Effective Identity Fraud Prevention and Detection with Machine Learning

Presented by

Kevin King, ID Analytics, Clyde Langley, Charles Schwab, Wayne Shoumaker, Wells Fargo and Joe DeCosmo, Enova International

About this talk

The rise of machine learning technology in recent years has provided businesses, particularly financial institutions, with advanced capabilities in preventing and detecting identity fraud at account opening. However, there are many arguments regarding the best practices in identity fraud defense, including the role of machine learning in pinpointing risks. The message is clear: a strong fraud defense requires machine learning, but equally requires strong underlying data and well-practiced fraud operations procedures to make it effective. Businesses should consider a number of factors before moving forward with a machine learning-based fraud detection and prevention solution. In this Webcast, a seasoned panel of thought leaders and professionals will provide and present an in-depth analysis of employing machine learning in detecting and preventing fraud. Speakers will also provide practical tips and strategies to ensure that potentials are maximized, and pitfalls are mitigated.

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