Detect Fraud in Real Time. Protect Every Revenue Stream.

We combine AI and DPI-powered intelligence to detect, score, and neutralize fraud across voice, SMS, data, roaming, and signaling before revenue losses escalate.

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Challenges

Industry Challenges

Telecom Fraud Creates Revenue Losses in Real Time

SIM box operations, international bypass, premium-rate abuse, and other fraud schemes can drain revenue long before retrospective reporting identifies them.

Fraud Increasingly Crosses Network and Service Domains

Sophisticated schemes span voice, SMS, data, roaming, and signaling, making isolated detection systems less effective.

Static Rules Miss Emerging Fraud Patterns

Fraudsters continually change behavior to avoid established thresholds and signatures, requiring intelligence capable of identifying zero-day patterns.

Revenue Leakage Is Difficult to Quantify and Investigate

Fraud teams need contextual evidence, financial impact analysis, and structured investigation workflows—not simply another stream of alerts.

Product Overview

AI and DPI-Powered Fraud and Revenue Protection

Our Fraud & Revenue Assurance platform identifies, scores, and neutralizes fraud in real time across voice, SMS, data, roaming, and signaling channels. DPI analyzes application-layer traffic for fraudulent signatures, including SIM box codec patterns, bypass route indicators, OTT tunnel characteristics, and abnormal data consumption profiles.
AI/ML models simultaneously evaluate behavioral, signaling, and DPI-derived features to score fraud probability and identify established and zero-day fraud patterns. Integrated case management, AI-assisted investigation workflows, revenue leakage quantification, and forensic reporting provide a unified environment for fraud operations.

The Outcomes Are Clear

01 Earlier fraud detection

02 Lower revenue leakage

03 Greater control over every investigation

Capabilities

Product Capabilities

Cross-Domain Fraud Detection

Detect and neutralize fraud across voice, SMS, data, roaming, and signaling through unified, real-time intelligence.

SIM Box and International Bypass Detection

Identify SIM box codec patterns, route anomalies, and traffic characteristics associated with international bypass and interconnect fraud.

OTT Bypass Intelligence

Use DPI to identify OTT tunnel characteristics and traffic patterns associated with bypass activity and potential revenue leakage.

AI/ML Fraud Probability Scoring

Combine behavioral, signaling, usage, and DPI-derived features to calculate fraud probability and prioritize suspicious activity.

Zero-Day Fraud Detection

Apply continuously learning AI models to identify emerging fraud techniques and behavioral patterns that rule-based systems can miss.

Multi-Scenario Fraud Protection

Detect SIM box, international bypass, OTT bypass, roaming fraud, premium-rate abuse, Wangiri, subscription fraud, and emerging fraud patterns from a unified platform.

AI-Assisted Investigation

Correlate network, behavioral, signaling, and DPI-derived evidence to accelerate fraud investigation and root-cause analysis.

Revenue Leakage Quantification

Measure the financial impact associated with identified fraud and leakage to prioritize cases according to potential revenue exposure.

Integrated Case Management

Centralize fraud alerts, evidence, analyst activity, investigation workflows, and case status within a common operational environment.

Forensic Reporting and Tamper-Proof Audit Trails

Generate detailed forensic reports and maintain tamper-proof audit trails to support investigation, governance, and evidentiary requirements.

Process

How It Works

Analyze Cross-Domain Activity

We continuously analyze voice, SMS, data, roaming, signaling, and application-layer traffic across the telecom environment.

Identify Fraud Indicators

DPI detects fraudulent traffic signatures, while behavioral and signaling intelligence identifies abnormal usage, routing, and subscriber patterns.

Score and Detect Fraud

AI/ML models evaluate behavioral, signaling, and DPI-derived features simultaneously to calculate fraud probability and identify known and zero-day patterns.

Quantify and Prioritize Exposure

Potential revenue leakage is calculated, and cases are prioritized according to fraud probability, supporting evidence, and financial impact.

Investigate, Respond, and Learn

AI-assisted workflows accelerate investigation, forensic reporting preserves the evidence trail, and confirmed fraud cases continuously strengthen detection models.

Results

Key Outcomes

Reduced Revenue Leakage

Detect and neutralize fraudulent activity earlier to limit avoidable financial losses across telecom services.

Real-Time Fraud Protection

Move beyond retrospective revenue assurance by identifying and responding to fraud as suspicious activity occurs.

Greater Zero-Day Detection

Identify emerging fraud patterns that static rules and previously known signatures may not recognize.

Better Investigation Prioritization

Focus fraud teams on cases with the highest fraud probability and greatest potential financial exposure.

Faster Fraud Investigation

Use AI-assisted workflows and correlated evidence to reduce manual analysis and accelerate case resolution.

Stronger Financial Visibility

Quantify revenue leakage to understand the commercial impact of fraud and prioritize protection efforts accordingly.

Greater Forensic Control

Maintain detailed reporting and tamper-proof audit trails across fraud investigations and operational actions.