Introduction
Fraud prevention is not just a technical issue—it’s a business priority. Telecom operators lose billions of dollars every year to fraudulent activities like Simbox bypass, CLI spoofing, Wangiri scams, and SMS fraud. To mitigate these risks, operators must go beyond basic monitoring and embrace a proactive approach powered by real-time Key Performance Indicators (KPIs). These Fraud KPIs serve as early warning signs, helping teams detect anomalies, understand fraud patterns, and respond quickly.
We’ll explore the essential KPIs every telecom operator should track to combat fraud effectively—and how Synaptique’s S-ONE FRAUD solution delivers these insights with precision.
What Fraud KPIs Should Telecom Operators Monitor?
1. Abnormal Traffic Volume per Route or Destination
Why it matters: Sudden spikes or drops in traffic—especially on international routes—often signal fraudulent behavior such as SIM box fraud or A2P bypass. S-ONE FRAUD advantage: Real-time dashboards flag unusual traffic volume changes, enabling fast detection and investigation.
2. Short-Duration Calls (e.g., less than 3 seconds)
Why it matters: High volumes of short-duration calls are classic indicators of Wangiri fraud or SIM box testing activity. S-ONE FRAUD advantage: The system monitors call durations continuously and alerts teams to irregular surges, filtered by country or destination prefix.
3. Invalid or Repeated CLI Usage
Why it matters: Repetition or spoofing of caller line identity (CLI) often signals CLI manipulation, a tactic used to hide call origins or bypass billing. S-ONE FRAUD advantage: By validating CLI consistency and detecting repeated patterns, the platform can flag spoofed or suspicious traffic in real time.
4. Success Rate by Call Type
Why it matters: A drop in call completion rates for certain routes or operators may indicate intentional call drops or filtering by SIM boxes. S-ONE FRAUD advantage: Monitors and compares success rates across destinations, helping isolate underperforming routes or fraud-affected destinations.
5. Traffic Pattern Anomalies
Why it matters: Unusual usage profiles—such as calls made in fixed time intervals or with identical durations—can be evidence of fraud. S-ONE FRAUD advantage: Uses machine learning to detect repeated patterns that defy normal user behavior.
6. Ratio of On-Net vs. Off-Net Calls
Why it matters: An imbalanced ratio can suggest SIM boxes using only on-net traffic to avoid detection. S-ONE FRAUD advantage: Tracks voice and SMS traffic across networks and compares behavior to operator benchmarks.
7. SIM Card Behavior Monitoring
Why it matters: Fraudulent SIM cards often switch IMEIs, never receive calls, or only send international traffic. S-ONE FRAUD advantage: Identifies silent SIMs, high churn rates, and other red flags from SIM behavior analytics.
8. Revenue Loss Estimation
Why it matters: Understanding how much revenue is at risk helps prioritize actions and report impact. S-ONE FRAUD advantage: Estimates loss by correlating suspicious traffic with interconnect rates and normal trends.
S-ONE FRAUD: A Smarter Way to Monitor Fraud KPIs
S-ONE FRAUD by Synaptique is built to empower fraud management teams with rich, actionable insights. Whether you’re a regulator or operator, the solution allows you to:
- Customize fraud dashboards by fraud type and severity
- Monitor KPIs in real time or on a scheduled basis
- Receive automated alerts for any deviation from fraud baselines
- Visualize trends through maps, graphs, and detailed reports
Let’s talk. Book a quick session with our team to discuss your current fraud challenges and see how S-ONE FRAUD can help you detect, analyze, and stop fraud with real-time data and smart alerts.
Book a call now to discover how data can power your fraud prevention strategy.
Final Thoughts
Fraud in telecom is evolving rapidly—but so are the tools to fight it. Monitoring the right KPIs is key to identifying fraud early and reducing financial losses. Synaptique’s S-ONE FRAUD solution not only helps you stay ahead of fraudsters but also provides the intelligence to make data-driven decisions.