From the report, “Widespread data breaches, the EMV migration, and efforts to extend the longevity of the SSN, have created an ideal environment in which synthetic identity fraud is flourishing. Furthermore, consumers’ physical and digital footprints are becoming more complicated, meandering across locations, devices, and geographies. This makes it more difficult than ever to differentiate legitimate user behavior from fraudsters. Businesses need to prevent synthetic identities from entering their ecosystems by understanding anomalies to individual user behavior and helping to correlate the seemingly disconnected events and security incidents in real time. Combining historical and real-time data and leveraging machine learning to analyze individual behavior across channels can reveal complex patterns to help detect and block synthetic identities without causing friction for real customers.”