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Machine Learning for Fraud Detection - Modern Applications and Risks

Machine Learning for Fraud Detection - Modern Applications and Risks

FromThe AI in Business Podcast


Machine Learning for Fraud Detection - Modern Applications and Risks

FromThe AI in Business Podcast

ratings:
Length:
28 minutes
Released:
Jun 25, 2017
Format:
Podcast episode

Description

Fraud attacks have become much more sophisticated. Account takeovers are happening more often. Many security attacks involve multiple methods and unexpected attacks can devastate businesses in just a few days, as we saw with Neiman Marcus and Target. False promotion and abuse is seen not only on social media sites but is also targeted at business. To combat these risks, fraud solutions need to be smarter to keep pace with fraudsters to prevent attacks and react quickly when they do happen. This requires a fast-learning solution with the ability to continually evolve. In this episode we talk to Kevin Lee from Sift Science and examine the shifts in the info security landscape over the past ten or fifteen year. Lee also highlights what new kinds of fraud are now possible and what machine learning solutions are available. See more episodes at: www.TechEmergence.com  
Released:
Jun 25, 2017
Format:
Podcast episode

Titles in the series (100)

Learn what's possible - and what's working - with artificial intelligence in the enterprise. Each week, Emerj founder Daniel Faggella interviews top AI and machine learning-focused executives and researchers in sectors like Pharma, Banking, Retail, Defense, and more. Discover trends, learn about what's working now, and learn how to adapt and thrive in an era of AI disruption. Be sure to subscribe to "AI in Industry."