screening

Screen customers against sanctions and PEP watchlists with HITL decision gates.

53|10|Updated Feb 15, 2026
One-click install
npx skills add https://github.com/vyayasan/kyc-analyst --skill screening-vyayasan
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: screening
Source: https://github.com/vyayasan/kyc-analyst/tree/main/skills/screening
Command: npx skills add https://github.com/vyayasan/kyc-analyst --skill screening-vyayasan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Screening customers against sanctions and PEP lists is repetitive, time-consuming, and easy to document inconsistently, especially when you must assess false positives and escalate uncertain cases.

Core Features & Use Cases

  • Multi-database sanctions and PEP screening across 12+ sources (e.g., OFAC, EU, UK, UN, Interpol, OpenSanctions, and multiple PEP datasets).
  • False positive assessment with HITL decision gates using name similarity, DOB, nationality, location, evidence/photograph signals, and contextual support.
  • Regulatory-style reporting and escalation briefs for TRUE MATCH, FALSE POSITIVE, and UNCERTAIN outcomes, including documentation artifacts.

Use case example: You onboard a customer and beneficial owners, run screening across relevant databases, then generate a manager/MLRO escalation brief only for true matches or unclear cases while documenting why likely false positives are accepted.

Quick Start

Run screening for a customer name and attributes by invoking /kyc:onboard-interactive with the customer identity and risk context.

Frequently Asked Questions about screening

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I screen customers against sanctions and PEP lists?

Sanctions and PEP screening searches multiple watchlists like OFAC, EU, and UN for each customer target, evaluating match quality to reduce false positives. It applies to onboarding, refresh, and batch screening scenarios covering individuals, entities, and beneficial owners.

What is the best way to assess false positives during watchlist screening?

False positive assessment during watchlist screening evaluates name similarity, DOB, nationality, location, evidence, and contextual support signals. It applies human-in-the-loop decision gates categorized as TRUE MATCH, FALSE POSITIVE, or UNCERTAIN to ensure accurate compliance outcomes.

Can I generate regulatory escalation briefs for KYC screening matches?

Regulatory escalation briefs for KYC screening matches are produced for TRUE MATCH and UNCERTAIN outcomes. The screening process generates compliance-ready reports with documentation artifacts and manager or MLRO escalation outputs when warranted.

Does sanctions screening work for batch processing and ad hoc reviews?

Sanctions screening supports onboarding, refresh, and ad hoc or batch screening scenarios. It searches over twelve databases including OpenSanctions and Interpol, recording search evidence and applying decision gates for individuals, entities, directors, and close associates.

Do I need human-in-the-loop decision gates for AML compliance screening?

Human-in-the-loop decision gates are required for AML compliance screening to categorize outcomes as TRUE MATCH, FALSE POSITIVE, or UNCERTAIN. This ensures regulatory-style reporting accuracy and proper documentation of likely false positives before acceptance.