Input

{
    "queries": [
        "Sberbank of Russia",
        "Kim Jong Un",
        "Iranian Revolutionary Guard",
        "Rosneft Oil Company",
        "Bank of Syria"
    ],
    "matchThreshold": 70,
    "entityType": "all",
    "includeOpenSanctions": true,
    "maxMatchesPerQuery": 5,
    "includeAliases": true
}

---

Output Schema

Each entity in the output contains match results with confidence scores, program details, and risk indicators.

erDiagram
    RESULT {
        string queryName "Original search term"
        string matchedName "Sanctioned entity name"
        integer matchConfidence "Similarity score 0-100"
        string riskLevel "CRITICAL | HIGH | MEDIUM | LOW | CLEAR"
        string sanctionsList "OFAC SDN or OpenSanctions"
        string entityType "individual | entity | vessel | aircraft"
        string_array programs "Sanctions program codes"
        string_array aliases "Known alternative names"
        string source "Data source identifier"
    }
    RESULT ||--o{ ADDRESS : has
    RESULT ||--o{ ID_DOCUMENT : has
    ADDRESS {
        string city "City name"
        string country "Country name"
    }
    ID_DOCUMENT {
        string type "Passport, Tax ID, etc"
        string number "Document number"
    }

Match Found (Sanctioned Entity)

{
    "queryName": "Bank Melli Iran",
    "matchedName": "BANK MELLI IRAN",
    "matchConfidence": 100,
    "sanctionsList": "OFAC SDN",
    "entityType": "entity",
    "sdnUid": 25578,
    "programs": ["IFSR", "IRAN", "SDGT"],
    "aliases": ["BANK MELLI", "MELLI BANK", "NATIONAL BANK OF IRAN", "BMI"],
    "addresses": [{ "city": "Tehran", "country": "Iran" }],
    "riskLevel": "CRITICAL",
    "sdnListDate": "03/09/2026",
    "screenedAt": "2026-03-11T12:00:00.000Z",
    "source": "US Treasury OFAC SDN List"
}

No Match (Clear Entity)

{
    "queryName": "Apple Inc",
    "matchedName": null,
    "matchConfidence": 0,
    "riskLevel": "CLEAR",
    "result": "NO_MATCH",
    "message": "No sanctions matches found for \"Apple Inc\" above 70% confidence threshold.",
    "source": "US Treasury OFAC SDN List"
}

---

Use Cases

mindmap
  root((OFAC\nScreening))
    KYC
      Customer Onboarding
      Identity Verification
      Ongoing Monitoring
    AML
      Transaction Screening
      Wire Transfer Checks
      Suspicious Activity Reports
    Payments
      Cross-border Payments
      Crypto Compliance
      Payment Gateway Checks
    Trade Compliance
      Export Controls
      Shipping & Vessel Screening
      Freight Forwarder Checks
    Due Diligence
      M&A Target Screening
      Vendor & Supplier Vetting
      Investor Background Checks

Use Case	Who	Why
KYC/AML Onboarding	Banks, fintech, payment processors	Screen customers at onboarding. Batch-screen hundreds in one run.
Import/Export Compliance	Logistics, freight, trade companies	Screen suppliers, buyers, and freight forwarders. OFAC penalties reach $20M per violation.
Due Diligence	Law firms, PE/VC, corporate dev	Verify partners, investors, or acquisition targets before signing.
Supply Chain Monitoring	Enterprise, manufacturing	Monitor your entire supplier network. Run daily to catch new designations.
AI Agent Pipelines	Developers, automation teams	Automated compliance checks embedded in LLM-powered workflows via MCP.
Crypto Compliance	Exchanges, DeFi platforms	Screen wallets, counterparties, and entities for OFAC compliance.

---

High-Risk Programs Tracked

Program Code	Target	Description
IRAN	Iran	Comprehensive Iranian sanctions
IFSR	Iran	Iran Financial Sanctions Regulations
RUSSIA-EO14024	Russia	Russia-related sanctions (Executive Order 14024)
SYRIA	Syria	Syrian sanctions
DPRK	North Korea	Democratic People's Republic of Korea sanctions
UKRAINE-EO13661	Russia/Ukraine	Ukraine/Russia-related sanctions (EO 13661)

---

Pricing

$0.01 per entity screened via Apify's pay-per-event model.

Volume	Cost	Per Entity
10 entities	$0.10	$0.01
100 entities	$1.00	$0.01
1,000 entities	$10.00	$0.01
10,000 entities	$100.00	$0.01

No monthly fees. No minimum commitment. Pay only for what you screen.

Platform costs (Apify compute + storage) are charged separately at negligible rates for this actor.

---

Integrations

graph LR
    subgraph "Data Sources"
        OFAC["US Treasury\nOFAC SDN\n(18,000+ entities)"]
        OS["OpenSanctions\n40+ International\nLists"]
    end

    subgraph "Sanctions Screener"
        ACTOR(("george.the.developer/\nofac-sanctions-screener"))
    end

    subgraph "Connect Via"
        API["REST API"]
        JS["JavaScript SDK"]
        PY["Python SDK"]
        MCP["MCP Server\n(AI Agents)"]
        WH["Webhooks"]
        ZAP["Zapier"]
        MAKE["Make"]
    end

    subgraph "Your Systems"
        CRM["CRM / KYC\nPlatform"]
        PAY["Payment\nGateway"]
        ERP["ERP / Trade\nCompliance"]
        AI["AI Agents\n(Claude, GPT)"]
        SLACK["Slack / Teams\nAlerts"]
    end

    OFAC --> ACTOR
    OS --> ACTOR
    ACTOR --> API
    ACTOR --> JS
    ACTOR --> PY
    ACTOR --> MCP
    ACTOR --> WH
    ACTOR --> ZAP
    ACTOR --> MAKE
    API --> CRM
    JS --> PAY
    PY --> AI
    MCP --> AI
    WH --> ERP
    ZAP --> SLACK
    MAKE --> CRM

    style ACTOR fill:#4A90D9,color:#fff,stroke:#2A70B9
    style OFAC fill:#D94A4A,color:#fff
    style OS fill:#8A4AD9,color:#fff

---

FAQ

---

Data Sources

• OFAC SDN List -- Official US Treasury Specially Designated Nationals list: treasury.gov/ofac/downloads/sdn.xml
• OpenSanctions (optional) -- Aggregated international sanctions from EU, UN, UK, and 40+ jurisdictions: opensanctions.org

---

Support

Found a bug or have a feature request? Reach out on the Apify platform or open an issue.