Friendly fraud and refund abuse require a new approach for e-commerce

The rise of online shopping and e-commerce in the U.K. is showing no signs of slowdown, with IMRG Capgemini Online Retail Results revealing that online sales grew 74% year-on-year in January 2021, which is the largest monthly year-on-year growth rate since 2008.

At the same time online merchants’ revenues are growing rapidly — Uber Eats revenue was up 224% year on year in Q4 2020 — but so is their exposure to various types of online fraud.

Research shows that growing retail fraud attempts can have a significant impact on a merchant’s bottom line. According to the LexisNexis True Cost of Fraud study, each dollar of fraud costs retailers $2.94 in fees, lost merchandise, security, redistribution and other associated costs.

Not all fraud will be committed intentionally, with consumers often acting in a confused or ill-informed manner rather than with malicious intent. But so-called "friendly fraud" and refund abuse are two types of increasingly common fraudulent activity that merchants need to understand and manage to protect their business.

We need to clearly differentiate between these two types of fraud that often get confused, and understand their root causes. Friendly fraud is when a customer orders goods online but then disputes the transaction with their issuing bank via chargeback rather than requesting an exchange or refund directly from the merchant. Chargebacks involve a forced retrieval of funds from the merchant by the issuing bank, which are then given back to the customer.

This can be a complicated fraud type as, on occasion, the customer may have simply not recognized the billing descriptor and flagged the transaction as fraudulent to their issuing bank without any malicious intent. Conversely, the customer may also know full well what the charge is and decide to intentionally pursue this type of fraud.

While chargeback is certainly a legitimate mechanism to protect consumer rights, its relative simplicity and convenience means that fraudulent consumers can abuse it fairly easily. It is estimated that 86% of all chargebacks are likely to be friendly fraud.

The growth of friendly fraud has been confirmed by Ravelin’s Online Merchants Perspectives report, with around 40% of merchants reporting an increase of this form of fraud. In fact, friendly fraud was found to be the third most common type of fraudulent activity, behind online payment fraud and account takeover.

Refund abuse differs from friendly fraud in that it doesn’t involve the chargeback process via the issuing bank, but instead takes advantage of a company’s refund policy and its terms and conditions.

Because of the pandemic, many merchants have made their refund policies more flexible but inadvertently also introduced a higher level of risk. According to the same Ravelin report, refund abuse was found to be the fastest-growing type of fraud, with 51% of merchants experiencing an increase in refund abuse in the past 12 months.

The significant rise in refund abuse may also be related to the changing buying patterns and rise in contactless delivery of goods due to the pandemic. Many online retailers are leaving products outside the customer’s front door which means the delivery may not be confirmed and the customer has the opportunity to claim that they never received the goods.

The lines between a genuine and malicious returns may sometimes be difficult to draw. For instance, food delivery services may find it difficult to prove (especially with contactless delivery) that the meal was indeed cold, while fashion companies can encounter "wardrobing," as customers return clothes after wearing them once, often damaged, dirty or unfit for resale.

Returns (be they legitimate or fraudulent) are a financial strain for merchants, with the growing trend of refund abuse now more than ever requiring a carefully managed response to prevent significant financial loss.

Despite the exponential growth in online transactions and the proliferation of customer channels (like mobile apps, call center orders) many companies track and review fraud manually, which is still an important method. However, managing chargeback disputes can be a protracted and resource-heavy process. If a merchant’s chargeback-to-transaction ratio becomes too high, it even risks having accounts disabled.

The key to managing risk related to friendly fraud and refund abuse lies in gaining in-depth customer insights, predicting their behaviour and understanding where the threats are coming from. Merchants need to further their knowledge of fraudster activity to boost detection accuracy.

AI and machine learning-powered analytics helps spot unusual patterns and detect fraud. When it comes to chargebacks, machine learning models have the potential to identify suspicious behaviour even when there hasn’t been a chargeback yet. With refund abuse, they can help identify serial returners and their linked accounts through network analysis. These insights enable merchants to set limits on the number of refunds per customer, or prevent certain customers from requesting a refund for a period of time.

Fraud detection and prevention technology must also be complemented with clear return policies and a strong customer service that clearly communicates in a timely manner, and ensures that confused but loyal and well-intentioned customers can continue to purchase from merchants.