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Name Matching Algorithms & SWIFT Payment Screening Explained | AML Ep 4 of 8
Welcome to Episode 4 of the AML Screening Masterclass — Name, Payment and Watchlist Screening.
Mohammed. Mohamed. Muhammad. Muhammed. Mohammad. All the same person — and all potentially the same sanctioned individual on the OFAC list. Does your screening system catch every variation? This episode explains exactly how it should.
WHAT YOU WILL LEARN:
✅ The 3 name matching algorithms: Exact, Fuzzy (Levenshtein distance) and Phonetic (Soundex) — how each works and when each is needed
✅ Transliteration challenges — why Arabic, Chinese, Russian and Korean names have multiple valid English spellings and how to screen them all
✅ SWIFT MT103 payment screening — all 6 fields that must be checked in real-time, including the free-text Field 70 that most systems miss
✅ Real-time vs Batch screening — the exposure window risk and when to run emergency batch jobs
✅ Internal Watchlist — the 4 types: Blacklist, Fraud Database, SAR-filed entities and High-Risk Monitoring List
WHY THIS MATTERS:
A single character change in a name can defeat basic exact matching. The Levenshtein distance algorithm closes that gap — but only if your system is configured correctly. This episode gives you the technical understanding to challenge your own screening setup.
🎓 FULL SERIES — AML Screening Masterclass:
▶ Ep 1 — Introduction to AML Screening [link]
▶ Ep 2 — Sanctions Screening Deep Dive [link]
▶ Ep 3 — PEP and Adverse Media Screening [link]
▶ Ep 4 — Name, Payment and Watchlist Screening (YOU ARE HERE)
▶ Ep 5 — Screening Operations and Alert Management [coming next]
▶ Ep 6 — Red Flags, Escalation and FATF Risk Lists
▶ Ep 7 — Case Studies and Programme Governance
▶ Ep 8 — Interview Prep and Final Assessment
💬 COMMENT CHALLENGE: Can you name at least 5 different valid English spellings of the Arabic name Mohammed? Drop your answers below — I'll reply with the full list.
🔔 SUBSCRIBE — new episode every week.
#AMLScreening #NameScreening #SWIFTPayments #KYC #AML #FATF #BankingCompliance #CAMS #FinancialCrimeAcademy #ComplianceTraining #Levenshtein #PaymentScreening
Видео Name Matching Algorithms & SWIFT Payment Screening Explained | AML Ep 4 of 8 канала Financial Crime Academy by Hemant Mishra
Mohammed. Mohamed. Muhammad. Muhammed. Mohammad. All the same person — and all potentially the same sanctioned individual on the OFAC list. Does your screening system catch every variation? This episode explains exactly how it should.
WHAT YOU WILL LEARN:
✅ The 3 name matching algorithms: Exact, Fuzzy (Levenshtein distance) and Phonetic (Soundex) — how each works and when each is needed
✅ Transliteration challenges — why Arabic, Chinese, Russian and Korean names have multiple valid English spellings and how to screen them all
✅ SWIFT MT103 payment screening — all 6 fields that must be checked in real-time, including the free-text Field 70 that most systems miss
✅ Real-time vs Batch screening — the exposure window risk and when to run emergency batch jobs
✅ Internal Watchlist — the 4 types: Blacklist, Fraud Database, SAR-filed entities and High-Risk Monitoring List
WHY THIS MATTERS:
A single character change in a name can defeat basic exact matching. The Levenshtein distance algorithm closes that gap — but only if your system is configured correctly. This episode gives you the technical understanding to challenge your own screening setup.
🎓 FULL SERIES — AML Screening Masterclass:
▶ Ep 1 — Introduction to AML Screening [link]
▶ Ep 2 — Sanctions Screening Deep Dive [link]
▶ Ep 3 — PEP and Adverse Media Screening [link]
▶ Ep 4 — Name, Payment and Watchlist Screening (YOU ARE HERE)
▶ Ep 5 — Screening Operations and Alert Management [coming next]
▶ Ep 6 — Red Flags, Escalation and FATF Risk Lists
▶ Ep 7 — Case Studies and Programme Governance
▶ Ep 8 — Interview Prep and Final Assessment
💬 COMMENT CHALLENGE: Can you name at least 5 different valid English spellings of the Arabic name Mohammed? Drop your answers below — I'll reply with the full list.
🔔 SUBSCRIBE — new episode every week.
#AMLScreening #NameScreening #SWIFTPayments #KYC #AML #FATF #BankingCompliance #CAMS #FinancialCrimeAcademy #ComplianceTraining #Levenshtein #PaymentScreening
Видео Name Matching Algorithms & SWIFT Payment Screening Explained | AML Ep 4 of 8 канала Financial Crime Academy by Hemant Mishra
AML Screening Financial Crime Academy Hemant Mishra AML compliance training KYC training name screening AML fuzzy matching compliance Levenshtein distance Soundex algorithm transliteration banking SWIFT MT103 screening payment screening internal watchlist OFAC name matching AML algorithms AML masterclass CAMS exam KYC algorithms
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17 мая 2026 г. 20:20:01
00:12:38
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