Our world is becoming ever more complex and fast-moving. Generalised, universal processes are increasingly being superseded by tailored solutions. We are also pursuing this approach at EOS by using various criteria to assess our debtors’ specific situations and developing customised solutions on the basis of our findings. This has already proved successful in our day-to-day collection business and will be the central method of controlling in FX, our future core system.

Knowing today
what debtors will do tomorrow

Taking the best action at the right time is a key factor in EOS’s success. In order to ensure this success both today and in the future, we use state-of-the-art machine learning algorithms in developing analytical models for data-driven forecasting. Analyses and solutions for the best next step as designed by data science experts are used in collection controlling to ensure optimal collection performance, including in the long term.

Our data scientists implement these solutions in line with accepted best practice and programming standards. In doing so, they benefit from the infrastructure and the software development and operating processes of the Analytical Platform, which combines high-performance computing hardware with infrastructure and management software. The platform is developed by the team from The Data Works at the EOS Holding Center of Analytics in close cooperation with its users.


We perform extensive testing with a view to answering analytical questions and continuously improving the collection process. This involves working in close cooperation with professionals from various fields in order to collect new insights and ensure that EOS remains on the right track.

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