Large insurance groups authenticate millions of customers, employees, and partners every day across complex multi-cloud environments. Detecting compromised accounts within that volume, in real time, requires AI models that can operate at production speed while remaining small enough to deploy cost-efficiently at scale. Multiverse Computing designed and deployed an anomaly detection system for one of the world's largest insurance groups, integrated directly into their existing cybersecurity infrastructure.
The Challenge
The client's cybersecurity team needed to identify compromised accounts within a continuous, high-volume stream of authentication events, without triggering excessive false positives that would overwhelm security operations. Standard anomaly detection approaches were either too large to run cost-efficiently at the required scale or too slow to deliver real-time signals. The solution had to integrate with existing cloud infrastructure without requiring new hardware or a separate detection pipeline.