Generative artificial intelligence (GenAI) is more than just the next buzzword. It’s proving to be a revolution across the payments ecosystem. The key? Intelligent integration — using GenAI to solve real-world problems rather than deploying it for the sake of appearance.
A deep dive into recent conversations with payments industry leaders for the “What’s Next In Payments Series: Memo To The GenAI Companies” series reveals four defining themes foundational to how the marketplace is thinking about the impact of GenAI innovation across payments:
As the payments industry grapples with the challenges and opportunities AI offers, one thing becomes clear: Companies that can compliantly and successfully integrate GenAI applications could be those best positioned relative to their peers to define the next era of financial services.
GenAI as a Security Guard for Payments Ecosystems
Fraud detection remains one of the most exciting use cases for GenAI in the payments space. With businesses processing trillions globally, safeguarding every dollar, transaction and customer detail is no small feat. As hackers get savvier, standing up AI guardrails for payment systems is moving from optional to mandatory.
Sam Hamilton, head of AI and data at Visa, underscored the importance of leveraging AI to combat increasingly sophisticated cyber threats. He said that Visa itself is attacked constantly. Fraudsters besiege their APIs billions of times each month, so the company is proving especially adept at using AI to fight fire with fire.
“We’re getting ready for AI to be deployed across the company — and enable capabilities that power the next wave of payment security,” he told PYMNTS. To get there, Hamilton said, data is critical.
Alex Hoffmann, general manager of North America at Edenred Pay, echoed this sentiment: “Where there’s money, there are crooks.” Edenred’s approach combines GenAI with autonomous fraud agents to detect anomalies across multiple applications, adding a layer of dynamic, real-time security, Hoffman said.
Similarly, Boost Payment Solutions Chief Technology Officer Rinku Sharma pointed to the importance of AI in fraud detection. “GenAI can analyze transaction patterns in real-time and identify anomalies, flagging potential fraudulent activities more accurately than traditional methods,” he said. “This enhances security, reduces financial losses and builds customer trust.”
Winning the Payments CX Battleground
Forget love — the real battlefield of the 21st century is customer experience (CX), and the transaction occasion is increasingly at the frontline. In a world where everyone’s vying for wallet share, clunky checkout pages and payment hiccups can be relationship killers.
Enter AI, which experts tell PYMNTS is set to revolutionize the payment journey.
Gaurav Singal, CTO at Cantaloupe, envisions a future where payments become invisible yet secure. Cantaloupe’s own social gifting platform, Cheq, leverages GenAI to craft personalized messages, blending functionality with an emotional connection.
“My vision for the future is to make payments disappear into the background,” he told PYMNTS. “The potential for GenAI to transform payments is immense. We’re just scratching the surface.”
The new era of payments is about more than swiping cards or tapping phones. It’s about speed, security and, most importantly, making the buyer feel like a VIP. The competition isn’t just about who can deliver the product fastest; it’s about who makes paying for it a breeze.
Tom Randklev, global head of product at CellPoint Digital, highlighted the role of AI in creating hyper-personalized payment experiences. “Through payment orchestration, we’re creating hyper-personalized, dynamic forms of payment presentation,” he said. “We’re meeting our customers where they want to do business, when they want to do business, and providing the ability to pay however they want to.”
GenAI: Giving the Back Office a Boost
For many payment companies, GenAI’s true power lies in its ability to automate complex workflows and reshape traditionally repetitive and laborious back-office functions.
“I can’t think of one area that GenAI is not going to transform,” Sam Hamilton, head of AI and Data at Visa, told PYMNTS.
Lisa McFarland, executive vice president and chief product officer at Ingo Payments, emphasized the importance of starting with “low-hanging fruit” such as customer service chatbots and moving toward more complex applications. “We’ve increasingly begun using AI-based tools in the technology area,” she noted, pointing out that AI-powered tools improve productivity and accelerate development cycles.
“Within the space of the office of the CFO and accounts payable, that’s where GenAI may be most transformative,” added Hoffmann of Edenred Pay. “What GenAI adds on top of all this is that beyond the payment, we can automate the invoice-to-pay cycle.” This capability reduces manual interventions and errors, streamlining the accounts payable process.
Cory Mann, vice president of product at FNBO, told PYMNTS that GenAI is already having an impact in financial services, enabling banks to help clients gain insight into spending patterns and predict future cash flows. But to truly leverage GenAI, he said, banks must take stock of the data that’s available to them, with an eye on not just how GenAI can bring innovation to client-facing interactions but also how it can improve the very operations of the financial institution itself.
“GenAI is great at helping us interact with and extract large amounts of data and interpreting them more quickly,” Mann said.
The result? Faster payments, fewer errors and a back office that doesn’t just support the business but drives it forward.
Ensuring Enterprise AI Alignment
AI is the shiny new toy in the enterprise world, but here’s the catch: Without proper alignment, it’s like giving a toddler the keys to a Ferrari. Misaligned AI can waste resources, churn out irrelevant data or make decisions that backfire spectacularly.
“Governance, cost and utility form the three points of the [GenAI] triangle we’re trying to balance. Getting it right will unlock transformative possibilities for our industry,” Mark Sundt, CTO at Stax Payments, said. “We’re moving away from the kitchen-sink approach of large models to focused, orchestrated agents that solve specific problems effectively and at lower costs.”
Sundt underscored the need for AI providers to align their rapid development cycles with the slower, compliance-driven nature of the banking industry. “The financial sector doesn’t move at the speed of tech. It’s crucial for AI companies to understand our industry’s unique challenges and design solutions accordingly,” he said.
McFarland of Ingo Payments called on AI providers to prioritize solutions tailored to financial services. “You can take core tools, but you’ve got to do a lot of work from a development perspective and a learning and intelligence perspective internally,” she said.
“Public AI systems, like chatbots, can’t simply be lifted and shifted for sensitive applications. Private AI offers greater control over data access and compliance,” Boost’s Sharma said, highlighting the importance of private AI models for enterprise use cases.