Firm highlights how EMV liability shift and data breaches are contributing to increasing online fraud

iovation, the provider of device intelligence for authentication and fraud prevention, today announced it will host a webinar entitled “Fighting CNP Fraud: 5 Things to Consider” on April 27, 2016 at 7am and 10am PDT. In the webinar, iovation’s Eddie Glenn will walk through a real-world card-not-present (CNP) fraud case and discuss how advanced device intelligence helped stop a fraud ring that was using stolen identities.

“In the U.S., we’re seeing a sharp rise in CNP fraud following the widespread implementation of EMV, or chip and PIN, cards last fall,” said Glenn. “Also contributing to the increase is recent major data breaches that have made stolen information available to cybercriminals.”

With the EMV shift underway in the U.S., fraudsters are increasingly migrating online for their schemes, as they did previously in other countries. For instance, after France implemented EMV cards it saw card-present fraud drop by 35 percent between 2004 and 2009, but domestic CNP fraud losses increased more than 360 percent in that same time span.

In addition to explaining how CNP fraud can grow extremely quickly and how advanced device intelligence helped track down the aforementioned fraud ring, Glenn will also address the top five ways to combat CNP fraud. This includes:

  • Leveraging an advanced global device intelligence network to fight CNP fraud
  • How separating user identity from device identity is imperative to reducing fraud
  • The criteria for selecting a global device intelligence solution

iovation is a leader in fraud prevention solutions and regulatory compliance such as EU GDPR and PSD2.

For more details and to register for the upcoming webinar, go to

About TransUnion

TransUnion Global Fraud & Identity Solutions unite both consumer and device identities to detect threats across markets while ensuring friction-right user experiences. The solutions, all part of the IDVision with iovation suite, fuse traditional data science with machine learning to provide businesses unique insights about consumer transactions, safeguarding tens of millions of transactions each day.

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