How Performance in the Telecom Payment ecosystem is empowered by Data…

Today, following the increasing smartphone penetration rate, Telecom Payment has become one of the most deployed payment methods in the world. The rise of Data centric analysis has impacted performance and risk management and plays an increasingly important role in the ecosystem.

Data is an essential lever  

The binding link between Telecom Operators and its customers has induced the need for trustworthy connection to ensure a sustainable ecosystem. Data is considered a valuable resource for reaching this objective. Big Data collection enables revenue generation monitoring and facilitates bugs identification. Beyond this, Data is also an essential tool for setting alerts and thresholds in case of fraudulent activity. Big Data collection, acquired through 5 billion transactions processed each year by Digital Virgo, is a valuable asset for reaching our industry’s objectives.  

Data as a ROI booster 

Data is extensively used for risk management and monitoring; it is also extremely valuable for performance management. Billing metrics can be isolated with a granular approach thanks to the Data collected through the voluminous transactions. It gives in-depth analysis and detailed insights to the partners so they can manage a sustainable and safe ecosystem. 

Data as a safeguard 

Fraud and illegal transaction in the Digital Economy is a growing concern for the Telecom Payment ecosystem. Data gathering throughout the conversion funnel, its analysis and visualization has enabled the industry to adapt to the risk. Optimized awareness on these topics has had a significant impact, but fighting against fraud remains an on-going process.  

Increased data awareness  

Our Partners, whether it’s Telecom Operators or Merchants, seek insights, views or KPIs to track their activities, reach better analysis of their billing performances and boost their revenues. In addition to third party solutions, Digital Virgo’s Data Teams continuously develop new classification algorithms based on Partners’ transactional Data and share findings.  

As uncovered above, with the expansion of Data centred analysis, Data awareness has evolved rapidly in the industry. Before this expansion, data was more of a reporting tool. It now supports performance enhancement and goes beyond classic dash boarding. This volume of Data provides new opportunities for development of predictive models and machine learning tools to meet pre-set goals.  

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