Visa is leading the AI race in payments, according to Evident’s AI Index for Payments, a major new ranking of AI adoption within the industry. 

The Index shows industry stalwarts Visa and Mastercard outpacing their peers and delivering tangible AI outcomes thanks to early investments in talent and innovation.

Behind them, PayPal (3rd), American Express (4th), Stripe (5th) and Block (6th) emerge as the challengers. They outperformed the Index average, but are yet to match the leaders’ scale of deployment and outcome disclosure.

AI Moving from Experimentation to Deployment

Over the past two years, the 12 payments companies in the Index have publicly documented nearly 100 AI use cases. Underscoring how rapidly AI has moved from experimentation to deployment across core payment workflows. It’s a landscape defined by constantly evolving fraud threats and rising customer expectations for faultless, high-speed processing. Evident notes that nearly a third of these use cases disclose measurable outcomes, including efficiency gains, risk reduction and revenue uplift.

“Payments firms adopted AI out of necessity long before many other industries – their business models demanded it. Companies who invested early – like Visa and Mastercard – have gained a clear advantage over their peers, both in AI capabilities and the value their deployments are realising.” Alexandra Mousavizadeh, Co-Founder and Co-CEO of Evident.

Talent, Innovation, Leadership and Transparency

The Evident AI Index for Payments provides the most comprehensive independent benchmark of AI maturity across the industry. It is based on publicly available data around four pillars critical to successful AI deployment: Talent, Innovation, Leadership and Transparency.

According to Evident, Visa’s lead is based on consistent performance across the four pillars. And because it demonstrates the clearest evidence that AI is institutionalised across its core transaction network. Visa and Mastercard show maturity in areas such as fraud detection, cybersecurity and network-level risk reduction. Visa stands out for the scale and measurable impact of a handful of large, multi-year deployments focused on the integrity and security of its entire ecosystem.

“Mastercard shows strong evidence of scaled deployment and quantified performance improvements. Particularly in areas like fraud detection and AML tracing,” continued Mousavizadeh. “But what sets Visa apart is the degree to which the company is demonstrating impact at scale over multiple years. From applications of AI across its operations and network. It signals a shift from individual use cases to AI as institutional capability.

“What the Index also reveals is the importance of consistent innovation to maintain competitive advantage. With relatively nascent industry players like Stripe and Block performing well – and showing their AI potential reflected in their valuations – the Index leaders cannot afford to drop off the pace.”

AI Impact on Show, but ROI Reporting Scarce 

Firms in the top half of the Index account for nearly 80% of use case disclosures (with the top three providing a significant 54%). Highlighting the link between AI maturity and the ability to scale deployment.

Visa performed strongly in this regard. For instance, its latest threat report disclosed advanced AI/ML blocked nearly 85% more fraud compared to one year prior. Similarly, when Mastercard incorporated Gen AI technology into its Decision Intelligence solution, initial modelling showed AI enhancements improved fraud detection rates from an average of 20% to as high as 300% in some instances.

However, Evident notes that no payments company has disclosed realised or projected ROI across all enterprise or group-wide AI activities. 

“The Index leaders are locked in a tight race at a point when the thinking around corporate AI adoption is shifting – away from chasing the biggest models to building technologies that solve real operational problems efficiently,” commented Annabel Ayles, Co-Founder and Co-CEO of Evident. “Against this backdrop, the absence of ROI disclosure – or any group targets for AI ROI – is increasingly conspicuous. Currently, 1-in-5 banks now report on group-level AI returns. However, payments firms have yet to quantify the aggregate impact of their AI investments. To keep justifying this expenditure, the market will sooner or later demand clearer evidence of value.”

A Hotbed of AI Talent

The Index also reveals that the average payments company has over 30% more AI-focused workers than other financial institutions, despite substantially smaller employee numbers. 

The three major card networks – Visa, Mastercard and American Express – account for nearly half (48%) of the payments industry’s AI talent stack. PayPal is currently the biggest employer, accounting for nearly a fifth (18%) of that AI talent.

PayPal’s AI talent has allowed it to build proprietary models tightly integrated with its data and workflows. Consequently, it accounts for nearly a quarter (24%) of the 98 AI use cases documented by its peers over the past two years – 1.7x as many AI applications as detailed by Visa or Mastercard.

“AI maturity is no longer defined by talent volume alone, and the Index leaders combine AI development, data engineering and product capabilities in ways that allow them to move rapidly from model experimentation to production deployment,” concluded Ayles.

The Evident AI Index Methodology

The Evident AI Payments Index ranks the AI maturity of 12 of the largest payment networks and processors across the globe. These 12 entities were chosen by aggregating the largest payment companies, with a minimum of $2B in annual revenue. 

It is an independent, ‘outside-in’ assessment based exclusively on publicly available information. Each company was assessed against 60+ individual indicators, organised into four pillars critical to successful AI deployment at scale: Talent (45% weighting), Innovation (30%), Leadership (15%) and Transparency of Responsible AI activity (10%).

Data is gathered through a combination of extensive manual research and proprietary machine learning tools that extract key data points from company reporting and public disclosures (including press releases, investor relations materials, group-level website pages, group-level social media accounts, and media interviews with senior leadership), as well as a range of third-party data platforms.

Further information on the methodology of the Index can be found at evidentinsights.com