Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
R Deep Learning Projects

You're reading from   R Deep Learning Projects Master the techniques to design and develop neural network models in R

Arrow left icon
Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788478403
Length 258 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (2):
Arrow left icon
Yuxi (Hayden) Liu Yuxi (Hayden) Liu
Author Profile Icon Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
Pablo Maldonado Pablo Maldonado
Author Profile Icon Pablo Maldonado
Pablo Maldonado
Arrow right icon
View More author details
Toc

Credit card fraud detection with autoencoders

Fraud is a multi-billion dollar industry, with credit card fraud being probably the closest to our daily lives. Fraud begins with the theft of the physical credit card or with data that could compromise the security of the account, such as the credit card number, expiration date and security codes. A stolen card can be reported directly, if the victim knows that their card has been stolen, however, when the data is stolen, a compromised account can take weeks or even months to be used, and the victim then only knows from their bank statement that the card has been used. 

Traditionally, fraud detection systems rely on the creation of manually engineered features by subject matter experts, working either directly with financial institutions or with specialized software vendors. 

One of the biggest challenges in fraud detection...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime