Sprint calls on open source analytics to prevent cyberfraud

Sprint’s open source Elastic Stack analytics implementation helped the mobile device and network provider reduce mobile phone fraud by 90 percent.

Sprint calls on open source analytics to prevent cyberfraud
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Mobile phone-related fraud is big business. Fraudsters, hackers, and other bad actors employ creative techniques to compromise networks, hijack user information, and piece together customer identities that are then sold for big bucks on the dark web. To protect its customers, Sprint needed to transform the way it detected and blocked fraudulent activity.

“In the mobile phone business, there’s no markup on selling devices — our bread and butter is the network and the services that are delivered on that network, through the devices,” says Scott Rice, CIO of Sprint. “Identity theft is a huge problem and the ability for nefarious actors to use that theft of information to impersonate our customers means we were eating the costs of the devices and the costs of services delivery.”

Sprint’s fraud management team, led by Helen Schallenberg-Tillhof, director of fraud management, with support and guidance from Rice and members of IT and the company’s project management and compliance divisions, knew they needed a better way to quickly identify and stop fraudulent activity before customer data was exposed. By implementing a set of open source monitoring, data analysis, and search tools using Elastic Stack, Sprint was able to identify, search, monitor, and analyze data from multiple sources and formats. The anti-fraud system, which received a CIO 100 Award in IT Excellence, has completely transformed how Sprint detects and blocks fraudulent activity, Rice says.

The power of open source

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