Open Source Powered Real-Time Fraud Analysis in a Hybrid Cloud Environment

Explore real-time fraud analysis in a hybrid cloud environment through this conference talk. Discover how open source and closed source technologies can be combined to build and train AI models for fraud detection in the cloud, then deploy them for real-time analysis on mainframes. Learn about using TensorFlow for model training, persisting models in ONNX format, and leveraging IBM's Telum AI Accelerator for high-scale, in-transaction inference. Gain insights into overcoming challenges in AI adoption, securing data in compliance with financial industry regulations, and applying this hybrid approach to various use cases beyond fraud detection. Understand the AI lifecycle, from data sourcing to deployment, and explore the role of open source technologies in solving real-world problems across industries in a hybrid multi-cloud environment.