Card-linked installment payments can prevent AI agents from abandoning purchases when traditional buy now, pay later (BNPL) fails at checkout, according to Splitit CEO Nandan Sheth. In a new PYMNTS eBook, "Building the Agent-Ready Payments Enterprise," Sheth argues that payment models built for human shoppers break down when AI agents act on a buyer's behalf - and retailers lose sales without knowing why.
Traditional BNPL has helped retailers solve affordability for a decade, raising conversion and average order value. But the model was built for a human shopper sitting in front of a screen.
In a BNPL transaction, a consumer applies for short-term credit at the point of purchase, receives a real-time approval decision and completes the transaction through a provider like Affirm. If there's a problem, the shopper can fill out a form, accept the terms and be redirected to a third-party flow.
Why BNPL breaks in agentic commerce
AI agents act on a shopper's behalf to find, evaluate and complete a purchase. There's no human in the loop to handle a new credit application. The transaction either completes or it doesn't.
With new-credit BNPL approval rates running between 35% and 40%, 6 in 10 BNPL transactions handled by AI could fail at the payment step. "The worst part is, the retailer won't even know. The agent will just move on to another merchant," Sheth wrote.
Businesses deploying AI Agents & Automation might only discover this limitation in production, when the cost of rearchitecting a payment integration is higher than modeling it correctly from the start. For sales teams, that means lost revenue that's hard to trace back to a payment problem.
How card-linked installments work
Card-linked installments provide the certainty that BNPL lacks. The merchant authorizes the full purchase amount against the shopper's existing credit card at checkout, then splits that authorized amount into monthly payments. No new credit application, no third-party loan - just installments drawn against credit the shopper already has.
"Card-linked installments help prevent payment failures because the credit decision is made when the card is issued," Sheth wrote. The agent draws on available credit rather than triggering a real-time lending decision.
This model also selects consumers with established credit and available capacity. These shoppers typically make higher-AOV purchases and are repeat buyers, making card-linked BNPL a high-quality, low-risk growth engine.
Why this matters for Sales
Sales teams evaluating AI for Sales should consider whether their payment infrastructure can handle unattended transactions. A 35-40% approval rate on new-credit BNPL means most agent-driven purchases using that model will fail silently. Card-linked installments approve at the card level, so agents can complete purchases without human intervention.
The companies that get this right will be the ones agents keep coming back to.
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