Fraud detection for E-commerce
Us-based client
We help our US-based client build patented technology that guards your company and workflow and minimizes duration wasted on mechanically revision operations and transactions. It’s easy to set up and it’s already used by more than 80 thousand merchants.
Our team created a non-linear, monitored machine learning model. The pattern identified fraud in real-time. We try to build a model for highly imbalanced data that are regular for this market. We used a mix of Classification methods like Random Forest, Bootstrap, Catboost, and LightGBM and implemented about 80 features.