Fraud & Risk

Machine Learning: A Silver Bullet for Fraud?

Gerry Carr, Martin Sweeney, and Stephen Whitworth - Ravelin


Machine learning is being used by a growing number of companies to reduce both fraud rates and false positives. Ravelin examines three common approaches to machine learning, as well as why supplementing machine learning with other technologies like graph networks can improve its efficacy. Drawbacks of machine learning are then shared, with insights on how to mitigate these downsides. A look at the intersection of machine learning and rules engines is then presented, with a case study in conclusion.

Note that this presentation is also available as a webinar. To view the webinar, click here.

Machine Learning: A Silver Bullet for Fraud?

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