Visa Announces Generative AI-Powered Fraud Solution to Combat Account Attacks
Visa’s new Visa Account Attack Intelligence (VAAI) Score helps identify the likelihood of enumeration attacks in card-not-present transactions
“Enumeration can have lasting impacts on our clients and there’s an immediate need for tools that can better detect and prevent these attacks in real-time,” said
Thirty three percent of enumerated accounts experienced fraud within five days of a fraudster obtaining access to their payment information2. By using generative AI, components to learn normal and abnormal transaction patterns, Visa’s VAAI Score identifies the likelihood of complex enumeration attacks in real-time to help reduce fraud without compromising the integrity of Visa’s performance and accuracy. The tool has been able to reduce the false positive rate by 85% compared to other risk models, as the VAAI Score focuses on specific signals for enumeration allowing for a stronger performance3. VAAI Score can help issuers with:
- Reduced fraud and operational losses: Helps identify complex enumeration attacks in real time which can help reduce follow-on fraud from validated accounts and operational losses due to enumeration such as customer center calls and card reissuance and help safeguard clients.
- Improved cardholder experience: Helps identify when legitimate cardholder transactions are not impacted, while giving issuers a tool to proactively decline transactions at risk for enumeration attacks.
- Real-time transaction scoring: Provides a real-time risk score in 20 milliseconds4 which can help clients in identifying enumeration and using it in their authorization decisioning when used with a rules engine.
“With access to advanced technology, fraudsters are monetizing stolen credentials faster than ever before,” said
The VAAI Score model has been trained on more than 15 billion VisaNet transactions and has six times the number of features compared to previous VAAI models to help better assess suspicious enumeration transactions. Visa’s approach uses noisy data to train the highly accurate real time AI model. By evaluating each CNP transaction against enumeration patterns, the new risk scoring model derives a two-digit risk score that helps predict the likelihood of enumeration to help better determine when to approve, and when to decline, transaction.
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1 Enumeration Fraud Loss from VAAI FY23
2 Enumeration Fraud Loss pulled from VAAI FY23
3 2024 U.S. Visa Account Attack Intelligence Score Model Documentation
4 In adopting AI models VAAI can evaluate up to 182 risk attributes in a millisecond to derive a two-digit risk score predicting the likelihood of enumeration attack.
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amcdermo@visa.com
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