Subscriber Fraud and Network Anomaly Detection

Detects anomalous subscriber, identity verification, network, and 5G slice behaviors to reduce fraud, predict failures, improve service assurance, and support targeted retention actions.

The Problem

“Telecom Fraud and Network Anomaly Detection across subscribers, identity, network operations, and 5G slices”

Organizations face these key challenges:

Fraud systems are fragmented across subscriber, identity, and network domains

Static thresholds generate excessive false positives and miss zero-day anomalies

Churn campaigns are broad and expensive due to weak targeting

SMS OTP introduces cost, latency, and vulnerability to interception or abuse

5G slice operations are complex and depend heavily on manual troubleshooting

Telemetry is high-volume, multi-vendor, and difficult to normalize in real time

Root-cause analysis is slow because alarms, logs, traces, and topology are siloed

Closed-loop remediation is limited by weak orchestration and policy guardrails

Impact When Solved

Reduce fraud losses from SIM swap, account takeover, synthetic identity, and suspicious usage patternsImprove churn model lift and retention conversion with propensity scoring and next-best-action recommendationsCut MTTR through anomaly correlation, root-cause prioritization, and automated remediation workflowsLower alert fatigue in NOC and SOC teams by suppressing noisy threshold-based alarmsIncrease sign-up and transaction completion rates with number verification using network possession signalsImprove 5G slice reliability and SLA compliance with predictive failure detection and orchestration

The Shift

Before AI~85% Manual

Human Does

•Review every case manually
•Handle requests one by one
•Make decisions on each item
•Document and track progress

Automation

•Basic routing only

With AI~75% Automated

Human Does

•Review edge cases
•Final approvals
•Strategic oversight

AI Handles

•Automate routine processing
•Classify and route instantly
•Analyze at scale
•Operate 24/7

Real-World Use Cases

Churn prediction and retention targeting

AI spots customers who may leave and helps the operator send the right offer or intervention before they churn.

Propensity scoring and next-best-action recommendationhighly mature and commercially proven

10.0

Number Verification for identity confirmation without OTP

Confirms that a user really controls a phone number by checking with the mobile network directly, instead of relying only on a texted code.

Deterministic identity verification using network possession signals.early commercial deployment via standardized telecom apis.

10.0

AI for 5G core slice management, anomaly detection, and failure prediction

AI helps the network core automatically give the right resources to customers, spot suspicious behavior, and warn about problems before outages happen.

Anomaly detection, prediction, and autonomous orchestrationemerging operational use case with clear 5g sa relevance.

10.0

AIOps network and service assurance for telecom services and 5G slices

AI watches telecom network data all the time, spots problems early, and helps fix them before customers notice service issues.

Anomaly detection and automated decisioning in a closed-loop assurance workflowcommercial solution with deployed aiops assurance positioning, though source excerpt provides limited implementation detail.

10.0