The Two-Score AML Model: Match Score vs Risk Score
Blog post from Didit
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Didit's AML Screening engine employs a two-score model to enhance the accuracy of anti-money laundering checks by independently assessing identity confidence and entity risk, thus minimizing false positives and ensuring that analysts focus on genuinely risky entities. The Match Score evaluates whether a watchlist hit is genuinely the customer by analyzing factors like name similarity, date of birth, and country, while the Risk Score assesses the potential threat level of a confirmed match based on elements such as category, country risk, and criminal record. These scores are calculated separately, allowing the system to automatically dismiss weak identity matches as false positives, optimizing the workload for analysts. A unique feature is the "Golden Key," where a document-number match guarantees a 100% Match Score, indicating definitive identity proof. Configurable weights and thresholds allow users to tailor the system to their risk preferences, and both scores are integrated into Didit's verification workflows, with a per-check cost of $0.20.
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