That’s according to the tech giant’s annual fraud prevention report, issued Wednesday (May 20) and showing that Apple has stopped more than $11.2 billion in fraudulent transactions in the last six years.
Apple credits this to a “multilayered” defense system, which melds “expert human review and advanced machine learning technologies to detect and stop malicious activity,” such as the theft of customers’ financial information.
A major portion of this effort centered on stopping fake accounts before they could do harm, with Apple’s security systems rejecting more than 1.1 billion fraudulent customer account creations at the outset.
In addition, the report said, Apple deactivated more than 40 million existing accounts that were found to be involved in fraud or abuse.
The company took similar steps with app makers, terminating 193,000 developer accounts and rejecting 138,000 new developer enrollments due to fraud concerns.
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Apple also addressed financial crimes, noting that it — in addition to preventing $2.2 billion in fraudulent transactions — had stopped 5.4 million stolen credit cards from being used to make purchases and barred nearly 2 million user accounts from making future transactions.
The findings are in line with last year’s report, which showed Apple preventing another $2 billion in fraud.
In other fraud prevention news, PYMNTS wrote recently about the “deepening paradox at the center of digital commerce and financial services.”
It’s the fact that the systems built to reduce uncertainty have become so “rigid, fragmented and automated” that they fail both when fraudsters are clearly fake and when legitimate users are obviously real.
The report cites two unusual examples. The first dealt with kids in the U.K. who were able to bypass biometric age-verification systems using fake mustaches. The other involved Pope Leo XIV trying to update the phone number on his account at his financial institution, after it was disconnected by his Chicago-based bank.
“Standard fraud protocols made it impossible to authenticate him,” PYMNTS wrote.
The trouble is that most verification systems emerged in an era when digital identities were relatively stable and human-generated content could generally be assumed authentic, before the advent of AI systems that can do things like generate photorealistic faces or clone voices.
As Veriff Chief Technology Officer Hubert Behaghel told PYMNTS in March, modern identity systems need to continuously answer three questions: “Are you who you say you are? Can you be trusted? And are you still the same person related to the account?”
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