As the telecommunications industry continues to evolve, embracing cutting-edge technology is no longer optional—it’s essential. In fraud detection, reliance on traditional pattern analysis and machine learning is rapidly being enhanced by AI fraud detection, which enables real-time support for analysts, improving both speed and precision in identifying fraud risks.

Integrating AI for Real-Time Detection Success

At iCONX, we’ve taken a significant step forward by embedding AI fraud detection capabilities into our system, offering a user-friendly interface that enhances decision-making. To learn more about our comprehensive approach to fraud management, visit our Fraud Management page. Ger Ryan, our Head of Professional Services, recently shared our progress at the Industry CEPT conference in Copenhagen. His session, “AI & Use Cases for Wholesale Voice in Proactive Fraud Prevention,” gathered leaders from telco and communication providers across Europe, as well as international regulators and solution vendors, all exploring new strategies to combat fraudulent communications. Check out our LinkedIn post on the Workshop. 

Our Fraud GUI (which can be seen below) includes a simple visual indicator: red, indicating a high likelihood of fraud, and green, indicating minimal risk. This system helps analysts make faster and more informed decisions. While AI fraud detection has proven highly effective, integrating AI into the telecom BSS/OSS ecosystem requires constant validation. The human factor remains critical, especially in retraining the AI model to minimise false negatives—when actual fraud could otherwise be misclassified as non-fraudulent.

Alert dashboard showing high predicted fraud likelihood. Severity is high, indicating activity from Saint Vincent and the Grenadines. Five warnings listed, including suspiciously low ACD values.

Case Study: Wangiri Fraud Detection Success

One real-world example that illustrates the power of AI fraud detection is its effectiveness against Wangiri fraud, a scam in which missed calls from premium numbers are used to entice victims into calling back, incurring high charges. In one instance, our AI system detected suspicious wholesale activity from a specific number range (+17846), signalling potential fraud impacting hundreds of subscribers. The AI’s prediction accuracy reached 100% in this case by matching critical data points—such as Average Call Duration (ACD), affected hours, and unallocated number ranges—with profiles from past fraud cases on which the model was trained.

AI-Driven Accuracy in Fraud Detection

Our AI model is trained using actual case data and fraud conclusions, with 90% of cases used for training and 10% for testing. The result? An impressive 98.8% accuracy in predicting voice fraud.

As we continue refining our AI fraud detection models and enhancing capabilities, we’re committed to the critical role of human insight alongside AI in protecting the telecommunications industry from sophisticated fraud schemes. Together, AI and human expertise are redefining standards in telecom fraud prevention. For a closer look at our fraud detection solutions, please visit our page.

Flowchart depicting an AI fraud detection process: training and re-training, obtaining AI predictions, and concluding fraud analysis, with corresponding visuals and icons.

Choose iCONX for your Voice Fraud Management Solution

To discuss how iCONX can support your Fraud Management please fill out our contact form or contact our experts at info@iconxsolutions.com.