Fraud and anomaly detection — Telecom
Graph and sequence models catching fraud and process anomalies in real time. Delivered for a telecom client in Kutch.
- Location
- Kutch
- Year
- 2023
- Duration
- 24 weeks
- Team
- 9 engineers
- 90%
- fraud caught
- −43%
- false positives
- 35k
- tx per second
The challenge
Leadership wanted measurable results inside one quarter, with no disruption to running operations.
What we built
A phased rollout: a measured pilot first, then scale-out. The core runs on XGBoost with Graph ML, integrated into existing systems through Go.
Delivery timeline
Phase 1
Discovery sprint and site survey
Phase 2
Prototype built and tested in the Motera lab
Phase 3
Pilot on site with before/after measurement
Phase 4
Scale-out, training and handover
Highlights
- Integrated with existing PLC, ERP or GIS systems — no rip-and-replace
- Before-and-after measurements agreed with the client up front
- Documentation, drawings and source handed over at close
- Operator training delivered in Gujarati, Hindi and English
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