Progressive risk segmentation

The process starts with minimal friction for low-risk users—like basic KYC. As the user engages in higher-risk actions (e.g., sending large transfers or accessing sensitive features), more layers of verification (IDV, MFA, biometric authentication) are triggered. The system evaluates real-time risk factors like device behavior, IP changes, or transaction velocity to dynamically assign a risk tier.

It strikes a balance between security and user experience. Rather than applying maximum verification to everyone upfront, progressive segmentation minimizes onboarding friction while maintaining strong controls for users who pose higher risk. This is particularly useful for fintech, crypto exchanges, and online marketplaces with varying risk thresholds.

The hardest part is designing reliable and real-time risk scoring models. Organizations often struggle with false positives or missing emerging threats due to rigid logic. Another issue is integrating behavioral and transactional data sources into one cohesive risk model. Regulatory expectations may also require that even low-risk users undergo certain checks, reducing flexibility.