A mobile provider decreased subscription fraud by 30%

Despite an implemented rule-based system and background check for new customers, one of the top Czech mobile providers suffered from subscription fraud (customers not paying for services and hardware) and struggled to reduce it.
We have applied our own machine learning fraud detection framework ML FDS to enhance risk management and empower the fraud prevention process with AI. Our framework works in synergy with the client's rule-based system as an additional security layer on top, making it easy and cost-effective. Machine learning looks at data from multiple angles, spots complicated fraud patterns, and prevents them in the future. As a result, your fraud prevention is robust, precise, resistant, and adaptive. In addition, anomalies identified by ML FDS are presented in intuitive dashboards, facilitating quick data-driven decision-making and efficient fraud solving.
Thanks to ML FDS enhancing risk management and empowering the fraud prevention process with AI, the provider prevented roughly 30% of fraud, which secured an ROI within the 1st year. The system adapts itself to new fraud automatically as new data arrives.

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