COMMENTARY: BNPL Is Booming, And So Are the Risks You Can’t Ignore

Buy now, pay later has changed the way people shop. It’s quick, intuitive, and built around modern consumers, a seamless option at checkout that breaks big purchases into manageable moments. No fuss, no friction.

For payments organizations, it’s opened new avenues of growth. Adoption is soaring. Merchants are happy. Consumers are coming back. But as BNPL matures, so does the conversation around how to protect it—not just from fraud, but from the kind of inefficiencies and blind spots that can hold back progress.

BNPL evolution comes with some tough questions: How do you keep the experience fluid while managing risk? How do you validate intent in a low-friction environment? How do you build trust into a model that moves by design at high speed?

BNPL is built on the promise of simplicity. That simplicity, however, is also what makes it uniquely vulnerable. Unlike traditional credit products, BNPL often minimizes upfront verification. There are fewer identity checks. Application processes are stripped down. Decisions are made in seconds. And yet, in a digital economy where synthetic identities, data breaches, and credential stuffing are now routine, simplicity without visibility can create gaps for fraud to slip through and quietly erode trust.

Payments providers processing these transactions have authorization responsibility. But they also are responsible for enabling confidence for merchants, for consumers, and for the broader payments ecosystem that depends on predictability and integrity.

Most fraud and risk models in payments rely on signals captured at the point of transaction––name, address, email. But by the time someone reaches checkout—especially in a BNPL context—the opportunity to intervene is already narrow. Approving or denying the transaction in that moment might prevent a chargeback, but it doesn’t address the underlying quality of the account or the data that shaped it.

What’s needed is earlier insight, a view that reaches back to the first touchpoint — account creation, signup, or application — and brings more context into the conversation. Not just, “Does this look risky now?” but also “Has this identity behaved in a way that makes sense all along?”

That upstream perspective is especially valuable in BNPL, where speed and convenience are often prioritized over robust credentialing. Fraud doesn’t always show up as a spike. Sometimes it’s just a mismatch, a timeline that doesn’t add up, an identity that looks slightly off, a usage pattern that subtly breaks from the norm.

While identity data validate transactions, the game is changing. Static fields like names and addresses don’t provide enough texture on their own. Fraudsters are adept at stitching together information that passes a superficial check, so more dynamic data is needed to show behavioral depth.

Email addresses carry histories of engagement across digital ecosystems. They reveal patterns: how often they’re used, whether they’ve interacted with legitimate merchants, whether they show signs of automation or mass creation. When examined in real time, email behavior is a powerful complement to existing fraud models. It’s not about blocking customers based on a single data point. It’s about enriching the decision-making process with context that isn’t always visible through conventional means.

What’s happening in BNPL is a preview of what’s coming across the broader payments landscape. Faster, cleaner, embedded payment experiences are becoming the norm. And with them comes a push to rethink how identity is validated in low-friction environments. The challenge is that traditional approaches to risk—rules-based, transactional, isolated—weren’t built for this pace.

There is an opportunity to use the right data and smarter models to maintain speed and ensure security. Early fraud detection, identity enrichment via email intelligence, and behavioral scoring aren’t new ideas, but they’re becoming newly urgent to support the growth of BNPL without becoming bottlenecks or blind spots in the process.

BNPL is going to keep growing. So will customer expectations. The question for the payments industry is how to support that growth in a way that strengthens the ecosystem, rather than stretching it thin.

Investing in earlier signals and identity intelligence that doesn’t rely on outdated assumptions is critical. Moving from reactive static data to proactive behavioral insight can reveal broader transaction patterns. In a space where speed matters, and trust matters even more, being able to quietly and confidently do both will set the leaders apart.

—Diarmuid Thoma is head of fraud and data strategy at AtData