Who Is Holding the Card? Machine Learning for Battling Friendly Fraud/First-Party Misuse

Fraud
Attack Types
Friendly Fraud
First-Party Misuse
Machine Learning
Booking.com
Apr 05, 2022
Presentations

Defeating fraud begins with understanding fraudulent behaviors, in order to correctly identify who the fraudulent agent is behind a transaction. The differences between first and third parties constitute the foundation of fraud knowledge and this distinction is a key component in mitigating the problem in an efficient way.

Machine Learning (ML) is widely applied in the field of fraud detection, but is not often used as a way to approach post-payment fraudulent behaviors, especially for identifying what is first-party misuse as opposed to third-party fraud. 

This presentation explores the use of ML to better scale what has traditionally been a lengthy manual process of reviewing chargebacks. This contributes to the recovery process by giving insights for representing chargebacks and training adaptive detection ML models in a more efficient way.

 

Some content is hidden, to be able to see it login here Login

Blue-tinted background of a man watching a webinar

Host a Webinar with the MRC

Help the MRC community stay current on relevant fraud, payments, and law enforcement topics.
Submit a Request

Publish Your Document with the MRC

Feature your case studies, surveys, and whitepapers in the MRC Resource Center.
Submit Your Document

Related Resources

There are no related Events

X
Cookies help us improve your website experience.
By using our website, you agree to our use of cookies.
Confirm