CubX – a new machine learning solution by efcom – allows for detection with an accuracy of 90,7% of problems in the factoring ecosystem.
The solution uses state-of-the-art machine learning algorithms to analyze data, including credit scores, financial statements, and customer payment history. While most risk-preventing instruments offer such or similar functionalities with historical data sometimes older than one year, CubX does risk-preventing with data from today, from now, and in real time. This allows us to predict the likelihood of late payments or even default accurately. In this way, efcom enables clients to uncover various risks, but also potential opportunities by clients, debtors, industries, or regions at an early stage in the respective factor’s ecosystem.
Here you can read more about CubX by efcom and vote for that solution
During that dedicated webinar, Federico Avellan Borgmeyer (Chief Partner Officer and Member of the Management Board at efcom) presented their solution in detail.
Interested? Watch the webinar’s recording below ↙️↙️
SPEAKERS:
Federico Avellán Borgmeyer
Chief Partner Officer & Member of the Management Board at efcom (Germany)
Olena Gryniuk
CEE Director at SME Banking Club
Founder & CEO at WOA.digital
Watch webinar recording:
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