Implementing Risk-Based Identity Verification

Excluded from normalized aggregate trends after staff review: 3056 posts were attributed to March 2026; 671 shared March 14, 2026. The preceding six-month median was 13.5 posts.

Review evidence: 3,056 posts in March 2026; 671 shared March 14, 2026; preceding six-month median 13.5. Reviewed August 9, 2026.

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Risk-based identity verification tailors the level of customer and transaction scrutiny to assessed risk rather than applying uniform checks, aiming to improve AML compliance, fraud prevention, operational efficiency, and customer onboarding. Risk scores can account for factors such as customer type, geography, transaction value and nature, business relationships, and the products involved, with results determining whether simplified, standard, or enhanced due diligence is appropriate. Because risk can change over time, continuous monitoring of behavior, transactions, regulatory updates, and new information is needed to detect suspicious activity and update verification requirements. Didit presents its platform as infrastructure for implementing these workflows through configurable rules, automated decisions, more than 1,000 data sources, and integrated KYC, KYB, transaction monitoring, and wallet-screening capabilities, supported by broad international document and language coverage and security certifications.

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