Defending telecom revenues with an AI-powered shield against IRSF and SIM-boxing
Overview
Our client is a Tier-1 telecommunications provider serving tens of millions of customers across multiple continents, with a robust infrastructure that processes over 1 billion call-detail events and 2.5 billion data loads daily. A significant portion of this traffic stems from short-term SIM usage by tourists and transient users, creating a dynamic and complex network environment.
To safeguard revenue and maintain service integrity, the client partnered with HCLTech to deploy a scalable, rule-based fraud detection solution capable of identifying and mitigating sophisticated threats such as International Revenue Share Fraud (IRSF) and SIM boxing. The initiative aimed to enhance fraud detection accuracy, reduce revenue leakage and ensure uninterrupted operations across the high-volume network.
The Challenge
Fighting sophisticated fraud, hidden in plain sight at scale.
Hidden within massive daily traffic volumes, two key threats evaded detection by traditional, subscriber-focused monitoring tools. The client was facing significant revenue leakage due to these prevalent and highly sophisticated fraud types:
- International Revenue Share Fraud (IRSF): Exploiting international revenue-sharing agreements by artificially generating call traffic to premium-rate numbers.
- SIM-boxing: Using illegal GSM gateways with prepaid SIM cards to terminate international calls as local traffic, bypassing legitimate billing.
Traditional subscriber behavior monitoring techniques were no longer sufficient to keep pace with these evolving threats. The fraudsters’ use of transient SIM cards, distributed across geographies and with rapidly changing usage patterns, made manual or legacy detection methods ineffective and delayed. The telecom provider needed a faster, smarter way to uncover fraud patterns in real-time, without compromising customer experience or operational performance.
The Objective
Enhancing fraud detection with deterministic, rule-based models
To address the increasing volume and complexity of fraudulent activities, the objective was clear:
- Move beyond reactive detection and adopt proactive fraud prevention strategies
- Introduce rule-based models capable of flagging suspicious behavior across multiple variables
- Accelerate fraud identification to prevent revenue loss and minimize exposure
- Strengthen fraud risk coverage across all international traffic profiles
This required a holistic approach that blends behavior analysis with deterministic, algorithm-driven fraud detection.
The Solution
Built-in fraud intelligence
We deployed Fraud Management framework — an extensible analytics platform tuned for high-volume telco environments — and configured it with a rich library of industry-proven fraud rules. The solution was purpose-built to meet the client's high-scale, high-risk operational demands. Key components of the solution included:
- Behavioral matching profiles: Developed profiles that tracked and analyzed usage patterns across key fraud indicators, such as top international calling destinations, IMEI variations, traffic spread and call diversity.
- Rule-based fraud detection engine: Applied deterministic algorithms to flag deviations from established norms. This enabled rapid identification of suspicious usage, particularly for high-risk activities like SIM cycling and short-duration, high-volume international calls.
- Scalable, data-driven architecture: Integrated seamlessly into the client’s existing infrastructure to handle over a billion events daily without performance being compromised.
- Continuous learning loop: Built feedback mechanisms into the system to refine detection rules and enhance fraud prevention over time.
This multi-layered approach significantly improved the accuracy and speed of fraud detection, allowing the telecom operator to act decisively before losses accumulated.
The Impact
Revenue safeguarded: From delayed detection to proactive fraud prevention
By pairing deep telco expertise with a purpose-built analytics stack, our team of experts turned fraud defence from a reactive cost centre into a proactive business enabler:
- 85 % faster fraud detection — minutes instead of hours or days
- 5x expansion in fraud-risk coverage within six months
- 50 % reduction in revenue loss attributed to IRSF and SIM-boxing
Through this initiative we not only protected the client’s financial health but also reinforced our trust with stakeholders, ensuring resilient operations in a fast-moving telecom environment. The outcome highlights how our rule-based, AI-ready approach can protect critical margins even in the most data-intensive telecom environments, helping carriers stay one step ahead of today’s most sophisticated threats.
At HCLTech, we are committed to future-proofing fraud management in an ever-evolving threat landscape.
