Cutting AML False Positives With Configurable Thresholds
Blog post from Didit
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Didit’s AML screening approach focuses on reducing costly false positives, particularly namesake matches across more than 1,300 watchlists, by allowing organizations to tune identity and risk decisions to their populations. Users can adjust match-score weights for name, date of birth, and country; set a match threshold that automatically classifies lower-confidence records as false positives; and configure risk thresholds that determine whether confirmed matches are approved, reviewed, or declined. A matching document number, called the Golden Key, overrides the match score to 100% and provides a stronger identity signal that can eliminate name ambiguity. Suppressed records retain scores and statuses for auditability, enabling teams to explain automated decisions to regulators. The service is positioned for uses including fintech, crypto, lending, marketplaces, and iGaming, with configuration available through the console and AML screening priced at $0.20 per check.
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