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Mastercard Aims to Detect Compromised Cards Faster Using AI

Mastercard incorporates AI into fraud prediction technology to detect compromised cards faster. AI enables banks to identify trends in stolen cards, allowing for proactive replacement. Contextual information, along with compromised card numbers, improves detection capability.

Mastercard's latest software update includes generative AI, which attempts to recognise patterns in stolen cards faster, allowing banks to replace them proactively.

Johan Gerber, Executive Vice President of Security and Cyber Innovation at Mastercard, explained that generative AI will aid in determining where and how customers' credentials were compromised, allowing for quick remediation not only for those affected but also for other customers who may be unaware of their compromised status.

The new version allows Mastercard to use more contextual information, such as geography, time, and addresses, as well as incomplete yet compromised credit card numbers discovered in databases. By combining these patterns, Mastercard can speed up the process of replacing compromised cards, protecting cardholders from fraudulent activity.

Moreover, the pattern recognition capabilities of AI can be used in reverse, potentially identifying compromised merchants or payment processors by analysing batches of compromised cards. This goes beyond what traditional database inquiries or standard methods can achieve, according to Gerber.

The dark web is filled with billions of stolen credit and debit card details that thieves may purchase. While many of these numbers were stolen from merchants during data breaches, a large number were obtained from unknowing customers who used their cards at hacked gas stations, ATMs, or online retailers.

Compromised cards can sometimes go unnoticed for long periods of time, ranging from weeks to months or even years. Payment networks or banks typically learn about compromised cards when they actively monitor the dark web, when a merchant reports a breach, or when a criminal uses the stolen card to conduct fraudulent transactions.

Mastercard's AI-powered solution enables proactive outreach to banks, ensuring that affected customers obtain new cards as soon as possible while reducing disruptions to their everyday life.

Payment networks are investigating the use of unique numbers for specific transactions in order to transition away from static credit and debit card numbers that are generally used by all businesses. However, this change may take some time, especially in the United States, where payment technology uptake is typically slow.

While chip cards currently account for more than 90% of in-person transactions worldwide, the proportion in the United States is closer to 70%, according to EMVCo, the body in charge of chip technology in payment cards.

Mastercard's AI update comes as its largest competitor, Visa Inc., looks for methods to lessen reliance on 16-digit credit and debit card numbers. Visa has just announced significant changes to how credit and debit cards will operate in the United States, intending to reduce the number of physical cards carried by consumers and eliminating the 16-digit card number.

  • Mastercard integrates AI into fraud-prediction technology to detect compromised cards faster

  • AI enables identification of patterns in stolen cards, facilitating proactive replacement by banks

  • Contextual information combined with compromised card numbers enhances detection capabilities

Source: AP NEWS

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