In its latest software update rolling out this week,
“Generative AI is going to allow to figure out where did you perhaps get your credentials compromised, how do we identify how it possibly happened, and how do we very quickly remedy that situation not only for you, but the other customers who don't know they are compromised yet,” said
The patterns can now also be used in reverse, potentially using batches of bad cards to see potentially compromised merchants or payment processors. The pattern recognition goes beyond what humans could do through database inquiries or other standard methods, Gerber said.
Billions of stolen credit card and debit card numbers are floating in the dark web, available for purchase by any criminal. Most were stolen from merchants in data breaches over the years, but also a significant number have been stolen from unsuspecting consumers who used their credit or debit cards at the wrong gas station, ATM or online merchant.
These compromised cards can remain undetected for weeks, months or even years. It is only when the payment networks themselves dive into the dark web to fish for stolen numbers themselves, a merchant learns about a breach, or the card gets used by a criminal do the payments networks and banks figure out a batch of cards might be compromised.
“We can now actually proactively reach out to the banks to make sure that we service that consumer and get them a new card in her or his hands so they can go about their lives with as little disruption as possible,” Gerber said.
The payment networks are largely trying to move away from the “static” credit card or debit card numbers — that is a card number and expiration date that is used universally across all merchants — and move to unique numbers for specific transactions. But it may take years for that transition to happen, particularly in the
While more than 90% of all in-person transactions worldwide are now using chip cards, the figure in the
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