The challenge

Without the extensive historical records of longer-established providers, Madrileña Red De Gas asked how advances in data analysis and the Internet-of-Things could be applied to the production of accurate and actionable data on non-technical losses. Most importantly, the new intelligence would need to ensure that the field teams paid to track down suspect usage could radically improve the success of local inspection.

The solution

The ability to combine Madrileña Red De Gas sector expertise with Atos analytics skills and resources was key to the success of the initiative. Working with usage data provided by their client, Atos used the advanced Atos Codex frameworks to design and build the set of algorithms needed to deliver the initial analysis.

Business benefit

The analytics process is continuous. The results of the first round of application are fed back for the second cycle, ensuring that results and tools are continuously refined for ever-better results. This iterative cycle of analysis is handled by the Atos Codex data scientists to deliver clear client benefit.

With the second wave of inspection, for example, Madrileña Red De Gas raised the hit rate, taking it from 20% to 30%. Since partnering on this new analytic approach to fraud detection, however, Madrileña Red De Gas has done more than increase their success rate.