GLOBAL PAYMENTS KNOWLEDGEISO 20022 / SWIFT / SEPA / MT / MX
SCREENING LAB / 6 CASES

Sit in the analyst's chair.

Each case reveals a screening decision stage by stage — input, normalization, candidates, scoring, disposition, investigation. Every person, entity, and list entry is fictional; the reasoning is the real thing being taught.

  1. 01NAME MATCHING
    A clean pass through the filterMost payments pass screening untouched: the filter generates weak candidates, scores them, and discards them below threshold without any human involvement.
  2. 02FALSE POSITIVES
    A common surname collides with the listA high name score on a common name is a starting point, not a conclusion — date of birth and geography are what separate the customer from the listed person.
  3. 03NAME MATCHING
    The alias that was the real nameListed persons rarely transact under their primary list name — a well-maintained alias set is what catches them, and secondary identifiers are what confirm it.
  4. 04SECONDARY IDENTIFIERS
    Strong name, wrong person: identifiers decideA near-perfect name score cannot outweigh hard identifiers — date of birth and passport data on the list entry are what let you rule a customer out decisively.
  5. 05OWNERSHIP & CONTROL
    Not on the list, still blocked: ownership adds upAn entity owned 50 percent or more in the aggregate by listed persons is treated as blocked even though it appears on no list — the investigation, not the filter, is what finds this.
  6. 06MESSAGE SCREENING
    The hit hiding in the remittance lineScreening covers every field that can carry a name, and a hit on a non-party in free text raises a question the message alone cannot answer: what role does that entity play in the underlying transaction?