Revenue Threat Analytics for Mobile Providers

Our native Hadoop applications use the latest big data and machine learning technologies to quickly identify previously unknown revenue threats.

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“Real-Time Anomaly Detection in Streaming Cellular Network Data”

A joint research paper from Argyle Data and Carnegie Mellon University on how to use machine learning to identify anomalous activity in telecom networks.

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Revenue threats are currently a $38 billion criminal business.

Leading mobile operators understand that data is a massively underutilized asset, and they understand the enormous potential revenue impact of big data analytics and machine learning. That’s why the leading mobile operators partner with Argyle Data to gain visibility into the revenue threats and attack patterns being waged against their networks – threats that, on average, cost 2% of revenue.

Argyle Data’s revenue threat analytics applications quickly identify attack points and potential losses.

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