Case Study: Global Financial Company achieves $50M+ annual cost savings with EdgeVerve's real-time fraud detection

Global Financial Company - Customer Case Study

Global Financial Company needed to detect and block fraudulent transactions in real time to avoid the high costs and customer impact of fraud. EdgeVerve was engaged to deliver a real-time fraud detection solution, using a fully non-linear supervised machine learning model trained on historic data to score incoming transactions and surface the most predictive variables.

EdgeVerve deployed the model to assign fraud probabilities in real time, record dataflows for regulatory compliance, and handle the highly imbalanced datasets typical in fraud detection; models are updated daily rather than annually. The solution delivered measurable impact: over $50M in annual cost savings, a 10% lift in accuracy and improved customer satisfaction, plus transparent insights into fraud drivers and a full audit trail.