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:
Wednesday, August 27, 2025 · 2:00 p.m.
Eastern Time (US & Canada)
The Data Science Salon has been providing unique content and a diverse, vendor neutral community to data scientists, machine learning engineers and other subject matter experts since 2016.
Srinivasan "Sesh" Seshadri is the Chief Evangelist at Aerospike. Sesh is a veteran technology leader with over three decades of experience spanning academia, startups, and large companies. Sesh is an accomplished expert in databases with over 50...
The DATA SCIENCE SALON is a unique vertical-focused data science conference that grew into a diverse community of senior data science, machine learning, and other technical specialists. We gather face-to-face and virtually to educate each other, illuminate best practices and innovate new solutions in a casual atmosphere.