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From Fuzzy Matching to Evidence Capsules: Building an Explainable Sanctions Screening Engine

DEV Community·Verifex·19 days ago
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Sanctions screening looks simple from the outside. Take a name, compare it against a list, return a score above a threshold, send it to review. That was how I thought about it before I started building Verifex. The reality is different. The problem nobody talks about A compliance reviewer does not just need to know that two names are similar. They need to understand why a match was created, what evidence supports it, what weakens it, and whether the decision holds up during an audit six months later. A score alone does not answer any of those questions. When the engine returns 0.92, the reviewer is still left asking: was that the surname? The alias? The date of birth? The country? The source list? Without that breakdown, every review is manual reconstruction from scratch. What fuzzy matching misses Fuzzy string matching works fine for clean data. John Smith vs John Smith -- no problem. ACME Ltd vs ACME Limited -- no problem. But real sanctions data is messier than that. Names get reordered.…

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