Driven by the COVID-19 pandemic, U.S. eCommerce sales “increased by 50.5% from 2019 to 2021,” according to an update shared by Chargebacks911.
While eCommerce growth is “predicted to slow to 9.4% year over year in 2022, online sales are expected to cross the $1 trillion mark for the first time.”
Taken at face value, this is “great news for virtual merchants.” However, as Fi911 and Chargebacks911 founder Monica Eaton notes, there are downsides.
The increase in online sales “has been accompanied by a corresponding rise in chargebacks — forced refunds initiated by customers through their financial institutions.”
Consumers dispute “at least 6 out of every 1,000 transactions — a substantial number in a country where more than 100 million credit card transactions take place every day.”
Counting added penalties and fees, “every dollar charged back represents a loss to the merchant of $4 or more.” Merchants lack the technology and/or competency “to effectively respond to invalid chargeback disputes.” The average recovery rate “for proactive merchants is 21%, even though invalid chargebacks account for 70% of total chargebacks.”
Altogether, “friendly fraud” chargebacks — cardholders “disputing a valid credit card charge — cost merchants more than $132 billion each year, making friendly fraud the leading source of fraudulent activity for merchants.”
While the major card networks are already implementing strategies to help thwart this growing problem, loopholes in the chargeback system “continue to be exploited both directly and indirectly.”
Eaton says:
“To proactively identify friendly fraud attempts, merchants need a process for providing real-time feedback to financial institutions.”
While first-party fraud is initiated by the consumer to secure a refund through their bank, Eaton contends that another type of fraud known as “second-party” friendly fraud is emerging.
Second-party friendly fraud claims “are initiated by the cardholder’s bank or credit card issuer.”
These cases often “go undetected due to the industry’s increasing reliance on automation.”
Because the claims are automatically initiated, “they are typically operating on incomplete or inaccurate feedback supported by machine learning and AI technology.”
As part of their risk mitigation, financial institutions sometimes “initiate chargebacks on behalf of their customers.”
In terms of protecting cardholders from the lack of transparency in the card-not-present environment, “the strategy makes sense — but there can be serious drawbacks.” For example, a consumer might “receive a post-purchase phone notification to confirm that a charge was legitimate.”
However, the transaction “is often authorized and settled before the customer receives the notification and decides to provide feedback on the charge.” This leads the financial institution to instigate the chargeback, “whether the complaint is innocent or malicious. Experts compare this form of digital automation to “leading the witness,” where the chargeback case stems from prompted behavior.”
Additional impacts follow; “because the merchant is now assumed to be suspect, future incidents are raised automatically.”
If the bank takes no further action, or if the merchant fails to provide any feedback to prove their innocence, the bank is “at increased risk of inviting being blamed for any potential consumer harm resulting from their ‘negligence.'”
In the absence of feedback from the actual merchant or seller, “there are no reliable standards to confirm or deny fraudulent activity.” Automation rules and AI (machine-learning modeling) are subject to error, “meaning bad data is added to the decisioning process, creating further inaccuracies.”
Fragmentation and siloed processes “compound the issue because card issuers lack sufficient information to establish a viable baseline.” Without this vital insight, what was originally intended as proactive consumer protection “is unintentionally transformed into increased costs that contribute to additional consumer harm.”
According to Eaton:
“The evolving demands of today’s consumers lead to the misuse of the protection mechanism. Cardholders don’t want to experience any friction in the purchasing process, and this includes receiving an unexpected decline. Banks want to approve all valid transactions, especially if it was made on a card they issued. But if a series of behind-the-scenes fraud checks reveal the merchant is a potential risk, the approval is flagged for a possible chargeback.”
Eaton adds:
“Unfortunately, there’s no alternate method for checking the validity of a transaction. And without more information from the buyer and seller, chargebacks are being filed by default, with consequences that increase costs and data integrity challenges for all stakeholders.”
Eaton suggests that “one reason friendly fraud continues to thrive is that both first- and second-party friendly fraud can become a fallback strategy.”
When a cardholder “files their first legitimate chargeback, they see how easy it is to get their money refunded, often without the need for a return.”
Innocently assuming this process is “no different from contacting the merchant directly, buyers are encouraged to file fraudulent chargebacks, increasing the odds that the behavior will become a repeated process.”
Financial institutions, for their part, “are motivated to keep their customers happy — not to determine whether or not they are being truthful.”
The current chargeback process “encourages an information exchange between buyers and sellers, with specific governance and oversight by each merchant and cardholder’s bank.”
Unfortunately, the network rules “do not redact the negative statistic earned by way of a chargeback — even if the merchant/seller successfully proves a case was filed in error.”
Eaton notes:
“The worst effect has been the new mindset being accepted by many customers and bank operators. For many banks, the fear of penalties or upset customers trumps common sense, logic, and justice. As a result, chargebacks have been weaponized — and this is not an easy thing to undo.”
In the absence of relevant insight for the bank to review and assess, models become static, and improvement “is unlikely.” The best way “to help resolve this and prevent bank-automated chargebacks is the transmission of merchant feedback information through their payment processors.”
Eaton asserts:
“Effectively preventing chargeback fraud — specifically the rule-based varieties — requires a two-fold merchant strategy: 1) Prevent chargebacks whenever possible and 2) Research every claim, providing timely feedback when available.”
According to Eaton, chargeback prevention and research can be a complicated, time-consuming, and resource-heavy chore.
“In-house strategies can address small, easy-to-manage issues, but the problem is usually bigger than that. Outside expertise is vital in developing and implementing a comprehensive, scalable strategy that protects the business and safeguards customers.”
Eaton says:
“Ultimately, the number-one value in leveraging software or support is not the ability to recover money from the cost of any given chargeback. It’s actually the opportunity to provide timely and necessary feedback to financial institutions. Without information to compare and assess, it’s difficult to forecast improvement.”