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Enumeration attacks, which involve threat actors using automated scripts or botnets to submit card-not-present (CNP) transactions with different payment values, result in up to $1.1 billion in fraud losses annually. To combat this, Visa has introduced a new tool called VAAI Score, which uses generative AI to identify and score enumeration attacks in real-time. This tool aims to help US issuers reduce fraud and operational losses by assigning risk scores to transactions to detect and prevent enumeration attacks.
Paul Fabara, Visa’s chief risk and client services officer, highlighted the importance of tools like VAAI Score in detecting and preventing enumeration attacks. The tool has reduced the false positive rate by 85% compared to other risk models, focusing on specific signals for enumeration to improve performance. VAAI Score aims to help issuers reduce fraud levels, operational losses, and improve the cardholder experience by providing real-time transaction scoring.
Visa has trained the VAAI Score model on over 15 billion VisaNet transactions to better assess suspicious enumeration transactions. By evaluating each CNP transaction against enumeration patterns, the tool derives a risk score to predict the likelihood of enumeration and make informed authorization decisions. Visa’s commitment to security and reliability includes investing over $10 billion in technology to prevent fraud and enhance network security.
Michael Jabbara, SVP global head of fraud services at Visa, emphasized the importance of advanced technology in preventing fraudulent transactions. Visa’s proactive measures have helped block $40 billion in fraud, demonstrating their dedication to protecting cardholder accounts and preventing fraudulent activities.
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Source link: https://thefintechtimes.com/visa-combats-enumeration-attacks-with-new-generative-ai-powered-anti-fraud-tool/
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