Case Study: Ezapp Payment Frauds Detection achieves 99% fraud detection accuracy and real-time prevention with Ezappsolution

Ezapp Enterprise Payments Fraud uses advance Deep learning AI models

Ezapp Payment Frauds Detection, a payments-focused organization facing rising loan and credit-card transaction fraud across channels and in open banking, needed a timely, accurate way to detect and govern suspicious payments. Ezappsolution addressed this with its Ezapp Enterprise Payments Fraud / Ezapp Payments Fraud solution, leveraging TensorFlow-based deep learning, behavioral profiling and anomaly detection to provide end-to-end fraud management for card and electronic payments.

Ezappsolution implemented adaptive AI models, real-time interdiction to block suspicious payments, and automated monitoring and investigation workflows. The deployment delivered measurable impact—up to 99% fraud detection accuracy in transaction screening, faster real-time stoppage of fraudulent payments, reduced investigation time and cost, and improved risk governance and customer experience.