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Home » How to Prevent Buy Now Pay Later Fraud
How to Prevent Buy Now Pay Later Fraud
Buy Now Pay Later

How to Prevent Buy Now Pay Later Fraud

By Andrew11 May 2022Updated:11 May 2022No Comments4 Mins Read
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Knowing how to prevent buy now, pay later fraud (BNPL) is essential to providing the “instant financing” option many consumers expect in order to facilitate larger sales at faster speeds, especially for those who can’t access or prefer to avoid interest-accruing payment methods like credit cards. This is because BNPL can present significant risks to retailers unprepared to fend off the many types of BNPL fraud.

Here are five ways to prevent buy now pay later fraud that you can start implementing immediately to protect online transactions from account takeover, repayment with stolen cards, and more.

Table of Contents

  • Validation is the most important way to prevent buy now pay later fraud
  • Confirm data points to prevent and detect account takeovers
  • 3D Secure can prevent buy now pay later fraud automatically
  • Use rules-based risk assessments
  • Detecting anomalies goes a long way to preventing BNPL

Validation is the most important way to prevent buy now pay later fraud

Consumers today are quick to abandon transactions or sign-ups that take too long. For this reason, many companies offering BNPL have made the sign-up process so easy that fraud is all too easy to commit.

Simple, manual measures like looking up the address to confirm that it is a real residence or more complex checks like biometric scans can protect both the customer and the company offering BNPL with minimal interruption to the purchase experience.

Confirm data points to prevent and detect account takeovers

Account takeover (ATO) is one of the oldest types of fraud, far predating eCommerce. In the digital age, this type of fraud can occur much faster and do more damage to the victims in the time it takes to spot account anomalies. Companies offering BNPL can be defrauded by a cybercriminal using the otherwise good credit and buying reputation of a legitimate customer’s identity.

Requiring security measures like one-time passwords (OTPs) isn’t enough; make sure to confirm that the phone number submitted for the OTP matches the account information on the BNPL. This quick check can help prevent ATO. Also consider implementing countermeasures, such as rate limits and time-based account freezes, for extra precaution.

3D Secure can prevent buy now pay later fraud automatically

“3D” in 3D Secure stands for ‘three domains.’ The first is the card issuer; second, the retailer receiving the payment; and third is the 3DS infrastructure platform that acts as a secure go-between for the consumer and the retailer.” While 3DS adds an extra step in the purchase process, it protects the customer, their bank or card-issuing institution, and the retailer offering BNPL. 

Including 3DS, especially for high-risk or high-value BNPL purchases, can protect against chargebacks and fraud from stolen credit cards. Retailers can minimize costs by performing manual checks like address verification first.

Use rules-based risk assessments

In the eCommerce age, fraud is inevitable. Learn from it. Using data from past fraud incidents is the most reliable method for establishing a set of rules to detect and prevent future fraud – and to avoid slowing or stopping legitimate transactions.

It may seem like common sense to use both credit and fraud risk to make decisions about a BNPL charge’s authenticity, but this can be too much or conflicting data. Instead, create rules based on internal data from past fraud, like speed of transaction and transaction amount, that will flag transactions that meet the rules. Human workers can then continue investigating and either pass or halt a BNPL transaction.

Detecting anomalies goes a long way to preventing BNPL

Criminals evolve along with the countermeasures meant to deter them. The current “final step” in BNPL fraud prevention strategies is the use of machine learning. This fraud-prevention method expands on rules-based risk assessments by employing machine algorithms. Machines can assess many more data points at much faster speeds than humans. And machine learning lets companies offering BNPL use third-party data to assess transaction validity even if the individual company doesn’t have enough fraud data to compare against. 

Collect telemetry data like endpoint information and run it against machine learning algorithms to spot patterns of chargebacks or never-pay fraud without slowing down legitimate BNPL transactions.

Buy now, pay later is a great option to make eCommerce available to more customers, especially those that may not have access to traditional financing. But take steps to protect against the many types of fraud common to BNPL before adding BNPL to your purchase options.

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