It’s been a year of weak growth in the US market in 2023, as the globe’s consumption powerhouse has adjusted to tightened monetary conditions caused by the fight against high inflation. The American consumer, faced with declining purchasing power due to relatively high inflation, turned to credit card debt. US consumer credit card debt exceeded the USD 1 trillion mark this year. And with debt climbing and real disposable income declining due to inflation and a weak economic environment, it’s no surprise that first-party misuse is booming.
First-party misuse is when the customer commits behaviour that defrauds, either intentionally or unintentionally, the merchant of legitimately earned funds. In terms of what merchants can expect to face this holiday shopping season, first party misuse will be seen through a combination of return fraud, as well as heavier than usual volumes of first-party misuse chargebacks.
In 2022, a senior Visa employee revealed that first party misuse chargebacks (also known as friendly fraud chargebacks) had grown by 20%-30% ‘depending on the market’, according to Axios. For 2023, we, at Justt, are expecting continued growth in friendly fraud chargebacks based on the majority of North American merchants we surveyed for our 2023 Chargeback Pulse reporting increased chargebacks this year. Our counterpart consumer survey of the US and the UK also found an increase in the share of people filing chargebacks this year.
For return fraud, the statistics are less clear on trends. However, a recent survey by Riskified found that policy abuse, which includes return fraud and other forms of first party misuse, is costing retailers around the globe USD 100 billion annually.
Looking just at return fraud, the scale of the problem is easy to imagine when you consider that USD 212 billion in ecommerce merchandise sold to Americans was returned in 2022, equivalent to 16.5% of total US ecommerce sales, based on National Retail Federation statistics. Of that USD 212 billion in returns, nearly 11% or USD 22.8 billion was estimated to be return fraud.
Elsewhere, in Europe, major retailers have complained of an uptick in large-scale return fraud, as professional fraudsters look for easier ways to make money than payments fraud, now that 3DS 2.0 has been widely implemented as part of PSD2. Meanwhile, how-to guides such as Bob’s Refunding eBook, are circulating online, instructing newbies on how and where to perpetrate return fraud and get undeserved refunds.
While when measured against gross sales, the costs of friendly fraud chargebacks and return fraud may seem like a manageable cost of doing business, when compared to retailers’ net profit margins, it is more apparent just how damaging these forms of fraud are to retailers’ bottom-line results and financial viability. With chargebacks, for every USD 1 reversed, merchants lose at least USD 2.40 in total costs. For every USD 100 of returned merchandise, USD 10.40 is lost to return fraud, according to the National Retail Federation. With both friendly fraud chargebacks and returns fraud, the damage is deeper than it first appears on the surface.
It is estimated that 40% of annual chargebacks and 25% of annual returns in the US are made on purchases that occur between Thanksgiving and New Year’s Day. That means if first-party misuse is growing, you can expect it to show up in your post-holiday results.
Machine learning and behavioural analytics can be used to identify anomalies in consumer behaviour surrounding returns. When orders display signs of suspicious behaviour, they can be sent to a merchant’s fraud prevention team for manual review, and the order can be cancelled, if necessary. By analysing historical transaction data, product preferences and return patterns, retailers can identify customers who consistently exploit return policies.
Retailers can then implement targeted measures, such as limited return options or increased scrutiny, for these individuals. Having systems in place to analyse which SKUs are problematic is also key, as profit margins on heavily impacted SKUs will need to be adjusted to account for return costs.
For friendly fraud chargebacks, it’s crucial to implement a post-transaction chargeback solution, whether internal or external, that helps the business collect evidence and refute chargebacks at scale. Given the growing nature of this problem, automation will be important for dealing with chargeback volumes during peak seasons. And like with return fraud, some chargeback solutions on the market now integrate machine learning into their offerings. The use of supervised machine learning in chargeback evidence building and representment enables the optimisation of the win rate by continuously examining all the variables that go into a successful representment.
Over recent years, retailers have gone through a paradigm shift from ‘the customer is always right’ to minimising the financial risk when the customer is in the wrong. Regardless of whether first-party misuse involves returns or chargebacks, state-of-the art solutions are going to implement elements of automation and machine learning. This technological leap is necessary to address the growing scale of the problem, whether during the peak holiday shopping season or throughout the rest of the year.
This editorial is part of The Paypers' Fraud Prevention in Ecommerce Report 2023-2024, the ultimate source of knowledge that delves into the world of fraud prevention, revealing the most effective security methods for companies to stay one step away from bad actors and secure their businesses.
Roenen Ben-Ami, Co-Founder and Chief Risk Officer of Justt, is an expert in the field of payments and chargeback mitigation. Previously, at the payments service provider Simplex, Roenen built the Chargeback and Merchant Risk teams that successfully recover millions of dollars a year.
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