Mastercard and GenAI: unleashing the future of commerce in 2025 and beyond
With the recent launch of DeepSeek, GenAI has hit the headlines again.
Mastercard has adopted a structured approach to informed, perceptive, and proactive AI
It seems that AI is following a well-trodden trajectory. Computing history confirms that key principles such as ‘costs decreasing while compute increases’ still hold true.
Yet, despite the excitement, concrete examples of how financial services firms use large language models (LLMs) and embrace the potential of GenAI remain sparse.
With this in mind, Mastercard’s latest report, GenAI Rising Superpowers, caught my eye. In it, the company introduces a framework for understanding GenAI’s evolution, categorising it into three types: informed, perceptive, and proactive AI. This provides a neat, structured way to assess AI’s impact on financial services.
- Informed AI is the most mature and widely used. It relies on LLMs trained with specific knowledge and real-time data to generate relevant insights, enhancing decision-making.
- Perceptive AI, or multi-modal AI, is in its early stages. It integrates various inputs—audio, visual, and sensory data—opening new possibilities for advanced customer service and marketing.
- Proactive AI, also known as agentic AI, represents the cutting edge. It has the potential to reason, make decisions, and act semi-autonomously. Or, in the future, fully autonomously.
This framework resonated with me, and I was interested in learning more, so I contacted Ken Moore, Mastercard’s Chief Innovation Officer. Our exchange provided a fascinating look into how the company is leveraging AI today and where it sees the technology heading next.
Mastercard’s ‘north star’ is powering economies and empowering people, and it sees AI as a key enabler. AI has been integral to Mastercard for over two decades, securing and intelligently managing its network to protect over 143 billion transactions annually.
According to Moore, Mastercard is now using its AI expertise to ensure safer, smarter, and more personalised commerce and strengthen its internal operations.
“Traditional AI excels at processing structured data, enabling applications like fraud detection and personalised experiences,” he explains. “Generative AI allows us to take this further, enhancing existing products while unlocking new possibilities – ranging from software development and implementation to customer support, sales, and service delivery.”
Talking to Ken, you can see that with a strong foundation of AI engineers and data scientists, Mastercard is well-positioned to harness GenAI’s potential for refining processes and creating new products.
I asked Ken which of the three AI types – informed, perceptive, and proactive – would be most relevant to Mastercard in 2025. He answered, “All three matter, but their readiness and scale vary.”
Mastercard already employs informed AI extensively. One standout example is Decision Intelligence Pro, which builds on the existing Decision Intelligence (DI) solution. This real-time decisioning engine helps banks assess and approve transactions. The system scans an unprecedented one trillion data points with GenAI techniques to predict transaction authenticity.
Decision Intelligence Pro further assesses the relationships between multiple entities surrounding a transaction to determine its risk. In less than 50 milliseconds, it improves the overall DI score, sharpening the data provided to banks. Initial modelling has shown that AI enhancements have boosted fraud detection rates by 20% on average and as high as 300% in some instances.
Informed AI is also enhancing customer support with GenAI-powered knowledge agents that streamline product onboarding and accelerate time-to-market.
Perceptive AI, which leverages multi-modal inputs like visual, audio, and sensory data, holds promise for more advanced customer service and marketing applications. While still in early adoption, its potential for creating highly adaptive, personalised experiences is significant.
Regarding proactive AI, Ken believes that in 2025, AI-enabled agents will primarily act as powerful informers rather than fully autonomous actors. However, in future years, he believes that advancements in reasoning models and deeper system integrations will pave the way for AI agents to act proactively on behalf of users. This could unlock capabilities such as autonomous financial planning, self-managing fraud detection, and real-time customer engagement.
I also asked Ken about Mastercard’s approach to partnerships in the GenAI space. His response was unequivocal: “Collaboration is central to Mastercard’s innovation strategy.”
Ken emphasised that Mastercard’s partnerships extend beyond large financial institutions. The company collaborates with smaller digital players, fintech start-ups, venture capital firms, academia, and other industry pioneers.
An example is Start Path, Mastercard’s accelerator programme. Over 400 start-ups from 50+ countries have benefited from Start Path, fostering innovation across AI, blockchain, open banking, ESG, and more. These partnerships allow Mastercard to prototype, test, and scale AI-driven solutions in real-world environments, ensuring they address complex industry challenges.
Despite AI’s potential, integrating GenAI into Mastercard’s global operations isn’t without obstacles. In its GenAI Rising Superpowers report, Mastercard identifies 12 key challenges, with data-sharing regulations and compliance being the most critical.
Ken pointed out that the fragmented global regulatory landscape is an important topic. Many GenAI applications are currently internal or enhancements to existing products, but scaling beyond these use cases requires robust consumer consent frameworks and interoperable systems.
Talking with Ken, you understand that Mastercard has a structured approach to informed, perceptive, and proactive AI alongside a strong ecosystem of partners, and it is this approach that gives it the best opportunity to retain its technology-leading position.
I believe that for now, financial firms should focus on AI as an intelligence enhancer rather than a fully autonomous decision-maker. But make no mistake, AI-driven financial agents could become a reality in years to come, reshaping the future of banking and commerce.
About the author
Dave Wallace is a user experience and marketing professional who has spent the last 30 years helping financial services companies design, launch and evolve digital customer experiences.
He is a passionate customer advocate and champion and a successful entrepreneur. All opinions are his own – feel free to debate and comment below!
Follow him on X at @davejvwallace and connect with him on LinkedIn.
