AIT Fraud in Telecom: Detection, Impact and Prevention with AI

Q: What’s the difference between Ping Calls and Wangiri Fraud?

Both involve missed calls, but Ping Calls are designed to inflate signaling traffic without user interaction, while Wangiri Fraud tricks recipients into returning high-cost calls.

Q: What tools or platforms are best for combating AIT?

Neural Technologies’ advanced Fraud Management Systems (FMS), IRSF Defense Modules, SS7/SIP analytics, and AI-machine learning engine, like ActivML offer proactive, real-time protection against AIT and related telecom fraud types.

Artificial Inflated Traffic (AIT) Fraud in Telecom

Telecommunications providers face a persistent and evolving array of telecom fraud threats. Among these, Artificial Inflated Traffic (AIT) fraud has emerged as a deceptive tactic that can severely impact telecom operators' revenue, voice traffic quality, and network integrity. Fraud schemes like AIT are part of a broader category of telecom revenue assurance challenges that affect both wholesale and retail voice services.

What is Artificial Inflated Traffic (AIT) Fraud?

Artificial Inflated Traffic (AIT) fraud involves fraudulent actors generating fake or artificially inflated volumes of calls, SMS, or VoIP traffic using automated tools like bots, auto-dialers, or SIM farms. These schemes often target termination rates, interconnect agreements, and revenue-sharing models, creating non-human (machine-generated) traffic that mimics legitimate communication patterns.

In essence, fraudsters create phantom traffic or fake call volumes to exploit telecom infrastructure and generate unearned revenue, often leaving operators to foot the bill.

The Impact of AIT Fraud

Telecom and VoIP Service Providers

Handle massive voice traffic volumes for clients.
Common targets for termination fraud, VoIP AIT, and interconnect bypass fraud.
May face revenue leakage, carrier billing disputes, and QoS (quality of service) degradation if AIT remains undetected.

Financial Institutions (Banks, Insurance)

High-risk targets due to sensitive financial data.
Use outbound VoIP dialers for verification and collections.
Exposed to vishing attacks, caller ID spoofing, and voice channel fraud.

Call Centers and BPOs

High-volume calling environments are ideal for international revenue share fraud (IRSF) and AIT.
May unknowingly originate or terminate fraudulent call traffic, leading to carrier surcharges, dispute settlements, or regulatory issues.

Mechanisms Behind AIT Fraud:

How It Typically Works

Fraudsters use automated systems to push massive volumes of low-duration, high-frequency calls, or bulk SMS, often via fraudulent SIM farms or compromised VoIP accounts. These attacks target traffic-based billing models and aim to inflate billing metrics while evading traditional detection systems.

Ping Calls (Ping Fraud)

Ping Calls focuses on infrastructure abuse; it is fully automated and requires no user interaction. Often involves placing a high volume of extremely short calls that disconnect after just one or two rings, before the recipient answers. These calls do not intend to initiate a conversation but are used to simulate legitimate signaling traffic, often for:

Artificially inflating interconnect traffic volumes
Exploiting carrier billing systems
Testing number validity for future fraud attempts

Wangiri Fraud (Missed Call Scam)

Wangiri fraud is a scam in which fraudsters place massive volumes of brief calls that disconnect before being answered. The difference from basic ping fraud is intent: the goal here is to lure the user into calling back. These return calls, once connected, incur high charges for the caller and generate income for the fraudster through revenue sharing or international call termination payouts.

This makes Wangiri fraud both an AIT method and a consumer scam, targeting:

Mobile subscribers
Enterprise VoIP users
Telecom operators handling inbound traffic

SIM Boxing / SIM Farms

Used to bypass international routing and inflate local traffic, resulting in SIM box fraud, grey route usage, and revenue leakage.

Fake SMS Traffic (SMS Pumping)

Bulk, non-human SMS generation, is often triggered by one-time password (OTP) forms, chatbots, or abused APIs on websites.

Auto-Dialer Flooding

High-volume robocalls that target test numbers, unused ranges, or premium-rate destinations, leading to auto-dial fraud.

Call Forwarding Exploits

Used to route fraudulent traffic through multiple networks, often exploiting PBX systems, diverted calls, or call chaining.

VoIP Traffic Manipulation

Attacks that generate synthetic VoIP traffic to inflate VoIP CDRs (Call Detail Records), often involve fraudulent SIP trunking setups.

PBX Hacking (Enterprise Traffic Exploitation)

VoIP PBX systems are vulnerable to unauthorized access, especially when using weak SIP credentials or unpatched software. Once compromised, attackers route mass outbound calls to high-cost destinations, inflating traffic via internal IP-PBX systems, making detection difficult.

Leveraging Artificial Intelligence (AI) in Combating AIT Fraud

Identifying AIT fraud in real time requires more than static rule sets. AI-powered telecom fraud detection systems offer dynamic, adaptive monitoring that can recognize subtle deviations in traffic behavior.

AI-Driven Detection Techniques:

Traffic Pattern Analysis – AI monitors for anomalous traffic volumes, spikes in average call duration, and short-duration call flooding.
Behavioral Profiling – ML models build profiles of normal subscriber or enterprise behavior, flagging outliers or synthetic traffic.
Real-Time Fraud Scoring – Enables immediate action through fraud scoring models that integrate call metadata, device data, and traffic patterns.
Known Fraud Signature Correlation – Matches traffic against databases of known fraud schemes, blacklisted IPs, or compromised number ranges.

AI-Powered Telecom Fraud Defense:

A Smarter Defense Against AIT

Artificial Inflated Traffic (AIT) fraud requires a multi-layered defense strategy rooted in real-time intelligence and automation. Neural Technologies’ comprehensive Fraud Management System (FMS) combines advanced signaling analytics, fraud detection models, and machine learning to protect operators from evolving attack vectors.

Real-time Fraud Intelligence: Powered by advanced behavioral profiling and signaling data analysis across voice, SMS, and IP-based services.
IRSF Defense Module: Detects and blocks suspicious international revenue-share patterns using number intelligence, call destination profiling, and behavior-based risk scoring.
Signaling-Layer Analytics: Enables deep visibility into SS7, SIP, and Diameter layers to identify anomalies like spoofing, bypass routing, or unauthorized call manipulation in real time.
ActivML Engine: Continuously adapts to new fraud signatures, learning from traffic behavior, historical patterns, and external intelligence to deliver proactive detection.

Protect your telecom network from evolving AIT fraud threats with Neural Technologies

Discover how Neural Technologies’ AI-powered Fraud Management System (FMS) can safeguard your revenue and ensure network integrity.

Frequently Asked Questions (FAQs)

What is Artificial Inflated Traffic (AIT) fraud in telecom? Artificial Inflated Traffic (AIT) fraud refers to fake or non-human call and SMS traffic generated by bots, auto-dialers, or SIM boxes to exploit interconnect fees or revenue-sharing agreements between telecom operators.

How does AIT fraud impact telecom providers? AIT fraud leads to revenue leakage, billing disputes, poor voice traffic quality, inflated usage reports, and network resource abuse. It can also damage trust with partners and regulators.

What’s the difference between Ping Calls and Wangiri Fraud? Both involve missed calls, but Ping Calls are designed to inflate signaling traffic without user interaction, while Wangiri Fraud tricks recipients into returning high-cost calls.

How can telecoms detect and prevent AIT fraud? Operators can prevent AIT fraud using AI-powered tools like real-time fraud scoring, signaling-layer analytics, and machine learning models that identify synthetic patterns in voice and SMS traffic.

What tools or platforms are best for combating AIT? Neural Technologies’ advanced Fraud Management Systems (FMS), IRSF Defense Modules, SS7/SIP analytics, and AI-machine learning engine, like ActivML offer proactive, real-time protection against AIT and related telecom fraud types.