CSPs slow to utilise machine learning for revenue assurance, finds WeDo survey
WeDo Technologies has announced the results of its revenue assurance (RA) and fraud management (FM) survey, which highlights that the telecoms industry is gradually recognising the benefits machine learning can bring to RA and FM, but reveals there is still progress to be made.
Conducted at at WeDo Technologies’ WDC Miami event, the survey collated the answers of 42 RA and FM professionals from 14 North American communications service providers (CSPs), with 21% stating that they are currently using some form of machine learning or artificial intelligence (AI) for RA and FM, while 28.6% revealed that they planned to do so in the future.
For mobile operators, machine learning has the potential to drive huge benefits, in particular when it comes to tackling fraud. In 2016 alone, CSPs are expected to face global fraud losses of $294 billion, making it vital that they look to utilise all tools at their disposal to combat such a pressing issue
“As the results show, operators are starting to wake up to the potential machine learning can bring to their business,” said WeDo Technologies’ CEO, Rui Paiva. “Machine learning can revolutionise RA and FM processes, and is a key tool operators should utilise to protect the bottom line. As awareness increases, we expect to see a surge in operators deploying machine learning capabilities as part of their RA and FM tools.”
Machine learning enables high-performance predictive analytics, which can help to stop fraudulent activities, such as subscription fraud, before they occur. WeDo Technologies’ system uses machine learning techniques to identify unusual patterns and correlations from disparate data sources, going far beyond traditional rule-based fraud management. By combining modern distributed system architectures with the ability to ingest massive amounts of data from new data sources, RAID FMS delivers actionable results in milliseconds, the company claims.
“The Internet of Things is proving to be a key enabler for new fraud threats, and with Gartner estimating that there could be over 20 billion connected things in use by 2020, operators need to ensure their FM systems are equipped to deal with the volume of data this will create, and the associated risks,” added Paiva. “Machine learning is able to stop fraud where it starts, by addressing the fraud enablers, making it highly effective at mitigating risk.”