Banks Use AI to Make Credit Card Rewards More Personal

For decades, the credit card industry competed to become top of wallet.

The strategy was simple. If a card was used most often, it would generate the most transaction volume and deepen the relationship between the cardholder and issuer.

However, that dynamic is beginning to shift. Consumers now move fluidly between credit cards, buy now, pay later plans, debit cards, and digital wallets, depending on context, cash flow and convenience. As payments choice becomes more flexible, loyalty to a single card is weakening.

As PYMNTS CEO Karen Webster wrote Wednesday (March 11), consumers are increasingly managing spending across multiple payment tools rather than committing to a single card. In that environment, the challenge for issuers is shifting toward influencing the moment a consumer decides how to pay.

Banks and payment networks are increasingly turning to artificial intelligence and transaction data to meet that challenge, using the technology to personalize offers, adjust rewards and tailor incentives around individual spending patterns.

Much of the innovation in credit card rewards is happening outside the checkout flow itself. Instead, the competitive frontier is shifting toward the offer ecosystems that shape purchasing behavior before a transaction occurs.

“I think the real AI revolution in credit cards isn’t necessarily happening at checkout,” Jeanniey Walden, chief marketing and executive advisor at Rakuten Rewards, told PYMNTS. “It’s happening in the offers feed.”

Traditionally, rewards programs relied on broad categories, such as travel, groceries or dining. While those structures were simple, they were designed for a hypothetical “average” cardholder whose spending patterns rarely matched reality, Walden said.

AI is beginning to change that by analyzing large volumes of transaction data and behavioral signals to determine which merchants, discounts or promotions are most relevant to each cardholder.

“For years, merchant-funded offers have tried to match what merchants want to promote with what consumers actually want to buy,” Walden said. “AI is starting to close that gap.”

Instead of generic promotions, rewards platforms can now generate offers that reflect where a consumer shops, how frequently they visit certain merchants, and the time of day or context in which purchases occur. The goal is to influence decisions earlier in the buying journey, shaping what consumers see before they reach the checkout page.

“The brands that understand how to show up when algorithms are deciding who gets recommended are going to find the most success down the road,” Walden said.

AI is also changing how issuers design rewards. Rather than relying on fixed categories that remain constant for months or years, AI systems allow incentives to become even more dynamic and responsive to behavior.

Malte Rau, co-founder and CEO of corporate card platform Pliant, told PYMNTS that early AI applications in rewards programs focus on analyzing transaction data to customize offers and category bonuses around real spending patterns.

“Most of the early use cases we see involve analyzing transaction data to tailor merchant offers, discounts or category bonuses around how cardholders actually spend,” Rau said.

That capability makes it possible to move beyond broad rewards categories toward more targeted incentives.

Instead of offering generic travel or dining bonuses, issuers could surface offers in real time when a cardholder is about to make a purchase at a particular merchant or location. The result is a rewards ecosystem built to influence decisions precisely when consumers are choosing how to pay.

Walden said the industry’s long-term direction is toward increasingly individualized reward experiences.

“AI makes it possible to move toward a much more localized and personalized experience, where the offers you see are shaped by your behavior and what the system learns about you over time,” she said.

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