CareCredit - Women's Health April 2024

12 Payments Experts Share How AI Changed Everything in 2023

The payments ecosystem reached an inflection point in 2023.

In a world where innovative payment offerings are increasingly populating the marketplace powered by technologies like artificial intelligence, many businesses find themselves stuck using legacy solutions and payment rails with limited choice and optionality.

Sticking to the way things have always been done could be harming firms in the long run. Payments sector experts told PYMNTS this year that when it comes to using AI’s capabilities for enhancing payments the question is “How,” and the answer is “Now.”

While the payments industry has been a latecomer to the financial technology revolution, AI promises to transform workflows from customer service to back-office automation, where resource-heavy processes and endless manual reconciliations offer wins for machine-led optimizations.

As Form3 CEO Michael Mueller told PYMNTS in October, “payments are still an exciting growth business, despite the fact that they’ve been around for so long.”

After all, it would be hard to go back to manual submission or sift through data by hand once firms have tried a process improvement based on AI.

See also: Demystifying AI’s Capabilities for Use in Payments

Scaling AI Across the Payments Landscape

Helping firms streamline formerly manual processes within areas like accounts payable and accounts receivable, cash flow forecasting, credit scoring, fraud prevention and compliance will be the easiest and first avenues where applications of generative AI can score an immediate impact.

More generally, the technology may enact cost-effective and non-manual decision-making processes that are increasingly auditable and do not sacrifice security for convenience.

“The folks that invest heavily in AI and use it to improve their authorization rates in the payment space are doing very well, as far as I’m concerned,” Andrew Gleiser, chief revenue officer at Aeropay, told PYMNTS in May. “Improving authorization rates by 10%, for example, ends up hitting the top-line revenue of both the processor and their customer.”

Historically, electronic payments lacked the depth of data required for sophisticated analysis. However, AI has transformed this landscape by allowing businesses to gain smarter and faster insights from their payment data.

“AI and machine learning (ML) are incredible tools [for the payments sector],” Justin Shoolery, head of data science and analytics at, told PYMNTS in October.

“[AI-driven] optimizations are translating into more successful businesses,” he added.

Billtrust Senior Vice President of Data Analytics and AI Ahsan Shah told PYMNTS in December: “What is fundamentally changing, is that AI is redefining itself this year with generative AI.”

“Things like fraud detection, forecasting, anomaly detection and recommendations have existed for a very long time — but generative AI knows how to write, how to communicate, and how to generate content. It’s a human-centric interface that is very much complementary from a tech stack perspective.”

As Aanchal Kochhar, head of product at Capital One Trade Credit, told PYMNTS in October, “You can delight customers and capture more customers when underwriting is seamless, the credit process is seamless, and how money flows is seamless and with less error. There is a lot of growth potential [when leveraging AI].”

Read also: Generative vs Predictive AI’s Role Across the Future of Payments

Building AI Confidence for Tomorrow With Wins Today

PYMNTS Intelligence found that 60% of Generation Z and 54% of both millennials and bridge millennials are interested in AI-enabled shopping experiences, and firms that integrate the technology can realize immediate wins across areas like customer support, sales, marketing and anomaly detection in payments.

“There are two ways to monetize [digital payments], which is efficiency of the finance teams, and then actually efficiency of the payments itself,” Karandeep Anand, chief product officer at Brex, told PYMNTS in August.

“If you can even save some eight- or 10-people’s worth of work at the end of the quarter and finish and close the books within 24 to 48 hours [using AI], that is priceless,” he added.

“There is a lot of opportunity to build new user-facing products, or those that better delight users in an existing experience, using AI,” Emily Glassberg Sands, head of information and data science at Stripe, told PYMNTS in March.

As the world moves to further innovations like real-time payments in 2024, AI’s at-speed capabilities will become more critical around orchestration and fraud protection.

Still, implementing AI involves building the data and technical infrastructure to accommodate the technology. These steps are neither easy nor cheap, and organizations must align their workforces to become proficient in providing context to AI models.

After all, long before AI existed, data fragmentation was always a sector-agnostic problem.

In the absence of regulation, compliance and governance concerns around AI will also need to be addressed.

“[W]e’ve got to be careful how we use this technology in a compliant manner,” i2c CEO and Chairman Amir Wain said to PYMNTS in June, cautioning against rushing full speed and embracing AI. “We cannot be at the bleeding edge of technology dealing with people’s money and funds. … We need to put a compliant framework around the tool.”

Beerud Sheth, CEO of conversational AI platform Gupshup, told PYMNTS in November: “Consumers can have fun with AI, but in a business chat or within an enterprise workflow, the numbers have to be exact, and the answer has to be right.”

“Enterprise use of AI has to be accurate and relevant — and it has to be goal-oriented,” he added.

See also: 10 Insiders on Generative AI’s Impact Across the Enterprise

But within the right framework, applications of AI within payments can be revolutionary in augmenting payment workflows, particularly across in-car purchases and other next-generation payment occasions.

“It’s totally transformative, and payments are in the middle of [the AI experience],” Ingo Money CEO Drew Edwards told PYMNTS in February. “It’s where the connected car comes in because you can’t use your hands, and you’re interacting with this artificial intelligence. All the way through to paying for that experience, it just happens without you ever touching a keyboard or putting your credentials in.”

Generative AI tools can use smart analytics that make sense of collected data while the payments are still flowing, but these capabilities don’t mean that humans are going to disappear.

“There’s a long way to go before there’s a futuristic version of AI where machines think and make decisions. … Humans will be around for quite a while,”  Tony Wimmer, head of data and analytics at J.P. Morgan Payments, told PYMNTS in March. “And the more that we can write software that has payments data at the heart of it to help humans, the better payments will get.”

Still, the future for AI within payments is set to accelerate.

“We always overestimate the first three years of a technology, and severely underestimate the 10-year time horizon,” Bushel CEO Jake Joraanstad told PYMNTS in December.

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