Visa Inc (NYSE:V), a leader in digital payments, has announced updates to its Visa Account Attack Intelligence (VAAI) offering with the addition of the VAAI Score, a new tool that uses generative AI components to identify and score enumeration attacks.
The VAAI Score, which will be available to U.S. issuers first, will help reduce fraud and operational losses by assigning each transaction with a risk score in real time to detect and prevent enumeration attacks in card-not-present (CNP) transactions.
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 performance.
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.
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.
