Buy Now, Pay Later (BNPL) quickly rose to become an alternative payment staple during the pandemic, appealing to millennials and consumers wanting to get that ‘longed for’ purchase or just make ends meet. A 2021 study conducted by The Ascent noted:

  • 56% of Americans have used a buy now, pay later service.

  • Among BNPL users who have utilized the service more since the pandemic started, 41% say they've done so to conserve cash in case of an emergency, while 25% say it's because they lost income.

  • 31% of buy now, pay later users have made a late payment or incurred a late fee.

  • 36% of BNPL users say they are at least somewhat likely to make a late payment within the next year.

But while consumer payments lapses will account for a portion of BNPL losses, fraudsters exploiting vulnerabilities in this relatively new and growing payment method, are also cause for concern. According to the credit bureau Experian, 2022 will see a sharp rise in fraud targeting BNPL.

That’s because BNPL offers certain unique attributes that make it particularly attractive for would be wrongdoers, including:

  • Approval of immediate credit decisioning at the time of purchase; impairing normal due diligence practices.

  • The lengthy payment window, which opens the door for bust-out payment schemes.

  • Application Programming Interfaces (APIs) ascertaining creditworthiness, increasing chances for account takeovers, synthetic identity theft, and never-pay fraud.

Here are a few of the more notable fraud schemes in the BNPL space.

Synthetic Identity/Account Take Over (ATO) Fraud—when forged or unreal documents (e.g., social security number, driver’s license, or bank account numbers) are submitted using items and information easily created or acquired through illicit means (like a data breach or phishing attack).

Card-Not-Present Fraud—perpetrated by fraudsters who utilize fake account and data to execute the initial low dollar payment required for a BNPL purchase and evade paying the remaining balance.

Chargeback Fraud Claim—mostly tied to “friendly fraud,” when account owners or family members claim to have never made transactions for a legitimate purchase and request that funds are returned to their account, triggering chargebacks and related fees.

Transactions Laundering Fraud—occurring when a collusive merchant uses an authorized account to move transactions for an unauthorized or underground store selling illegal products or services.

Here are some suggested measures to address this surge in fraud trends.

Expansion of Real-Time Data Assessment-of email addresses, phone numbers, card BINs, IP addresses in a real-time data share environment that allows for a more robust evaluation of the requestor(s).

Use of Rule-Based Risk Assessment--that pulls in historical data to help identify potential imposers or ATO attacks. It is important to mention that while dollar amount and velocity assessments serve as a suitable place to begin analysis, fraudsters are making themselves more familiar with system rules. Thus, the ability to utilize “think outside the box” tools is imperative.

Merchants offering a BNPL option must manage fraud prevention strategies that also balance a frictionless purchase experience – a key strength for those entities that do it well. Fortunately, AI-powered solutions are increasingly available and becoming more sophisticated in effectively fighting fraud.

Alan Nevels is ICBA Bancard’s senior vice president of card risk and merchant services.