Fraud & Risk
Machine Learning: A Silver Bullet for Fraud?
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Machine learning is being used by a growing number of companies to reduce both fraud rates and false positives. In this webinar, 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 discussed, 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.
Slides from this webinar are available here.