Machine learning supports fraud prevention in the telecommunications industry

Challenge

A top German provider of telecommunications contracts and hardware regularly has to contend with unpaid invoices from its customers for contracts involving hardware, as this causes severe financial damage to the company. The goal and challenge was to predict these fraud cases as best as possible and prevent them accordingly.

Solution

With the help of a supervised machine learning pipeline including customized feature engineering, it is possible to predict whether future invoices can be paid or not based on various customer information in combination with payment history.

Added value

  • 90% of all unpaid contracts are reliably detected.

Highlights

  • Data from six different online stores from one year as well as other data sources, including device, product and customer information such as past purchases.
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