The mobile industry is beginning to acknowledge a need for detection methods that are able to adapt to the fast pace of evolving network crime and usage patterns. It has become increasingly evident that traditional, rules-based systems with pre-set thresholds are no longer the answer.
The industry is experiencing an increase of payment and subscription fraud, identify theft/impersonation, account takeover, insider threats, and SIM swap. The traditional usage-based fraud scenarios such as PBX or IP-PBX hacking, call-back schemes, and abuse of weak networks and devices is also on the rise.
A combined big data and machine learning approach is proving one of the most promising of the new wave of solutions. Already in use in major service provider networks, the machine learning strategy is proving exponentially more effective in fighting fraud, delivering 350 percent better results than rules-based systems, and allowing analysts to shut down attacks in instants rather than hours or days. The key is to catch them early, and stop them fast.
At TELSA we are prepared to discuss a commitment free proof of concept project on predictive analytics in fraud management or machine learning capabilities in subscription, commissions or mobile money assurance.
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Using the latest technology, industry insight, AI in combination with machine learning, we help you combat telecoms fraud on your network.
We use a unique approach that takes a holistic view of the enterprise, focused on typical areas of leakage.
Training focused on hands-on RA experience rather than tool specific training.
Training focused on hands-on RA experience rather than tool specific training.
Proactive risk management, revenue recovery and control implementation, assisting departments to improve financial performance within the business.