Revenue loss and fraud

Nokia Revenue loss and fraud uses machine learning anomaly detection and behavioral profiling, combined with traditional analytics and visualization, to detect and surface revenue loss and/or fraud.

The Nokia difference

Revenue loss due to fraud, theft, or asset failure is a problem for most asset-intensive industries. Often the hardest part of stopping these losses is finding out they are happening in the first place, and pinpointing the specific point of loss in the network. Nokia Revenue loss and fraud will root out the problems causing your revenue loss.

Detect, quantify, and locate non-revenue usage

The first step in stopping revenue loss is understanding you have a problem. Nokia’s visual analytics help makes sense of huge amounts of data so you can intuitively understand the size and scope of the problem. Then, our machine learning analytics go to work finding the needles in the haystack, pinpointing the points of loss in time and space, and recommending courses of action to remedy the cause of loss.


Detect fraud

Fraudulent activity may come from inside or outside your organization. Either way, analytics can detect it and stop it. Using advanced anomaly detection and machine learning profiling, our applications will find fraudulent activity and help predict risk for fraud within your organization.

Improve cybersecurity

For all the benefits of the Internet of Things, the dark side is the potential for infiltration of networks and damage to assets and operations. Nokia’s machine learning analytics monitor networks in real time, detecting anomalous activity and asset behavior.


Electricity utilities
Natural gas utilities
Renewable energy generators
Water utilities

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