BPM Analytics
Why BUY NOW, PAY LATER is the new playground for fraudsters
When you go shopping today, there is hardly an outlet that accepts cash payments. Digital disruptions, from credit cards to online banking and more recently the Unified Payments Interface (UPI), and a younger generation of customers, the traditional modes of payment are declining. A popular mode that has emerged from this disruption is “Buy Now, Pay Later” (BNPL); a short-term financing solution that has been a boon for shoppers and merchants across the retail and e-commerce industry. This facility gives consumers with financial difficulties the luxury to purchase products and make interest-free payments on a future date.
Why BNPL is winning over the consumers
So, what does BNPL essentially offer?
- Pay within 30 days,
- Pay in 3-6 Installments, or
- Split the cost for a longer duration but with low interest rates
This is slightly different from the other digital payment modes, such as credit cards, as it is easier to execute, affordable with no or lower additional cost due to reduced interest, offers instant approvals, and requires lesser checks such as credit score. Many popular brands have accepted this format of payment, including Adidas, Airbnb, Amazon, Expedia, Instacart, H&M, and GameStop.
Post the pandemic BNPL saw a meteoric rise as the preferred mode of payment, especially in the bracket of low-income consumers who may not be eligible for credit cards due to a poor credit score. As per a recent survey done by The Ascent, about 27% more customers in the US favoured BNPL in 2021 than in 2020. In fact, a study by Research and Markets suggests that BNPL is expected to reach $ 443 Bn by 2028 in the US. With BNPL, users believe that they are empowered to purchase products that they considered outside their stipulated budget.
It’s no secret that providers are capitalizing on the younger generation who prefer alternative payment methods, to the traditional modes. This could be the main driver of growth in the BNPL segment. The popularity of BNPL among younger shoppers can be attributed to the ease of use, adequate time to make full payment, along with the use of developing technology like AI and Machine Learning.
BNPL is on the rise and is anticipated to become a universal mode of payment in the coming years. Having said that, scaling up BNPL to this level comes with its own challenges, as is the case with any technology. A glaring loophole for fraudsters is BNPL’s facility to purchase a product without having to pay anything for a month, a factor that can be highly exploited.
The lurking threat of fraud in BNPL
With the easy access and availability of leaked personal credentials on the dark web, fraudsters can target multiple innocent profiles for their malicious use. Another major fraud is synthetic identity theft, wherein the imposter can steal real identities and combine them with falsified information to create hard-to-detect synthetic accounts. For example, a fraudster can take over an account with stolen credentials or create a synthetic profile. Using this disguise, they order various goods to be shipped to different locations and for which they obviously have no intention of paying. To cleverly maneuver payment, the fraudster can pick the BNPL option from the payment gateway. This can lead to multiple chargebacks and bad debts for the merchants.
Apart from this scenario, false chargebacks may also stem from fake merchants. The gap between the BNPL providers and the merchants’ systems is a serious area of concern. With little visibility and experience when it comes to BNPL fraud if merchants do not tackle this area seriously by drawing a well-defined fraud methodology, they are paving the way for bigger losses.
There has been an increase in triangulation fraud, refund abuse, and friendly fraud which are common in the BNPL space. Unfortunately, new account abuse, fraudulent chargebacks, transaction laundering, never-pays fraud, and trojan-horse fraud are a few of the other kinds of fraud that now plague the BNPL market. Furthermore, including BNPL, a massive estimated loss of $206 Bn is expected by 2025 due to online payment fraud.
Now, various companies deploy several measures to mitigate these fraudulent transactions. Companies across the BNPL ecosystem need to implement special defenses against such attacks. It is crucial that Data Science, Machine Learning, and other technical tools be used to fight and reduce such fraud. There are other measures as well that retail and e-commerce companies can adopt, such as anti-money laundering checks, identity validation, device and IP evaluations, consumer behavior analysis, link analysis, anomaly detection, and fraud screening by manual investigations.
We can only expect online payment fraud to get worse before it gets better in the coming years. With the growing demand for BNPL, there lies the possibility of the evolution of different kinds of fraud. Organisations, along with their risk management teams, should be armed with adequate tools and technologies, Fraud management solutionsand strategic plans of action to defend the business without sacrificing customer experience.
