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Artificially Inflated Traffic
Spot artificial traffic surges early. Contain cost exposure fast. Protect A2P and termination revenues.
Move from post-settlement discovery to near real-time detection of inflated traffic. Subex combines behavioral baselining, ML-driven anomaly detection, and route-level risk analytics to catch artificial volumes before they hit settlement.
Overview
Artificially Inflated Traffic (AIT) is a telecom fraud scheme in which perpetrators deliberately generate unnecessary or artificial traffic to create chargeable traffic. This traffic is typically directed toward high-cost destinations or revenue-share partners, allowing fraudsters to profit from termination fees or revenue-sharing arrangements.
Subex addresses AIT through proactive, AI-powered fraud detection that monitors network traffic in near real time, identifies abnormal traffic patterns early, and enables rapid containment to minimize fraud runtime and financial exposure
The Challenge
Global telecom fraud losses now stand at $41.82 billion, or 2.46% of industry revenues. IRSF and artificial traffic inflation (AIT) alone account for an estimated $2.6 billion, driven by automated traffic, high-cost routes, and detection that often comes too late.
Sudden, artificial spikes in A2P and voice traffic significantly increase termination and interconnect costs.
Automated bots, scripts, and click-farms systematically trigger chargeable events at scale.
Revenue-share agreements and high-cost destinations create incentives that fraudsters exploit.
Post-event reconciliation and billing reviews detect losses only after financial damage has occurred.
Genuine enterprise campaigns and seasonal promotions can obscure fraudulent traffic patterns.
Benefits
Early Detection of Abnormal Traffic Patterns
Identify traffic anomalies in near real time before artificial volumes escalate into significant termination losses.
Reduced Fraud Runtime
Shorten detection-to-action cycles to limit the financial impact of high-cost traffic bursts.
Protection Against Revenue-Share Abuse
Flag suspicious partner-linked traffic spikes and enforce policy controls to prevent revenue-share exploitation.
Safeguarding Legitimate Campaigns
Differentiate between genuine marketing campaigns and fraud-driven traffic inflation to avoid unnecessary service disruption.
Operational Transparency
Provide clear audit trails, traffic intelligence, and evidence for finance, fraud, and wholesale teams.
Key capabilities
Real-Time Traffic Monitoring
Continuously monitor A2P, voice, and signaling events across routes, destinations, partners, and enterprise sources.
AI/ML-Based Anomaly Detection
Use behavioral baselining and ML model-driven pattern recognition to detect unusual traffic surges, velocity shifts, and destination clustering associated with AIT.
Revenue-Share & Route Risk Analytics
Correlate traffic spikes with high-cost routes, premium destinations, and revenue-share agreements to identify potential abuse patterns.
Bot & Automation Pattern Detection
Identify traffic signatures linked to scripted or automated triggering of calls and messages.
Policy-Driven Controls
Enable configurable thresholds, alerts, route blocks, partner restrictions, and workflow escalations to contain fraud quickly.
Dashboards & Financial Impact Tracking
Provide real-time visibility into traffic trends, cost exposure, blocked volumes, and estimated loss prevention.
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Frequently Asked Questions
Everything you need to know about how our Artificially Inflated Traffic solutions work.