This is like a 24/7 security system for telecom transactions and customer accounts that watches patterns across billions of events and flags activity that ‘doesn’t look right’ before fraudsters can do real damage.
Telecom companies suffer losses from identity theft, account takeover, subscription fraud, and payment fraud that are hard to catch with manual reviews or simple rule engines. This solution uses analytics to automatically detect and prevent suspicious activity across large customer bases in real time, reducing fraud losses while minimizing friction for legitimate customers.
Access to large, proprietary cross‑industry identity and fraud data combined with mature fraud models and integrations into telecom onboarding, billing, and customer-care workflows.
Classical-ML (Scikit/XGBoost)
Feature Store
Medium (Integration logic)
Real-time scoring latency and maintaining up-to-date, high-quality identity and transaction features at telecom scale.
Early Majority
Positioned as an advanced, data-rich fraud analytics layer specifically tuned for high-volume, high-risk customer and transaction flows, going beyond simple rule engines by leveraging broad identity intelligence and telecom-relevant patterns.