UTCS Colloquium/AI-Tal Tversky/Apple: "Detecting Online Credit Card Fraud: A Data Driven Approach," ACES 2.402, Thursday, February 11, 2010, 11:00 a.m.

Contact Name: 
Jenna Whitney
Date: 
Feb 11, 2010 11:00am - 12:00pm

There is a sign-up schedule for this event that can be found
at http://www.cs.utexas.edu/department/webeven

t/utcs/events/cgi/list_events.cgi

Type of Talk: UTCS Collo

quium/AI

Speaker/Affiliation: Tal Tversky/Apple

Date/Time:

Thursday, February 11, 2010, 11:00 a.m.

Location: ACES 2.402

Host: Risto Miikkulainen

Talk Title: Detecting Online Credit

Card Fraud: A Data Driven Approach

Talk Abstract:

A consisten

t problem plaguing online merchants today is the
growth and evolution

of online credit card fraud. Thieves
harvest credit card numbers from

a myriad of sources, place
online orders from all over the world, an

d ship to countless
drop locations. Current estimates place the proble

m at 1 to
1.5 billion dollars annually of which the online merchant
holds complete liability.

In this talk, I will describe the

problem of eCommerce fraud
and outline various detection measures that
online merchants
employ. Like many merchants, Apple Computer leverag

es
techniques from data mining, machine learning, and statistics
to efficiently discover fraud patterns and adapt to new
trends. Some
topics that I will discuss include evaluating
fraud patterns in histo

ric data, building fraud predictive
models, inferencing through orde

r linkages, and anomaly
detection.

Speaker Bio:

Dr. Tal Tversky is a Data Mining Scientist at Apple, Inc.&nbsp

; He received
his Ph.D. in Computer Science from the University of Tex

as at Austin
in 2008.  At Apple he works primarily on fighting o

nline credit card
fraud, but he has dabbled in forecasting sales and

inventory
optimization.