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Argyle Data: Drowning in Data, Telcos Turn to Machine Learning to Provide Actionable Analytics

By   /  January 5, 2017  /  No Comments

by Angela Guess

A new press release out of Argyle Data reports, “In 2017, machine learning will become a mainstream tool for communications providers struggling to transform data overload into actionable analytics, according to Argyle Data. ‘The telecommunications industry is drowning in data,’ said Padraig Stapleton, Vice President of Engineering at Argyle Data. ‘Functions like support, billing, customer care and marketing, throwing off large amounts of data as a by-product of their activities, the exhaust fumes of data. Fraud and financial analysts alike are overwhelmed by the struggle to control and harness this fire-hose of information into actionable analytics. There is just too much IP traffic going across mobile networks for humans to review, detect and respond to fraud in the traditional ways (e.g. discovering fraud and writing preventative rules). Machine learning does all the grunt work for analysts, sifting through data in real time and providing output instantly in understandable, accessible formats’.”

THe release goes on, “Based on customer feedback, Argyle Data says the following rank among the top communications service provider (CSP) concerns for 2017: Subscription fraud and dealer fraud: these are currently the most prominent fraud issues plaguing mobile operators, the complexity of the fraud, the volume of data and the need to need to react in real time all require machine learning to stop the revenue bleed. Fraud using mobile data services and IP applications will absorb greater amounts of CSP focus. Call bypass: the growing popularity of voice and video calling from applications such as WhatsApp, WeChat and Viber will have an increasingly significant impact on carriers’ revenues. Mobile voice is going the way of the dodo. Most smartphone conversations today take place over IP; data-only phones and plans are becoming more mainstream worldwide.”

Read more at Marketwired.

Photo credit: Argyle Data

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