Subscription Fraud
Stop fraud at signup, before it ever becomes bad debt.
Subex scores identity risk the moment a customer onboards and watches early-life usage for the signals that give fraudsters away. Stolen and synthetic identities are caught at the door, not written off months later on a collections report. Cleaner signups, fewer early losses, bad debt cut at the root.
Overview
Subscription fraud occurs when fraudsters obtain SIMs or accounts using stolen or synthetic identities, then monetize the account through high-cost usage, resale, or downstream fraud. Subex helps CSPs score risk at onboarding and continuously monitor early-life usage to prevent losses.
The Challenge
Subscription fraud often begins at onboarding and escalates before early-life risk signals are reviewed. The CFCA Global Fraud Loss Survey 2025 estimates losses of $5.45 billion from application fraud and $5.06 billion from credit mule fraud.
Fraudsters exploit onboarding gaps using stolen IDs, synthetic profiles, or mule networks.
Losses often occur in the first days/weeks (early-life fraud) before risk signals are reviewed.
Manual verification and static rules cannot keep pace with high-volume digital onboarding.
Downstream impacts include bad debt, chargebacks, and reputational damage.
Real Impact. Real Efficiency. Real Results.
Reduce early-life losses by identifying high-risk activations and behaviors sooner.
Improve approval quality by applying consistent risk scoring across channels.
Lower bad debt and collection overhead by preventing avoidable exposure.
Protect customer experience by keeping controls targeted and evidence-based.
Key capabilities
Fraud scenarios detected and prevented across all services.
Real-time and near real-time risk scoring using onboarding and early-usage signals.
Velocity and pattern checks across identity attributes, device, location, and behavior.
Integration hooks for external KYC, credit scoring, device fingerprinting, and email/domain risk tools.
Case workflows for analysts to validate evidence and take policy actions.
- Webinar
Combating Identity Fraud with AI/ML Techniques
- Case Study
How Batelco Is Tackling Nefarious Telecom Frauds with Subex Fraud Management System
Case Study How Batelco is Tackling Nefarious Telecom Frauds with...
- Whitepaper
AI Agents in Telecom Fraud Management
Resource Center
- Point of View
Why telcos need an AI-first fraud management system?
- Whitepaper
Be Vigilant Against SMS Fraud with Proactive Mitigation
- E-book
AI-First Defense Against Telecom Fraud
Frequently Asked Questions
How does the solution detect fraud during digital onboarding?
The platform evaluates onboarding data in real time using AI-based risk scoring. It analyzes identity consistency, velocity signals, device attributes, geolocation, behavioral indicators, and external risk inputs to generate a risk score before approval or activation.
Can the solution integrate with our existing KYC and credit systems?
Yes. The platform provides integration hooks for external KYC providers, credit bureaus, device fingerprinting tools, and third-party risk intelligence sources. It complements, not replaces your existing onboarding stack.
Is this only for postpaid, or can it support prepaid and digital SIM onboarding?
The solution supports postpaid, prepaid, eSIM, and fully digital onboarding channels. Risk logic adapts based on product type, exposure model, and revenue profile.
How is synthetic identity fraud detected?
Synthetic identity fraud is identified by analyzing inconsistencies across identity attributes (name, DOB, address), unusual velocity patterns, device reuse signals, and cross-account linkages. The system detects subtle correlations that traditional rule-based systems often miss, particularly when identities appear partially legitimate.
Does the system support explainable AI?
Yes. Each risk score includes contributing factors and decision drivers, providing transparency for analysts, compliance teams, and audit requirements.