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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)


In Partnership With


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

Introduction from all attendees
Matthew Tod - Introducing how to use behavioural data to power ML and AI models to help with fraud prevention
Live Q&A
Network with your peers over the discussion topics
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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Why Kinetic Alliance

We provide a platform for you to learn from your peers, in a closed door environment, using key discussion topics to drive thought leading engagement.
Take the opportunity to benchmark what you’re doing with your peers, discussing common challenges and actionable outcomes.
Our tailored format is designed for you to collaborate with industry leaders, as well as gain insight into innovative solutions in a relaxed environment.

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