Working in risk management comes with a certain amount of difficulties. But when the cardholder is in fact the perpetrator, it only gets more complicated.
With the pandemic forcing more consumers to turn to eCommerce, the issues of friendly fraud and more prevalent than ever before.
What Is Friendly Fraud?
Friendly fraud occurs when a cardholder disputes a transaction on their account despite the fact that the card was not stolen. This differs from genuine CNP (card not present) fraud, where a criminal actually steals the card information to make unauthorized purchases.
Friendly fraud can take different forms. It’s known as “family fraud” when a close family member, such as a child, uses the card without the cardholder’s permission (for example, buying apps through a parent’s account). Another form, often called “first-party fraud,” involves an accidental chargeback request, such as when a cardholder forgets they made the purchase. Intentional friendly fraud, on the other hand, occurs when a cardholder knowingly lies, claiming a legitimate purchase was unauthorized to receive a refund.
In all these scenarios, friendly fraud is especially difficult for businesses to dispute. They must prove whether the purchase was made with genuine intention, through an honest mistake, or by someone close to the cardholder without authorization.
Five Examples of Friendly Fraud
Here are some examples of what is considered friendly fraud:
- Accidental friendly fraud: When a customer makes a purchase but requests a refund from the bank due to either not recognizing the transactions in their bank account or forgetting it entirely.
- Intentional friendly fraud: An act of genuine fraud. Here, a consumer makes a purchase knowingly but still requests a refund from the issuing bank. This sometimes can involve what is known as double dipping, including receiving a refund and chargeback while keeping an item.
- Merchant error: The issue lies with the merchant with a range of possible reasons such as lack of descriptors on a bank statement, missing products, delivery issues, etc.
- Family fraud: Also known as shared card fraud. An unauthorized purchase is made with a card that is not directly administered by the cardholder e.g: a child buying in-app purchases for a mobile game using their parents’ card.
- Policy abuse fraud: Given the demand from consumers for a seamless returns policy, some buyers will abuse a merchant’s availability of refund requests.
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How Serious Is Friendly Fraud?
With consumer behavior changing due to the pandemic, digital transactions have increased dramatically resulting in more frequent friendly fraud cases.
According to statistics from Expert Market, friendly fraud is increasing every couple of years at a rate of around 41%, and 86% of chargebacks are “probable cases of ‘friendly fraud’”.
The COVID-19 pandemic has also greatly accelerated the increase in friendly fraud cases, especially for travel and ticketing companies. In many ways, chargebacks have become weaponized by consumers, who know they can put pressure on a company by asking for a refund directly from their bank. This is done to protest a return or cancellation policy, for instance.
As Elena Emelyanova, Senior Payments and Fraud Manager at Wargaming put it in our podcast:
“I would say that with COVID, it definitely brought some new trends. And what is curious that I see now is that people become more sophisticated and more educated. Even friendly fraud or real fraudsters, they turn to read. We have some cases where we see that people know how to fight chargebacks, or they know the restrictions from our side, from a merchant’s side. People who didn’t understand the difference between refund and chargeback. Now they know about it.”
Friendly Fraud vs Traditional Fraud
The main difference between friendly and traditional fraud is that the former is often opportunistic in nature and is done by a known person: the customer or legitimate cardholder.
Meanwhile, traditional fraud is conducted by a third party and is mainly associated with career criminals, who have knowledge of how fraud schemes work and often have access to specialized tools that help them hide their true identity, location and intentions.
However, you will want to bear in mind that the consequences of these two types of fraud for merchants can be similarly devastating – and that, despite its lack of sophistication, or perhaps exactly because of it, friendly fraud is sometimes even more difficult to detect than traditional fraud committed by a professional fraudster.
Consequences of Friendly Fraud to Your Businesses
When a customer bypasses the merchant’s refund policies to go directly to a bank, a chargeback fee is assigned by the acquiring bank to cover any of the related costs.
A merchant typically has 45 days to dispute a chargeback. However, the process can be tedious since the cardholder has the upper hand – unless you can provide specific evidence.
For merchants, keeping their chargeback ratio as low as possible is imperative to ensure maximum profits.
Furthermore, the cost of shipping the original item has to be factored in with other operational costs.
How to Prevent Friendly Fraud
Despite being in a weak position when faced with a dispute, merchants can take several steps to combat and reduce friendly fraud and minimize risks.
Friendly fraud prevention is, in essence, similar to standard chargeback fraud prevention, as well as closely associated with refund fraud prevention. You want to identify the cardholder and verify they are the same person as your customer, as well as log information to prove that – and their good intentions.
Specifically, SEON allows you to do the following to combat friendly fraud:
- use digital footprinting, device fingerprinting and other real-time checks to verify customers’ identities and intentions
- keep granular, meticulous records to assist merchants with any chargeback recovery disputes
- know whenever a customer tends to exhibit suspicious patterns that can indicate friendly fraud
- monitor whether a customer has been a repeat offender of refund and other requests
- help provide evidence to customers, banks and payment processors that the merchant did their due diligence
- set up custom rules to flag all the above as well as other patterns of friendly fraud
- get machine-learning rule suggestions based on previously-seen attempts that can help with friendly fraud.
Uniquely, SEON will investigate the social and digital footprint associated with the customer’s provided email address and phone number, as well as their IP address. Combined with device fingerprinting, behavioral data and velocity checks, the resulting profile will make it clearer whether this person is who they say they are.
However, because friendly fraud is almost always the same as first-party fraud, the customer is indeed likely to be the cardholder. Therefore, your efforts also ought to focus on identifying suspicious, recurring patterns – for example, too many refund requests for a legitimate customer – as well as keeping records that you did your due diligence, to assist with any disputes.
On your end too you can consider making adjustments to your refund policies and other policies to provide less opportunity for chargebacks – as they cost merchants much more than refunding the same sale directly:
- Provide an easy means for customers to contact you, so they don’t turn to their bank straight away.
- Create and observe a carefully worded refund policy that allows you to request more specific evidence from customers, or even to ask them to send the item back, when you can reuse it.
- Consider disputing chargebacks. Incorporating fraud-fighting data such as social media lookup details in the chargeback recovery process can also make the bank decide in your favor. While a cardholder can claim that the transaction was unauthorized, if you can prove there was no attempt to resolve the issue from their side, you convince the bank that the customer isn’t acting in good faith.
- Consider communicating with the customer. You can understand whether it was chargeback fraud or friendly fraud, and treat it as an opportunity to gain insights into the customer experience
Key Challenges When Preventing and Fighting Friendly Fraud
A major issue in separating the two cases is that, from the point of view of an anti-fraud system, both of these transactions will look legitimate. The buyer has physical access to the card and is often the same person who is ordering the item or service.
Fraud prevention systems find friendly fraud hard to spot since it’s committed by legitimate customers doing legitimate transactions.
There are no patterns to spot, no way to detect malicious intentions, it sometimes comes down to a matter of “your word vs mine”.
Another key issue is the lack of awareness from the consumer of chargeback fees. A recent study by Expert Market revealed that 81% of cardholders have filed a chargeback out of “convenience”.
The consumers’ preference for convenience and lack of payments knowledge ultimately means that merchants are facing further losses to their revenue.
Conclusion
Blacklisting a customer is the worst-case scenario. But sometimes, it’s the best option.
Before it comes to that, however, you can implement effective chargeback management software that mitigates risk without impacting your frictionless user experience.
At SEON, we believe merchants can take control of the chargeback processes by integrating social media lookup into your KYC process.
You can read more about how we do it in our case studies with a crypto exchange or marketing software to see how SEON can decrease your friendly fraud rates today.
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Ask an Expert
Frequently Asked Questions
When a chargeback is claimed, often the issuing bank immediately refunds the customer with a provisional credit to that customer’s account. It is then up to the merchant if they wish to dispute and then an investigation will take place.
Sadly it’s near on impossible to 100% confirm if friendly fraud as the customer can simply deny any claims.
For merchants, proving friendly fraud is a challenge, because it is a form of first-party fraud, where the fraud is being committed by the legitimate cardholder. You can prove friendly fraud to the bank or any other stakeholder by demonstrating that you have used best safety practices throughout the ordering, payment and fulfillment process. C
Machine learning can be trained to detect unusual patterns in purchases and other behavior, so it can flag potential cases of friendly fraud. What’s more, it always improves over time, so it is more likely to do so in the longer run.
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Learn more about:
Digital Footprinting | Browser Fingerprinting | Device Fingerprinting | Fraud Detection with Machine Learning & AI
Sources:
- Qredible: In-App Purchases: Consumer Protection Rights in the UK
- Expert Market: Chargeback Fraud Statistics 2021: Everything You Need to Know About Chargeback Fraud
- Justice – United States Department of Justice: New Orleans Man Sentenced To Six Years in Prison for Charges Related To Credit Card Fraud Conspiracy
- Razorpay: Here’s Why Blacklisting Customers Is Bad for Your E-Commerce Business