
Fraud Management System
Fraud Detection Enhanced with Machine Learning
Beyond traditional types of voice fraud, such as Revenue Share Fraud (IRSF) and Wangiri (missed call) fraud, fraudsters have begun to leverage SIP architectures for fake call centers and robocalls which has led to major damage for mobile subscribers.
Fraudulent activity has caused a dramatic drop in legal enterprise voice traffic, leading to multiple regulator initiatives on preventing Caller ID spoofing and robocalling. This problem is not limited to any geography and is slowly spreading across Europe, Asia, and the Middle East, as regulators prepare to step in and force Communications Service Providers (CSPs) to take action.
Mavenir has introduced the Mavenir CallShield solution to address growing challenges with Mobile Voice Communication Services. Mavenir’s CallShield leverages the Mavenir Fraud and Security Suite framework.
With years of AI/Real-Time Machine Learning (ML) and live call screening capabilities to identify malicious call attempts, CallShield provides CSPs with controls to minimize voice fraud damage, protect subscribers, and revenue.
CSPs can no longer rely on using only rules and thresholds for detection, as fraudsters themselves are using state-of-the-art technology to avoid detection such as artificial intelligence to change behavior in real-time and CLI Spoofing for more successful Robocall attacks.
By using Mavenir’s native ML algorithms to identify fraud and other anomalous network behavior, reliance on rules can be avoided, providing higher accuracy, lower false positives, and the knowledge that known, future, and unknown types of fraud will always be quickly identified. CallShield’s framework allows flexible control of all processing and decision stages via rules leveraging both ML and Rule-Engine technologies.
CallShield is delivered with three ML models to automatically detect and classify behavioral anomalies across voice fraud (IRSF, Wangiri), robocalling, and call centers.
CallShield’s ML supports dedicated features for fraudulent call centers, operating from dedicated bases and generating mass nuisance calls to subscribers. These call centers are often focused on specific frauds or scams.
ML features support dedicated detection of these call centers in operation, including outbound call rate, declining call rate, voicemail durations, and call origin.
Mavenir has brought the latest in detection together from 10+ years of proprietary Machine Learning technology, enhanced with a fully scalable and highly adaptable solution suitable for CSPs, MNOs, MVNOs, and wholesalers alike.