Merchant Fraud Journal

Buy Now, Pay Later Fraud: How to Stop Chargebacks

Buy now pay later fraud, or BNPL, a system that allows customers to access ‘instant credit’ at the point of sale, is progressively gaining steam in the industry across various eCommerce verticals.

With all types of BNPL, the merchant can still get the money they need, but instead of paying the total amount at the checkout point, customers spread out the cost of an item over installments.

It helps merchants boost their sales and allows customers to alleviate pandemic-induced economic pressures.

But not just that. Analysts have noted that the boom in BNPL adoption is because the concept appeals to some virgin market segments. That is folks who lack access to established credit channels, especially customers in less-developed credit markets, and gen-z/millennial shoppers who are always seeking out credit card alternatives.

How does Buy Now Pay Later fraud work exactly?

It’s simple.

Win, win, win – service providers make their money by charging a fee to merchants, which is between 2% to 8% of the transaction.

One estimate shows that consumers amassed close to $100 billion from retail purchases with BNPL programs in 2021, a significant rise from $24 billion in 2020 and $20 billion in 2019. Another research found that more than half of all buyers have used a BNPL service at least once – nearly a 50% increase in one year.

But it’s not all bliss, as you’ll find in the following section.

bar chart showing by now pay later adoptions by generation 2019-2021

What are the downsides of offering Buy Now, Pay Later

Aside from the many attractive benefits, BNPL also comes with undeniable risks.

Paying through a BNPL process is unbelievably easy: a seamless checkout experience requiring few clicks, zero processing fees, and instant credit without a cumbersome approval process.

And as with any business construct, such effortless procedure often creates loopholes for fraudsters to game BNPL systems and services.

By and large, BNPL fraud generally manifests in the following ways.

The first and most prevalent instance of fraud in BNPL is fraudulent chargebacks. With BNPL fraudulent chargebacks, the actor takes advantage of the Buy Now Pay Later feature that permits consumers to settle debts using credit cards and pay their debts using a stolen credit card.

When the actual owner of such a card notices the payment, they force a reversal with a chargeback, and the BNPL provider is left holding the bag.

Another instance of BNPL fraudulent chargebacks is when an opportunistic online shoplifter uses their card to make a transaction and then file a chargeback. That technique is known as friendly fraud. And in each case, for every $1 of a chargeback, the merchant loses at least $3.

BNPL providers give every new account a default credit line as part of the process. The lending limit for such statements increases with established indices such as account, transaction frequency, and payment history.

Online shoplifters often capitalize on that default credit principle with synthetic or fake accounts. They equally target existing accounts with phishing, credential stuffing, and SIM card cloning to rip genuine customers off to increase their bounty. 2021 Identity Fraud Study by Javelin Strategy & Research noted that about $13 billion in losses were due to identity fraud, where cybercriminals steal personally identifiable information and use it for their gains.

Many BNPL providers allow buyers to sign up with primary documents such as proof of identity (like a driver’s license) or proof of address (like utility bills).

In many instances, fraudsters use documents obtained from questions sources, such as stolen mails or data breaches, combined with their data to create fake accounts that help them bypass fraud and credit checks. For instance, an online shoplifter could provide a phone number from a disposable phone to pass a one-time password requirement, a drop-off address for delivery to avoid traceable addresses, and synthetic data for the other identity information.

The BNPL, in their due diligence, will usually take into consideration the person whose data was used in deciding whether they can repay the bill. And the fraudster will likely use a virtual card for initial payments or checks and dispose of them before the repayment date.

With that, they enjoy the same introductory line of credit offered to actual consumers, with no intention of ever making repayments on the transaction.

How to stop BNPL fraud effectively.

Some BNPL frauds are hard to crack because providers aren’t always sure how to distinguish when someone lacks the money to make the bill and when they generally don’t intend to make any repayment. Detractors have noted that the Buy Now Pay Later payment option invites payment defaults.

For example, consumer protection advocates have been vocal in that it pushes people into debts:

“There is a risk that BNPL schemes may attract people who are already in financial difficulties and may be struggling to make their existing bills and payments.”

Service providers must devise preventive and detective security protocols to counter the rising chargeback fraud onslaught and other forms of BNPL fraud.

That means, first, providers must ensure that every information customers provide are legitimate. That will mean establishing the credibility of phone numbers, emails, addresses, and so on.

Equally crucial, providers should consider establishing third-party validation protocols too. Such instruments can help ensure the name on a transaction matches that of the resident at the delivery and billing location provided. Combining third-party verifications with proof of identity verification at sign-up will help BNPL providers thwart incidental fraud while maintaining a seamless user experience.

Further, BNPL providers can also use consumer behavior pattern recognition as a reference to intuit chances of fraud. For instance, if a customer has a history of “never pay” fraud incidents or has repeatedly filed chargebacks, chances are they’ll carry that pattern forward. 50% of consumers with a successful chargeback will do it again in less than two months.

Establishing standard protocols that move transactions into pe-defined buckets can also be an added safety measure. That can mean creating a logic like “reject, accept, or manual review” to ensure that questionable transactions aren’t slipping through the cracks.

More so, using technology tools such as 3D Secure on high-risk transactions can help BNPL providers limit fraudulent chargebacks. As BNPL is about cost efficiency, BNPL providers can reduce the associated costs of deploying 3DS by integrating simple validation before moving transactions for 3DS. That helps ensure only potential fraudulent orders are going to 3DS and not every single order.

Those are standard practices that help to stop BNPL fraud.

However, the ultimate gamechanger is to use artificial intelligence and machine learning to excavate uncommon insight from over 50 data points. Such an informed fraud mitigation approach looks beyond the easily spoofed points of origin to track bots and pierce their intent.

Using fraud protection apps such as Chargeflow’s world-first fully automated chargeback framework gives you the most exceptional advantages in that regard.


This article was contributed by Chargeflow.io

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