UTCS AI Colloquia - Dr. Greg Kuhlmann and Dr. Jefferson Provost, Apple, "Fraud Prevention for eCommerce: A Data Driven Approach" PAI 3.14

Contact Name: 
Craig Corcoran
Location: 
PAI 3.14
Date: 
Mar 27, 2013 11:00am - 12:00pm

Signup Schedule: http://apps.cs.utexas.edu/talkschedules/cgi/list_events.cgi

Talk Audience: UTCS Faculty, Grads, Undergrads, Other Interested Parties

Host:  Peter Stone

Talk Abstract: A consistent problem plaguing online merchants today is the growth and evolution of online credit card fraud.  Multi-million dollar organized crime rings use stolen credit card numbers to steal and re-sell both physical and digital goods.  The recent emergence of transferable digital goods such as gift certificates and in-game currencies means that risk decisions must be made in fractions of a second on enormous transaction volumes.  In addition, pervasive use of online credentials linked to payment instruments extends the scope of the problem to online identity theft.   The problem is highly adversarial, with fraudsters capable of adapting to and overcoming unsophisticated prevention measures within days or even hours.

In this talk, we will describe the problem of eCommerce fraud and outline various detection measures that online merchants employ. Like many merchants, Apple leverages techniques from data mining, machine learning, and statistics to identify fraud patterns and adapt to new trends. Some topics that we will discuss include evaluating patterns in historical data, building predictive models, inferencing through transaction linkages, active learning and anomaly detection. 

Speakers Bios: Dr. Jefferson Provost received his Ph.D. from the UT AI Lab in 2007, where he studied machine learning for robot navigation.  Since then he has worked applying machine learning for account protection and fraud detection at Amazon.com and Apple, Inc.

Dr. Greg Kuhlmann received his Ph.D. from UT Austin in 2010 under the supervision of Dr. Peter Stone.  His graduate work included reinforcement learning, robotics and general game playing.  In industry, he has applied machine learning to communication link analysis for national defense, network anomaly detection and fraud prevention at 21CT and Apple, Inc.

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