Chargebacks... What is at stake for online store merchants? Oh, just money, reputation, time (which is money). eCommerce sellers are easy targets for friendly fraud and chargeback scams. What can be done? Chargeback guarantees sound enticing, but the best method is to prevent chargebacks from happening in the first place and align your KPIs with your anti-fraud solution provider.
What is a chargeback item?
According to Visa, a chargeback (otherwise known as a dispute) is a way for your bank that issued your card to reclaim money from the retailer’s bank when you do not get the goods or services you paid for, including if the retailer or supplier has gone out of business. For the chargeback to occur, it is sufficient for cardholders to contact the bank and say that they do not recognize a particular purchase. Although chargebacks exist to protect customers, already you can see the difficulty for online merchants -- there is a delay between when the chargeback is filed and when the merchant actually hears about it. Currently, no card company assumes the risks of this type of transaction, leaving the entire loss to the retailers. This fact, unfortunately, leaves retailers exposed to the action of fraudsters, who seek this type of loophole.
What is friendly fraud?
“Friendly fraud” is a type of chargeback. It occurs when a legitimate customer purchases a product or service online using their credit card, yet once the order is delivered they request a chargeback (refund) from their bank. It is one of the most difficult challenges that each and every online business has to encounter sooner or later. According to CardNotPresent.com, it accounts for up to 86% of all chargeback requests and costs retailers more than $11 billion per year.” The customer may claim the following:
- they didn’t receive the ordered item (although they did),
- a family member had carried out the transaction that the cardholder was unaware of
- they do not recall making the purchase
- they hadn’t been informed about the terms and conditions of subscription-based purchasing
- their cat was responsible for the purchase
OK we're kidding about the last one, we just want to make sure you're paying attention. But you get the point. :)
How does a chargeback work?
Imagine the following situation:
A customer buys a T-shirt worth $10, pays by card. The eCommerce store fulfills the order and delivers it to the customer. The customer receives the package. As soon as the courier is gone, the recipient contacts the bank (not the seller) claiming that their credit card has been charged for purchases that have never been delivered and demands a refund (chargeback). The bank, as well as the card organisation have no reasons not to believe the customer, so they accept the complaint. As a consequence, the online store that sold the T-shirt receives the demand to return the charged amount to the customer’s credit card. The merchant not only loses their product and money but also has to cover the costs associated with the whole chargeback procedure.
If the online store does not agree with the decision and claims that the customer actually received their order, it can assert its rights in court. However, the cost of such a judicial proceeding would be much higher than $10. In other words, it’s not worth it. Therefore, it comes as no surprise, that many online stores treat “friendly fraud” as a necessary evil and include it in their overall operational costs (although they shouldn’t).
As an online merchant retailer, how do you fight chargebacks? How do you prevent friendly fraud?
It is essential to get to know and deeply understand your customers. It requires careful observation enabling accurate conclusions and predictions towards their future behaviour. And there are tools out there that you can use.
In the digital world, the ability to “observe” customers is limited – most often, merchants know about their customers only as much as the latter choose to tell/show them. Therefore, it is necessary to use software that allows us to reveal more information about each of the customers individually. The process of collecting data about them and discovering interdependencies between numerous, apparently unrelated variables is called “profiling." Due to the volume and the complexity of data, one needs to apply Machine Learning for this task.
High quality “profilers” collect thousands of data points describing each person’s software, hardware, network environment and behaviour each time they interact with the service – be it an online store, a gaming platform, a SaaS product, you name it. In the case of “friendly fraud”, behaviour is the most important aspect. It’s not only what a customer is doing but also how they behave while visiting the analysed website. The point is that, you need to simultaneously collect information about, for instance, what product categories the customer is browsing, what parts of the website they are clicking, how they are using their mouse/touch screen etc. During the analysis, there are also other data taken into account, including:
- the history of previous purchases made by the users (when was the last time the user bought anything in your e-store and for what price, how often they make purchases, were there any chargeback requests before etc.).
- Device fingerprinting – allows for verification whether a given device (computer, tablet, smartphone) had been used before for a fraud attempt.
- By recognizing individual behavioural patterns of each customer, you can create their digital profile and compare it with behavioural profiles of previously detected fraudsters. It is also possible to detect behaviour indicating that someone other than the legitimate account owner is logged in, before the purchase is made (like a child instead of their parent in the aforementioned example).
Thanks to this information you can then secure the transaction, e.g. by activating a conditional authentication layer, for example a request to provide the CVV number of a card or a unique PIN code.
If the online stores owners described in the above examples had used profiling and Machine Learning solutions, they could have significantly reduced the risk of “friendly fraud”. The eCommerce store could have secured a shipment by requesting the recipient’s identity card while delivering the T-shirt. And the game publisher could have prevented a child from making a transaction by requiring a confirmation code that only the parent would know. That kind of friction should be added only where it’s necessary and the probability of fraud is high. The cost of introducing such security measures, would be much lower than the losses caused by “friendly fraud."
Last but not least. Let’s not forget about building strong relationships with your customers. Applying profiling and Machine Learning solutions should be reinforced by an excellent customer experience, as it is considered one of the most effective ways of reducing the risk of friendly fraud.
What about chargeback guarantees?
Some firms offer “chargeback guarantees,” which are intended to insulate merchants from fraudulent transactions involving unauthorised use of a credit card. There’s a substantial non-obvious level of risk tied to chargeback guarantees though. Why? When two partners want to do business together, they have to align their motivations. Issuing chargeback guarantees breaks this alignment. Merchants want to maximize accepted transactions and minimize chargebacks at the same time. A company that offers a chargeback guarantee issuing solution will simply be looking to minimize chargebacks, precautionarily turning down transactions, even those initiated by legitimate customers (high false positive rate). A recent study found that approximately 24% of declined transactions were in fact false positives. Moreover, the average cost of a false positive can be several times higher than the cost of a chargeback.
A fraud prevention firm offering chargeback guarantees can land one of three cases:
- The chargebacks they are reimbursing are greater than the fees they are charging.
- The chargebacks they are reimbursing are equal to the fees they are charging.
- The fees they are charging are superior to the chargebacks they are reimbursing.
In each of these cases there are some problems for the merchant:
Instance 1 or 2: This is an unsustainable situation and the merchant should be wary of their fees increasing at some point knowing that the anti-fraud solution might have higher negotiation power the day of the fee increase.
Instance 3: In this case, it will become quite evident that the fraud prevention solution is motivated to keep refusal rates at their maximum levels in order to maximize their revenues. It is estimated that US e-tailers lost $8.6 billion due to wrongfully declined transactions in 2016, which is $2 billion more than the $6.5 billion in fraud they could have stopped. This is, therefore, a motivational misalignment, which can be very expensive for the merchant.
Choose what’s best for you and your business
The best way to align the motives of both the merchant and the fraud prevention tool is to set up a relationship in which both parties profit when the number of legitimate transactions increases. We recommend looking at a mix of KPIs: the chargeback ratio, the denial rate and the manual review rate. Such an approach will help you make the most of your fraud prevention solution.
If you need that aforementioned peace of mind, simply acquire an elite fraud prevention system. I can assure you it will both mitigate the risk and keep fraud at bay. Online merchants have been pushed to implement deep analytical tools into their infrastructure to counter payment fraud (but many choose to remain with simple rules-based systems surprisingly). Such tools, however, should also be creating value in their core business. Make sure that your fraud prevention provider is helping you leverage this opportunity to grow your business. If you want to discuss chargebacks and chargeback guarantees, please feel free to reach out!