AI Opens a New Distribution Channel for Credit

Economic pressure is incentivizing consumers more reason to compare the cost of a purchase, the possibility of financing behind it and the alternatives before committing. Financial providers are embedding those choices into a new place: the artificial intelligence (AI) platforms consumers are using to research what to buy.

AI’s potential financial-product distribution channel is taking shape across several fronts.

Among the latest examples came Thursday (Aug. 27), when Experian launched a credit-card app in ChatGPT that lets consumers search and compare cards by goals such as earning rewards, building credit or reducing interest costs. Consumers can compare fees, rewards rates, introductory offers and APR ranges inside the conversation before continuing to Experian for offers matched to their credit profile.

That follows Experian’s June launch of personal-loan shopping in ChatGPT. The loan application surfaces options from Experian’s lender network using lender criteria and permissioned consumer data.

Separately, Synchrony said this month that that it plans to launch a ChatGPT plugin through which consumers can browse promotional financing, deals and other offers from participating Synchrony partners. Its broader collaboration with OpenAI is intended to bring financing, rewards and loyalty into AI-based shopping and checkout experiences.

Klarna has approached the opportunity from the commerce side. Its Shopping Search app, launched in ChatGPT in May, lets consumers describe what they’re looking for and see products, current prices, availability and merchant offers without first visiting individual retailers.

There’s a common theme running through the announcement. The corporate actions noted above extend an embedded-finance model that historically put payments, lending and banking capabilities into merchant sites, marketplaces and software platforms. Now some of those capabilities are being positioned inside an AI interface that can influence the decision before a consumer arrives at checkout.

Discovery Moves Upstream

Ample evidence indicates consumer behavior can and will embrace such a channel.

PYMNTS Intelligence’s benchmark data found that 50.7% of consumers had used generative or agentic AI to discover what to buy as of May, while 41% had used it for activities involving managing finances and banking. Separately, PYMNTS Intelligence research with Visa found ChatGPT’s use for product search rose from 2% in 2024 to 30% in 2026 among surveyed consumers in the U.S., Brazil and the United Arab Emirates.

Financial providers therefore have a distribution question familiar from earlier generations of embedded finance: where does their product need to be available when a customer is making a decision?

An AI platform can compress several stages of that process. A consumer researching a refrigerator, for example, could potentially compare products, prices and financing within the same conversational environment. A consumer trying to consolidate debt could encounter loan options while asking an AI service how to reduce monthly expenses.

Placement alone isn’t enough. Financial information presented through an AI interface has to be current and tied to authoritative sources, particularly when the conversation moves from general information toward personalized eligibility, pricing or credit decisions.

As financial products move into third-party AI environments, verification covers more than identity. Providers need confidence that product terms are current, that offers originate with the provider or an authorized marketplace, that customer data is handled appropriately and that personalized results reflect actual eligibility criteria rather than an AI model’s inference.

The existing embedded-finance market offers a useful indication of how companies view those responsibilities.

PYMNTS Intelligence and Green Dot surveyed 515 senior executives and found that provider selection already depends heavily on trust, security and operating fit. Among firms with less than $250 million in annual revenue, nearly two-thirds prioritize trust in their provider and close to half prioritize data security. Larger companies put greater emphasis on customization and compatibility with existing operations.

The same research found roughly 80% of small and middle market companies planned to upgrade their embedded-finance capabilities within 12 months. Those investments have largely concerned financial services embedded in companies’ own operating ecosystems. AI distribution adds another layer because the interface where a consumer discovers the financial product may belong to someone else.

AI platforms can put a financial product closer to the beginning of a purchase decision, a function that makes them potentially powerful distribution channels. It also makes the accuracy, provenance and verification of financing options part of the product itself.

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