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ABOUT THIS WEBINAR
As financial fraud becomes faster, more adaptive, and harder to detect, financial institutions are rethinking how they build and scale machine learning systems for real-time fraud detection. Achieving this requires not just smarter models—but the right data infrastructure to power them.

In this session, we’ll explore how PayPal, Barclays, and TransUnion built AI-driven fraud detection systems that can process thousands of signals across transactions, customer history, and behavioral patterns—in milliseconds. Learn how they achieved a 30x reduction in fraud exposure and cut infrastructure costs by up to 80%.

Whether you’re building fraud models, scaling real-time ML inference or rolling out generative or agentic AI projects for improving fraud detection, this session will equip you with practical guidance to elevate your fraud detection systems.
AGENDA
  • Proven strategies to reduce false positives and false negatives—without increasing customer friction
  • Architectures for real-time machine learning inference at scale
  • New approaches using graph analytics, generative and agentic AI to uncover hidden fraud patterns faster
ADDITIONAL INFO
  • When: Eastern Time (US & Canada)
  • Duration: 1 hour
  • Price: Free
  • Language: English
  • Who can attend? Everyone
  • Dial-in available? (listen only): Not available.
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