The model connects more than 2,400 predictive variables across ten intelligence pillars into one calibrated fraud score on a 0 to 1 scale, with reason codes and underlying signals exposed. The system adapts to context, allowing for tailored risk assessments based on user behavior and transaction type. The company positions its proprietary identity graph, built over 12 years across names, addresses, PII, devices, and biometrics, as a differentiator over providers that assemble checks from third-party vendors, while RiskOS lets teams adjust decision strategies without engineering work.