Payoneer selects Iguazio for real-time ML

As such, by deploying Iguazio, Payoneer moved from a reactive fraud detection method to proactive prevention with real-time ML and predictive analytics. Prior to using Iguazio, fraud was detected retroactively, enabling customers to only block users after damage had already been done. However, Payoneer is now able to take the same machine learning models built offline and serve them in real-time against fresh data, thus ensuring immediate prevention of fraud and money laundering with predictive ML models identifying suspicious patterns continuously.

Moreover, Iguazio’s Data Science Platform enables Payoneer to bring its data science strategies to life. It was designed to provide a simple cloud experience deployed anywhere, and it includes a low latency serverless framework, a real-time multi-model data engine, and a modern Python eco-system running over Kubernetes.