In this week’s issue of Business Weekly, Dave Excell, founder and CTO at Featurespace, talks about how the company leverages its U.K. roots to innovate the fight against payments fraud in the U.S.
The U.K. has an illustrious track record of introducing revolutionary innovations, including the Atlas (heralded as the world’s first supercomputer), the first portable computer, the first laptop (the Osborne 1 and the Grid Compass, respectively) and even the World Wide Web.
Dave Excell explains how Featurespace – also born out of the U.K. – leverages its rich fraud detection and prevention experience to help organizations in the Americas, and also how this supports the company’s mission to risk score every transaction on the planet.
About the author:
Dave is an experienced technology innovator with over 18 years dedicated to the study of engineering. He founded Featurespace in 2008 and has since grown the company from a concept to a commercial success.
An expert in fraud-fighting technology, Dave has received several accolades including the ITC Enterprise Award for Young Entrepreneur and has spoken at conferences and to media around the world.
More from Dave:
No Stranger to Innovation: How the U.K. is Revolutionising the Fight Against Global Payments Fraud
No Stranger to Innovation: How the U.K. is Revolutionising the Fight Against Global Payments Fraud
Podcast: Dave Excell talks payments fraud, machine learning and expansion to the U.S.
Podcast: Dave Excell talks payments fraud, machine learning and expansion to the U.S.
Will PSD2 Be AI’s Big Break In Fighting Payments Fraud?
Will PSD2 Be AI’s Big Break In Fighting Payments Fraud?
Digital Transactions: Convenience And Security Require Education And Technology
Digital Transactions: Convenience And Security Require Education And Technology
Using Adaptive Behavioral Analytics to Detect Fraud
Using Adaptive Behavioral Analytics to Detect Fraud
The difference between Machine Learned models and Machine Learning models
The difference between Machine Learned models and Machine Learning models