A rapidly growing payment option among customers, buy-now-pay-later (BNPL) is forecasted to grow to 4.5% of North American e-commerce payments by 2024, up from 1.6% in 2020. As the name suggests, BNPL enables customers to buy what they want now and pay later, in installments over time or by other methods.
Most BNPL schemes are interest-free, making this an attractive and popular option for customers with less spending power or in need of payment flexibility. Merchants benefit from BNPL schemes because they reduce customer inhibitions, decrease cart abandonment, and increase conversion rates.
Additionally, as merchants willingly pay high Merchant Discount Rates (MDR) for this option, financial companies across the board, from startup fintechs like Affirm and Klarna to large financial institutions like Mastercard enter the market. Unfortunately, the unique nature of BNPL coupled with this increased popularity opens both BNPL providers and merchants up to fraudsters.
BNPL operating models
The number of BNPL providers is increasing and the space is becoming more competitive. This has led to a variety of approaches to BNPL distribution. The four most typical BNPL operating models include:
Direct merchant integration
In this model, third-party BNPL providers integrate directly with merchants’ checkout processes, offering consumers installment options as they make their purchases. Fintechs like Klarna, Afterpay, Splitit, and Affirm use this model.
Multi-lender networks
Large card networks like Mastercard and Visa offer consumers BNPL options at checkout, with their proprietary solutions or partners. Card networks have their own network of lenders, and the financing type and fee structure varies for different transactions. Examples of this model include the partnerships between Mastercard and Vyze, and Visa and ChargeAfter.
Existing bank credit card
Existing credit card companies offer their own BNPL options for transactions above a certain amount. Companies like Chase, Citi, and American Express came up with such solutions to stay competitive, due to BNPL options like split pay and specialty POS lending offered by fintechs rapidly gaining traction amongst consumers.
White-label BNPL providers
Under this model, third-party BNPL specialists enable retailers to offer their own white-labeled financing options to consumers at checkout. Bread, Jifiti, and Limepay provide such a model.
BNPL fraud types
Each BNPL distribution type comes with its own risk for fraud. Most of the risk arises because providers often sacrifice the rigorous credit checks that usually happen before offering loans in an attempt to ensure a frictionless consumer experience. Three primary types of fraud emerge due to the low-entry barrier that BNPL poses for fraudsters:
Synthetic identity fraud (SIF)
Fraudsters create false identities by combining stolen identities with fictitious identifying information, and purchase items using BNPL options. Then, they default on their payments either immediately or after the first payment. The fraudster aims to give away as little of their information as possible, only providing untraceable or disposable personal data. For example, a prepaid phone number or a random dropoff address for delivery. SIF poses a particular challenge as sophisticated fraudsters often build good credit on a false identity before “busting out”, meaning that many show up as normal customers in most databases.
Account takeover
Fraudsters take control of a consumer’s digital account using stolen information and make purchases with BNPL before they abscond. In normal situations, such fraud would be detected in time as financial institutions usually notify consumers of payments happening from their accounts. But with BNPL, delayed payment options make it harder to detect such activities quickly. The individual whose account was taken over may not notice the fraud for weeks or even months, depending on the gap between BNPL installments.
Chargeback fraud
Some BNPL agreements require an upfront payment as part of the transaction. If a fraudster used stolen information to make the transaction, the true owner may realize that their information was used and demand a refund. Alternatively, opportunistic fraudsters use their own information but deny making the transaction. Due to the challenging nature of returning items purchased via BNPL, they might get to keep the product. Chargeback fraud occurs most frequently and thus requires the most attention.
Reducing BNPL fraud with the Fraud.net solution
With so many different forms of fraud emerging around BNPL, it is crucial to use a multi-layered approach to combat it. A good first step is to review shoppers’ credentials while finding a balance between security and a frictionless customer experience. Policies to support people who struggle with making their installment payments on time can reduce bad debt and even first-party fraud.
Merchants can also pitch in to mitigate chargeback fraud by updating their return policies and making it difficult for fraudsters to implement chargebacks. Finally, it is important to thoroughly verify the consumer’s identity when they fill out the BNPL application, while still offering them a seamless transaction experience.
Fraud.net’s suite of AI-powered fraud-prevention solutions can help protect your organization from all types of fraud:
- Application AI helps with identity proofing, verification, and authentication
- Transaction AI’s machine learning models assess transactions in real-time and correlate that across client data and our global anti-fraud consortium to provide a risk analysis and insights into the likelihood of fraud
- Our Collective Intelligence Network provides a detailed and anonymized history of previous BNPL transactions, which helps understand the trends of earlier fraudulent purchases at various merchants and offers vital insights into the potential for BNPL fraud.
- Link Entity Analysis also helps you identify any applicants tied to known organized fraud rings
- To strengthen your defenses further, Fraud.net’s solution enables you to customize your fraud-prevention ecosystem to suit your needs through easy integrations with 70+ third-party APIs.
Get in touch with our experts now and book a free demo to find out how Fraud.net can help you get rid of BNPL fraud!
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