AML Entity Screening

Comprehensive Anti-Money Laundering and Counter-Terrorism Financing (AML/CFT) screening engine that runs 13 sub-actors in parallel to check any person or company against OFAC, OpenSanctions, Interpol, FBI, FARA foreign agent registrations, FEC campaign finance records, OpenCorporates, GLEIF LEI, FDIC, SEC EDGAR, CFPB complaints, and nonprofit registries. Produces a scored AML risk classification across five dimensions with explicit SAR filing guidance and compliance recommendations.

Features

• Screens entities against OFAC SDN list, OpenSanctions (40+ international lists), Interpol Red Notices, and FBI Most Wanted simultaneously
• Detects Politically Exposed Persons (PEPs) through FARA foreign agent registrations and FEC campaign finance records
• Identifies shell company indicators by analyzing corporate registration patterns, nominee directors, and secrecy jurisdiction registrations
• Verifies financial institution legitimacy through FDIC insurance verification
• Produces four-tier AML classification (LOW / MEDIUM / HIGH / PROHIBITED) with automatic SAR filing recommendations
• Computes a Proximity to Crime convergence score measuring how many independent adverse signal categories overlap on a single entity

Use Cases

• BSA/AML Compliance Officers: Screen customers and counterparties for AML onboarding. Get a structured risk tier with SAR filing guidance and dimensional scoring that maps directly to your compliance framework.
• Financial Institutions: Automate batch screening of new account applicants against sanctions, PEP, and adverse media databases. Direct sanctions matches automatically trigger PROHIBITED classification.
• Legal Due Diligence Teams: Run pre-engagement screening on new clients to identify sanctions exposure, shell company indicators, foreign agent registrations, and political connections.
• Fintech KYC Pipelines: Integrate via API for automated entity screening at scale. The structured JSON output integrates directly into decision engines and case management systems.
• Audit and Investigation Teams: Generate auditable screening reports that document exactly which databases were checked, what was found, and what the computed risk tier is.

How to Use

1. Click Try for free on this page
2. Enter the entity name to screen (e.g., "Viktor Bout" or "Huawei Technologies")
3. Select the entity type (person, company, or any) and optionally specify a country
4. Click Start and wait for the run to finish
5. Download results from the Dataset tab in JSON, CSV, or Excel

Input Parameters

Parameter	Type	Required	Description
entityName	string	Yes	Name of the person or company to screen for AML risks
entityType	string	No	Type of entity: "person", "company", or "any" (default: "any"). Selecting "person" skips corporate-specific checks.
country	string	No	Optional ISO country code (e.g., "US", "GB") to narrow search results

Output Example

{
  "entity": "Viktor Bout",
  "entityType": "person",
  "country": "RU",
  "amlRiskTier": "PROHIBITED",
  "amlRiskScore": 85,
  "directSanctionsMatch": true,
  "sarRequired": true,
  "recommendation": "TRANSACTION MUST BE BLOCKED. File Suspicious Activity Report (SAR) within 30 days.",
  "scoringDimensions": {
    "sanctionsWatchlist": { "score": 30, "max": 35, "findings": ["2 EXACT sanctions match(es) — PROHIBITED."] },
    "corporateTransparency": { "score": 12, "max": 25, "findings": ["No corporate registration found"] },
    "politicalExposure": { "score": 16, "max": 20, "findings": ["Registered foreign agent under FARA"] },
    "financialRegulatory": { "score": 4, "max": 10, "findings": ["80% insider transactions are sales"] },
    "proximityCrime": { "score": 10, "max": 10, "findings": ["CRITICAL CONVERGENCE: 4 adverse signal categories"] }
  },
  "sanctions": { "totalHits": 5, "exactMatches": 2, "blocked": true },
  "politicalExposure": { "pepClassification": "POLITICALLY EXPOSED", "fara": { "isForeignAgent": true } },
  "shellCompanyAnalysis": { "shellRisk": "HIGH", "shellScore": 75 },
  "proximityCrime": { "convergenceScore": 68, "convergenceLevel": "CRITICAL" }
}

Scoring Model

The AML Risk Score runs from 0 to 100 across five dimensions. A direct sanctions match automatically triggers PROHIBITED status regardless of the numeric score.

• Sanctions and Watchlist Exposure (0-35 points): Exact OFAC/OpenSanctions matches score 30 points. Fuzzy matches score 5 points each (up to 15). Interpol Red Notices and FBI Most Wanted hits each add 15 points.
• Corporate Transparency (0-25 points): No corporate registration adds 12 points. Shell company indicators (nominee directors, bearer shares, registered agents) add 8. Secrecy jurisdiction registration adds 6. Dissolved or inactive status adds 5. No LEI adds 4.
• Political Exposure / PEP (0-20 points): FARA foreign agent registration adds 12 points. Multiple FARA registrations add 4 more. FEC campaign donations exceeding $100,000 add 10 points.
• Financial Regulatory Standing (0-10 points): SEC enforcement filings add 3. Insider selling patterns exceeding 80% of trades add 4. CFPB complaints above 50 add 3. Inactive FDIC institution adds 5.
• Proximity to Crime (0-10 points): Counts how many distinct adverse signal categories (sanctions, Interpol, FBI, foreign agent, consumer complaints, shell indicators) converge. Four or more active categories score the maximum 10 points.

AML Risk Tiers: LOW (0-20), MEDIUM (21-45), HIGH (46-70), PROHIBITED (71-100 or any direct sanctions match).

How Much Does It Cost?

Each run uses approximately $0.10-$0.15 in platform credits. On the Apify free tier you can run approximately 30-50 screenings per month. Screening persons is slightly cheaper as corporate-specific actors are skipped.

Programmatic Access

Python

from apify_client import ApifyClient
client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("ryanclinton/aml-entity-screening").call(run_input={
    "entityName": "Huawei Technologies",
    "entityType": "company",
    "country": "CN"
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript

import { ApifyClient } from "apify-client";
const client = new ApifyClient({ token: "YOUR_API_TOKEN" });
const run = await client.actor("ryanclinton/aml-entity-screening").call({
    entityName: "Huawei Technologies",
    entityType: "company",
    country: "CN"
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

FAQ

What happens when a direct sanctions match is found? Any exact OFAC or OpenSanctions match (confidence 95% or above) automatically triggers PROHIBITED status, regardless of the total numeric score. The recommendation instructs you to block the transaction and file a SAR within 30 days.

What is the Proximity to Crime convergence score? It measures how many independent adverse signal categories overlap on a single entity. A person who appears on sanctions lists AND has Interpol notices AND has foreign agent registrations has high convergence, which is a stronger indicator than any single signal alone.

How is PEP status determined? An entity is classified as Politically Exposed if it has FARA foreign agent registrations or if FEC campaign finance contributions exceed $10,000. This aligns with standard PEP screening frameworks.

Can I screen both individuals and companies? Yes. Set entityType to "person" to skip corporate checks (faster, cheaper), "company" for full corporate screening, or "any" to run all checks regardless.

What does the shell company analysis look for? It searches corporate records for nominee directors, bearer shares, trust companies, corporate services firms, shelf companies, and formation agents. Registration in known shell havens (Panama, BVI, Cayman Islands, Seychelles, and others) also contributes to the shell risk score.

Integrations

Use this actor with:

• Zapier for automated workflows
• Make for complex automations
• Google Sheets for spreadsheet export
• The Apify API for programmatic access