Case Study: Creditstar Group AS achieves 30% more approved customers and faster, higher-quality credit decisions with Microsoft Azure Machine Learning

The biggest advantages of Azure are a cloud-based platform, the speed of integration, and personality

Creditstar Group, an Estonia-based fintech and leading consumer credit provider operating in eight European countries, needed a dynamic, cloud-based system to assess creditworthiness and predict payment defaults. Many off-the-shelf options required high fees or on-premises infrastructure, so Creditstar prioritized a cloud platform with fast integration, volume-based pricing and reliable support.

Creditstar implemented Microsoft Azure Machine Learning (Machine Learning Studio) in early 2016, building, training and deploying a scoring model — moving from account registration to production in about four days. The solution accelerated and improved credit decisions while keeping human oversight, enabled easier market expansion (notably into Spain), increased approved applicants by roughly 30% and significantly reduced bad loans, delivering time savings, strong support and security.

Creditstar Group AS

Virgo Riispapp

Head of IT