Fighting retail fraud starts with speaking the same language, says NRF’s Christian Beckner
As fraud tactics become more sophisticated and digitally enabled, retailers are facing a new kind of challenge: how to define what’s happening in the first place.
That’s the message from Christian Beckner, vice president of retail technology and cybersecurity at the National Retail Federation, in the latest episode of the Cyber Focus podcast hosted by Frank Cilluffo. The conversation, recorded April 30 at the recent RSA Conference in San Francisco, explored the evolving threat landscape in the retail sector — and why better language may be just as important as better tools.
“We’re seeing an increase in account takeover fraud, gift card fraud, return fraud,” Beckner said. “It’s often hard to draw the line between what’s a fraud issue and what’s a cyber issue.”
To address that growing overlap, NRF is developing a fraud taxonomy — a standardized way to define and categorize different types of fraud — so that retailers, law enforcement and partners can communicate more clearly. “Right now, we’re all speaking different languages,” Beckner said. “When we’re talking to law enforcement, or even among companies, we’re not using consistent definitions. And that’s really important if we want to have an impact.”
The conversation also touched on the broader convergence of fraud and cyber threats, as well as NRF’s policy priorities — including the implementation of the Cyber Incident Reporting for Critical Infrastructure Act of 2022 (CIRCIA), the SEC’s cyber disclosure rule, and hopes for stronger engagement from CISA in the year ahead.
Beckner emphasized that retail, as one of the most consumer-facing sectors of the economy, sits at the intersection of technology, trust and threat. “Retail is a huge part of the economy,” he said. “It touches every person, every day. That makes it central to our overall cybersecurity posture.”
The full episode is available on the Cyber Focus podcast feed at the McCrary Institute website and here on Threat Beat.