How are AI and Analytics Helping Redefine Crypto Compliance?

Crypto card payments have hit an all-time high, with a staggering US$584.5m in March, up 211% year-on-year.

This follows a strong 2025, where crypto card spending reached an annualised run rate of US$18bn, according to Yahoo Finance.

But, as digital assets evolve from sitting on the outskirts of finance to being placed in the palms of consumers, the stakes for anti-money laundering (AML) have never been higher.

It’s this explosive growth in crypto-linked spending that is forcing a radical evolution in how financial institutions understand and react to – or preempt – risk.

Because digital currencies are becoming more popular and widely used – and, as a result, becoming part of the fabric of daily commerce.

What comes with an elevation of this scale is a move away from manual oversight toward network-level security.

Shifting to network intelligence

For payment giants around the globe, the challenge balances on maintaining the speed of a card swipe while conducting deep forensic analysis. 

“While many financial service providers and institutions may think they have the tools and policies to prevent attacks, fraudsters are proving to be exceedingly sophisticated – often covertly disabling the internal monitoring systems of their targets before launching highly coordinated attacks,” Mastercard says in its Securing Trust in Central Bank Digital Currencies whitepaper.

“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 record-breaking 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.

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 AI-driven future began with a focus on digitised transparency.

Karen Griffin, Mastercard’s Chief Risk Officer, explains that the goal has always been to use technology to remove the guesswork from global monitoring. 

“We use data mining and analytics to identify outliers. With this approach we eliminate blind spots and flag exceptions as they occur,” she tells Finextra, adding that this high-level intelligence is now “available at the touch of a finger”.

It’s this foundation that laid the groundwork for the Gen AI era – ensuring systems don’t just flag exceptions but predict them.

As no organisation can survive through self-reliance alone, Mastercard highlights how AI-driven compliance isn’t just about stopping fraud, but about building the trust necessary for mainstream crypto adoption.

Ultimately, it’s this integration of Gen AI and network-level intelligence that is driving a shift from defensive compliance to proactive ecosystem trust.

And, as Mastercard’s traveling together philosophy suggests, the future of crypto isn’t just about faster transactions, but about creating a global safety net that scales as it grows.