MTN turns to AI to catch gigabyte thieves
The telco uses AI to catch revenue leakage from data tunnelling and to understand how customers actually use its network.
MTN South Africa is leveraging artificial intelligence (AI) to bolster its network management, particularly in identifying and combating revenue leakage. CEO Ferdi Moolman highlights that the adoption of AI has surged, as it provides practical solutions across the business, notably in the area of revenue assurance. This application involves pinpointing potential revenue loss, which is achieved by detecting suspicious activities such as data tunnelling.
Tunnelling is a technique employed by fraudsters to circumvent mobile operators' charges for data usage, especially on zero-rated sites like university websites. The Independent Communications Authority of South Africa (ICASA) initially mandated such zero-rating during the COVID-19 pandemic to ensure free access to essential government and educational sites.
However, this led to an uptick in data tunnelling, as highlighted in MTN's submission to ICASA in November 2021. Moolman explains that while zero-rating sites presents challenges due to the ease of tunneling, AI helps identify and focus on specific sites where suspicious behavior is likely. In addition to revenue assurance, AI is being employed to examine usage patterns across MTN's network.
This involves anonymizing data in a secure environment to derive insights that would otherwise be challenging to glean manually from the vast amount of information generated. Moolman elaborates that this analysis offers a clearer picture of which online services consume the most data and the origins of network traffic. This capability extends to geographical analysis, such as in Sandton, where the mix of residential and office users complicates traffic assessment.
Furthermore, AI enables MTN to revisit strategies akin to MTN Zone, launched in 2008, which utilized dynamic per-second tariffs to offer location-based discounts. However, applying this concept to the complex data landscape, especially with the coexistence of various mobile technologies like 3G, 4G, and 5G, necessitates the use of AI.
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