About Us Contact Us Privacy Policy Terms of Use DMCA Opt-out of personalized ads
© Copyright 2023 Market Realist. Market Realist is a registered trademark. All Rights Reserved. People may receive compensation for some links to products and services on this website. Offers may be subject to change without notice.

Visa, Mastercard Turn To Generative AI To Combat Fraud; Here's How It Works

The use of Artificial Intelligence has become increasingly common in the Fintech space.
VISA, MASTER Card are arranged for a photograph | Getty Images | Photo by studioEAST/Getty Images)
VISA, MASTER Card are arranged for a photograph | Getty Images | Photo by studioEAST/Getty Images)

Banks across the globe are witnessing a jump in a variety of scams. Criminals are using sophisticated tools and technologies to carry out large-scale attacks causing damages worth billions. To combat this, banks are turning to Artificial Intelligence (AI). One of the leaders in digital payments, Visa recently launched a generative AI-powered tool that is embedded in its Visa Account Attack Intelligence (VAAI) system. The company said that the updated VAAI Score system will be available to U.S. issuers first. Similar technologies were launched by another market leader Master Card as well. 


To combat enumeration attacks in which criminals employ technologies like botnets and automated scripts to exploit vulnerabilities, Visa is using its VAAI Score. As per its release, 30% of enumerated accounts experienced fraud within five days of compromising their payment information.

Thus, by using generative AI, components to detect abnormal transaction patterns, Visa’s VAAI Score identifies the risk of complex enumeration attacks in real-time and helps stop and mitigate the attacks. 

Visa credit cards are arranged on a desk | Getty Images | Photo Illustration by Justin Sullivan
Visa credit cards are arranged on a desk | Getty Images | Photo Illustration by Justin Sullivan

The new VAAI Score tool is expected to tackle the costly financial frauds that cost $1.1 billion in losses and operational costs annually to the global financial industry, as per Visa’s release. 

The new model reportedly trains on "noisy data" to predict the complex enumeration attacks. So far, the VAAI Score model has been trained on over 15 billion VisaNet transactions and has six times the number of features compared to previous VAAI models. 

The tool assigns a risk score to each transaction in real time for a faster response. As per the release, the company claims that the tool has already delivered an 85% reduction rate in false positive cases. 

Apart from Visa, Mastercard also rolled out similar tools that use AI-powered insights. Last year, Mastercard announced that as per TSB bank’s estimates, the Consumer Fraud Risk tool could help prevent losses worth £100 million to scams across the U.K. if all banks adopted it. 

Coming to 2024, last month, Mastercard unveiled a new generative AI tool called Decision Intelligence Pro. As per a Fortune report,  the company says that the tool can scan one trillion data points in less than 50 milliseconds to predict if a transaction is legitimate. As per Mastercard’s, initial testing, the tool could increase fraud detection rates on average by a minimum of 20% with the highest recorded rate being 300% in some cases.


In late 2022, the Treasury Department began using enhanced fraud-detection methods powered by AI to detect fraud, as per a CNN report. The strategy mirrored the one that has been adopted by the banks in the private sector and the use of AI to root out suspicious transactions has produced positive results. 

The U.S Treasury’s AI-powered fraud detection system helped recover $375 million in 2023 alone, Treasury officials told CNN. The use of AI has also led to multiple new active cases and arrests made by law enforcement. 


The Treasury officials added that the type of AI used falls into the bucket of machine learning and Big Data. This is similar to the tools used by Visa and Mastercard.  The Treasury’s goal is to move with speed and flag the anomalies to the banks before fraudulent checks and transactions go through.