Case Study: Clicklease achieves sub-second real-time credit and fraud decisioning with Hopsworks

Clicklease achieves sub-second real-time credit decisions with Hopsworks

Clicklease, a U.S.-based fintech company providing micro-leasing solutions, faced significant challenges scaling its machine learning workflows. Its existing architecture was plagued by high latency from database scans, inconsistent feature transformations, and a heavy operational burden for its lean team. To modernize its real-time fraud detection and credit decisioning system, Clicklease adopted the Hopsworks Feature Store.

By implementing Hopsworks, Clicklease gained a centralized platform for managing features and serving models. The solution enabled on-demand feature computation, achieving sub-second latency for real-time decisions. Hopsworks provided a unified feature schema for both training and inference, which eliminated training-serving skew and simplified model operations. This resulted in faster, more reliable credit approvals and a significantly reduced operational overhead for their engineering team.

Clicklease