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The pace of change in the telecommunications industry is accelerating with the focus on digital transformation and the next few years promises to be one of rapid growth and opportunity. Those who can keep up are primed to realize the potential of the approaching 5G wave. But to do so, telcos need to rapidly mature their digital transformation whilst paving the way for automation and simplification in an increasingly demanding marketplace.
TM Forum’s Digital Transformation North America 2019 event co-located with Action Week, brings together change-makers from the telecoms ecosystem to focus on the ‘how’ of digital enablement in a collaborative environment.
Once the conference ends, TM Forum’s Collaboration community will come together during Action Week for valuable face-to-face time to work on setting priorities, contributing to best practices and standards, and creating the roadmap for digital transformation.Find out more »
RAG returns to South Africa thanks to MTN Group, who will host our October conference at their impressive facilities in Johannesburg. The conference is scheduled for Tuesday 1st and Wednesday 2nd October. All talks will be given in English. Attendance will be free for telcos and regulators, but based on the long lines of attendees for RAG Johannesburg 2017 (pictured left) we expect to fill the venue, so book your place as soon as possible.
The conference will cover fraud, revenue assurance, cost management, nuisance calls, margin assurance, other kinds of business assurance, enterprise risk management and cybersecurity
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Dr. George Bolt of Neural Technologies will be speaking on Fraud Management & Risk Analysis Using Machine Learning
This session will discuss the importance of Digital Integration in machine learning for finding and managing fraud quicker and more effectively. Having the availability of data to train machine learning models, together with the ability to produce the same representation of data for the analysis, is key. The lessons learned from other vertical domains (banking, finance, utilities, geophysical sciences etc.) where machine learning has been profitably used extensively, are transferred to telecommunication companies. The different types of machine learning methods of supervised, unsupervised, reinforcement etc., are presented and described along with their applicability for use in telecommunications. Methodologies for successful use of machine learning are described with the key underlying factor of Data highlightedFind out more »