Why LLMs are the new standard in watchlist screening

Socure argues that conventional string-matching watchlist screening creates excessive false positives, citing examples in which legitimate banks were mistakenly matched to sanctioned entities and noting that poor screening can increase regulatory, operational, and reputational risk. It positions its rebuilt watchlist engine as an LLM-based system that evaluates name semantics, corporate relationships, transliterations, cultural naming conventions, and contextual references rather than only character similarity. The company reports performance claims including more than 98% accuracy in name-degradation testing, a reduction in false-positive ratios from 100:1 to 3:1, 100% recall in tests involving PEPs and sanctioned individuals, faster alert reviews, and real-time processing capacity. Socure also plans to apply similar methods to identity matching and improve model explainability, validation, traceability, and audit readiness to support compliance with BSA, OFAC, and FATF-related obligations.

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