Machine learning in 2017 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, VP 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.”
Stapleton said 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 such as 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,” said Stapleton.
Based on customer feedback, Argyle Data said the following rank among the top communications service provider (CSP) concerns for 2017 — subscription fraud and dealer fraud; fraud using mobile data services and IP applications; call bypass; mobile voice is going extinct; identifying, analyzing and monetizing IP-based traffic; and the explosion of IoT devices across communications networks.
“These issues can only be addressed if CSPs have better insight into voice and data traffic passing through their networks,” added Stapleton. “New machine learning algorithms give them the ability to respond rapidly to new trends, anomalies or threats.”