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Detecting and Preventing Fraud with Behavioural Data and Machine Learning

Join us for an interactive virtual roundtable, with like-minded peers in the Fintech & FSI - 11:00-12:30 (BST)

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In Partnership With

Speaker

Matthew Tod
Matthew Tod
Chief Data Officer/Non Executive Director

Discussion Topics

Creating clean, high-quality behavioural data vs using data exhaust from other systems
The role of behavioural data in fraud detection
Machine learning models in fraud detection and prevention

Event Format

11:00-11:15
Introduction from all attendees
11:15-11:30
Matthew Tod - Introducing how to use behavioural data to power ML and AI models to help with fraud prevention
11:30-11:40
Live Q&A
11:40-12:30
Network with your peers over the discussion topics
12:30
Closing remarks

Event Synopsis

Detecting and preventing fraud with behavioural data and Machine Learning

Using only transactional and demographic data for fraud detection and prevention can leave your organisation vulnerable. As fraudsters are becoming more sophisticated in their attacks, machine learning models can help you detect patterns that humans can’t. But where can you get the clean, high-quality behavioural data required to power machine learning models? Join this roundtable as we discuss behavioural data creation, and using it to detect and prevent fraud.

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Event Sponsor

Snowplow generates, governs and models high-quality, granular behavioural data, ready for use in AI, ML, and advanced analytics applications. When integrated with other tools from the modern data stack, Snowplow can power a wide variety of advanced use cases, allowing organizations to drive significant business value with behavioral data.

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