DIGITAL ASSETS
“ These modern cybercriminals exploit both organisational silos and national borders to undermine the safety and security of critical systems. The result is a world where no organisation pursuing a strategy of cybersecurity‘ self-reliance’, regardless of their sophistication, can be confident that their systems are secure. The safest organisations will be those that‘ travel together’ – sharing critical insights in real time from a network that is global in scope.”
Raj Dhamodharan, Head of Digital Assets and Blockchain at Mastercard, sees the future of maintaining speed and security with seamless integration at the core. Speaking on the need for various digital currencies to work together safely, Raj says that Mastercard believes in payment choice“ and that interoperability across the different ways of making payments is an essential component of a flourishing economy”.
He adds that, for the recordbreaking spending rates to continue, the user experience cannot be hindered by the underlying complexity of compliance.
“ As we look ahead toward a digitally driven future, it will be essential that the value held as a Central Bank Digital Currency( CBDC) is as easy to use as other forms of money,” he says. By making these assets easy to use, fintechs are tasked with ensuring the“ invisible” AML layers – such as real-time wallet screening – are more robust than ever.
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Mastercard accelerates card fraud detection with generative AI technology
How Gen AI turbocharges real-time fraud defence With crypto card spending continuing on its record-breaking trajectory, the window to detect fraud has shrunk to milliseconds. To stay ahead, Mastercard turbocharges its defence layers with Decision Intelligence Pro, a proprietary Gen AI-powered engine designed to scan an unprecedented one trillion data points to predict transaction authenticity.
While traditional AI models often rely on historical rules and manual feature engineering, Mastercard’ s Gen AI takes a network-level approach. By assessing the complex relationships between multiple entities involved in a transaction – such as merchant history, device ID and behavioural clusters – the system can refine a risk score in fewer than 50 milliseconds.
The journey toward this AIdriven future began with a focus on digitised transparency. Karen Griffin, Mastercard’ s Chief Risk Officer,
108 May 2026