Fraudsters steal millions of payment card numbers through spyware, malware, and other clandestine practices such as card skimming. In a bid to sell this data to other criminals, they place part of the 16-digit numbers on illegal websites.
The generative AI technology works by scanning transaction data across billions of cards and millions of merchants. It identifies new and complex fraud patterns, which allows Mastercard to predict the full card details of compromised cards on its network. As a result, banks can block these cards much faster than before, greatly reducing the risk of fraudulent transactions.
Moreover, this technology has improved the detection rate of compromised cards, reduced false positives during the detection of fraudulent transactions by up to 200%, and increased the speed of identifying merchants at risk from fraud by 300%. These enhancements enable Mastercard to alert banks more quickly and with greater accuracy when a card is likely to have been compromised, allowing for immediate action to be taken.
This is a clear example of how generative AI is being used to bolster cybersecurity measures in the financial industry, ensuring that transactions remain safe and trustworthy.
Other major credit card companies are also adopting Al technologies to combat fraud. Visa has introduced new payment technology that leverages Al to enhance the security of card information. American Express employs machine learning-powered fraud detection systems to monitor and detect fraudulent activities whenever an Amex card is used.
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