Identity Risk Scoring Only Works If Attribution Is Defensible

The post argues that identity risk scoring only becomes operationally valuable when grounded in defensible attribution—resolving identities across multiple identifiers, updating with new intelligence, and providing transparent, confidence-weighted explanations. It highlights common shortcomings (single-identifier matching, static models, lack of explainability), explains how verified breach data improves attribution and reduces false positives, and outlines the benefits for fraud and security teams, including better automation, auditability, and faster investigations.