The 4 Easy Wins GenAI Brings to the Payments Sector

The ability to scale is what qualifies an innovation as such.

While generative artificial intelligence has, by many observers’ accounts, already reached innovation status at a broad level, the question remains: Can AI scale across the payments ecosystem?

2024 may be the year we find out.

“In today’s world where differentiators between companies, especially in the payments ecosystem, are becoming more and more narrow, you need to be an early adopter and quick on your feet,” Netanel Kabala, chief data and analytics officer at Nuvei, told PYMNTS for the series “What’s Next in Payments — Payments and GenAI: What’s New and What’s Next?”

Kabala highlighted the complementary nature of generative AI and its cousin, predictive analytics, emphasizing the potential of generative AI to create new products and enhance efficiency across the payments landscape.

“Predictive AI learns from the past, and generative AI is about something new,” he explained, noting that one of the most compelling existing applications of generative AI in payments is fraud prevention, where generative AI can assist in labeling data at scale and predicting future trends.

AI’s potential to transform the payments industry is undeniable, and Kabala highlighted four easy wins AI can bring to payments companies, including improving internal efficiencies, streamlining operations, enhancing customer service, and creating new products and services.

“I’m excited about everything related to internal efficiency, how [using AI] we can improve all the inner workings of a payments company from reconciliation to customer service, to integrations, and so on,” he said.

The Potential of Generative AI Within Payments

Generative AI is particularly effective in parsing tasks that involve large amounts of text and context in little time, and Kabala suggested that generative AI can be used to improve organizational knowledge bases and enhance the productivity of customer service, operations and risk teams, by summarizing vast quantities of information to provide insights.

Looking ahead, Kabala said he envisions generative AI playing a role in creating new products and services, including using real-time pricing to enable adaptive pricing solutions that benefit both merchants and consumers, as well as using AI to customize financial products, such as buy now, pay later (BNPL) plans and lending options.

But if scaling were easy, everyone would do it.

Generative AI solutions meant to improve the payments ecosystem will first need to overcome institutional inertia and other obstacles.

“First, it is a mental obstacle putting trust in these new systems,” Kabala said. “People really need to see the benefit of how it helps in their day-to-day. It’s really nice that you improved your internal efficiency by 7%, but that needs to be made visible and meaningful.”

Beyond educating the market about the benefits and most effective uses of AI-driven solutions, Kabala said the availability of skilled engineering staff who can handle both traditional data analytics and new AI technologies is essential for successful implementation.

The Future of Generative AI in Payments

As generative AI becomes more prevalent in the payments ecosystem, it has the potential to contribute to the development of super apps that offer a range of services, from banking to wealth management, Kabala said.

But he cautioned that the technology can also be used by bad actors, making fraud prevention a critical issue.

“Fraud has always been challenging, but now scams are easy,” he said, noting that fraudsters can exploit AI-generated content by using the technology to do things like build fake websites, translate scams across languages in one click, and power many other malicious tactics.

When it comes to the security of the AI systems themselves, transparent decisioning is crucial to ensure trust from consumers, merchants and internal teams.

Kabala emphasized that being able to audit generative AI’s “black box” of decisioning will be crucial, and organizations need to start building the “proper steps and the proper explainability measurements” now to stay ahead of the innovation and address any future challenges.

When it comes to the future of generative AI within payments, Kabala noted that “a year ago, we wouldn’t have been able to discuss generative AI.”

While he said he doesn’t know what the future might hold, he does know that having “the right resources, the right people, the right infrastructure and the right mindset to be wherever the new technology, the new opportunities might pop up” is crucial to success across any industry — but especially payments.

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