Screen for sanctions and PEPs with real judgment — read list logic and ownership/control, resolve name-match alerts into true match, near-match or false positive, escalate true matches and unresolved hits the right way, and avoid both missed targets and self-inflicted alert noise.
Sanctions and PEP screening is where a single wrong disposition can mean a frozen payment that should have moved, or a designated party moving money that should have been stopped. This is the second course in the "Financial Crime / Compliance Track" and builds directly on AML / KYC & Financial-Crime Effectiveness, taking the same controls-to-outcomes mindset into the screening engine. Across four phases — Engage, Share, Practice, Perform — analysts work realistic 2026 cases (the OFAC 50-Percent shell, the Volkov fuzzy-match, the relationship-manager PEP, the post-list-update batch, the over-tuned filter) to build the judgment that a cleared hit is a sound decision, not just an emptied alert queue.
Hook into why hit-clearing is the riskiest job in compliance, and surface where your own screening judgment actually sits today.
Learn the models that drive sound dispositions: how lists and ownership/control work, the name-matching decision, the true-match freeze rules, and PEP handling.
Apply the judgment with feedback across the whole topic: resolve a fuzzy hit, screen behind an ownership chain, sequence a true-match response, oversee an over-tuned filter, and defend a disposition in writing.
Prove the judgment: defend a disposition under challenge, pass the screening knowledge gate, then attest to your sanctions/PEP duties and commit to a concrete habit.
Related in this track
Book a demo and we'll run "Sanctions & PEP Screening: Judgment Over Hit-Clearing" end to end on your people — the AI asks, your people think — or point the Forge at your own material instead (a pre-pilot capability preview).