Identify and Fight First-Party Misuse
Identify, monitor, and take action against rising first-party misuse—including return abuse, refund fraud, and chargeback fraud—before it eats into your margins.
In 2023 and 2024, first-party misuse became one of the biggest trending issues for commerce businesses worldwide. This trend of customers abusing or misusing refund, return, and chargeback processes for financial gain leads to considerable financial losses for merchants of all sizes in nearly all industries.
If history has taught us anything, it’s that fraud only gets more sophisticated over time, and those who commit it are always innovating new ways to get something for nothing. As such, it’s our responsibility to openly communicate with our networks about the fraud trends we see, and to innovate on new ways to protect ourselves.
Return Abuse
If you sell goods and services, you have a return policy—accepting and processing returns is an expected and understandable part of doing business. Unfortunately, in a time where online shopping is king and fraud is becoming an industry unto itself, returns have now also become the newest target for fraudulent activity.
Return abuse typically involves customers purposefully abusing your return policy to make money, save money, or get an item for free. Examples include:
Returning Used or Damaged Items
"Try and Return" - Shopping Behavior
Sending Back an Empty or Incorrect Package
Exploiting Free Shipping Thresholds
Keep in mind: Fighting return abuse is tough and requires a delicate balance of priorities for your business. A generous return policy can improve customer satisfaction and retention, but it also invites this abuse. If you crack down to reduce returns, you may drive away legitimate customers, damage your brand reputation, or even see an increase in chargebacks from frustrated buyers who couldn’t get their money back.
Refund Fraud
Slightly different from return abuse, refund fraud involves exploiting loopholes in your refund policies to make financial gains. Typically the fraudulent party attempts to deceive or scam your business into giving them money even though they aren’t entitled to any sort of refund. Examples include:
Fraudulently claiming they didn’t receive their full order and requesting refunds on the “missing” items
Requesting multiple refunds on the same item
Requesting a refund on a transaction they’ve already charged back (i.e. double dipping)
Creating fake receipts or altering real receipts to request refunds for purchases they never actually made
Chargeback Fraud
Chargebacks are unfortunately an expected and expensive part of doing business online. They’re designed to help customers protect themselves against bad actors or identity thieves, making it possible for them to get their money back for purchases they didn’t make or when they can’t get an appropriate refund for valid reasons. As a part of the recent rise in first-party misuse, we’re seeing ever-increasing incidents of customers abusing the chargeback process to get money back for purchases they did make but want to circumvent paying for.
In addition to the losses your business incurs by refunding a customer for their disputed transaction, you’ll also pay chargeback fees and waste time and resources in-house or via vendors going through the dispute process. As such, chargeback fraud can quickly put a significant strain on your resources and finances. Examples of this type of fraud include:
Disputing a purchase they forgot about (i.e. friendly fraud)
Disputing the same purchase they already returned and received a refund for, more than doubling your losses
Disputing a purchase they can’t return under your return policy guidelines (e.g. they used it already, it’s past the return window, or the item was sold as non-refundable)
Fighting First Party Fraud
Monitoring Base Metrics
Before you can do something about refund abuse, return fraud, or chargeback fraud, you must first explore whether or not such fraudulent activity is really impacting your business. Start by analyzing the following base metrics for a selected time period:
Share of Declines - Key predictors for both chargebacks and refunds can be the change in the key decline codes of suspected_fraud, transaction_not_allowed, do_not_honor, and blocked (by you or by your PSP)
Refund volume - Both the total count and value of refunded transactions
Refund rate - The number of refunds you’ve processed divided by the total number of processed transactions
Chargeback volume - Both the total count and value of disputed transactions
Chargeback rate - The number of chargebacks processed divided by the total number of transactions
Because first-party misuse has significantly increased in popularity among fraudsters starting in 2023, try to look back at least a year into your data. That way, you can establish expected ranges for each of these metrics while simultaneously monitoring against the baseline for any increases over time. It's also worth looking at both month-over-month and week-over-week changes across different segments in order to tease out the actions that make the most sense; for refunds, you might even look at day-over-day changes! Actions include things like adjusting your fraud rules, changing customer support operations, or even switching up processors.
Within our payments data aggregation and visualization platform, Pagos Insights, we have interactive dashboards specifically dedicated to Refunds and Chargebacks. In these dashboards, you can quickly narrow down the exact parameters associated with most refunds or chargebacks. For example, you may discover a large proportion of your chargeback volume comes from a single payment method or card type; in that case, you may stop accepting that payment method altogether to avoid this issue, configure the appropriate fraud rules to prevent known bad actors, or even enable 3D Secure as a way of adding friction where there is more risk.
Enriching Your Data
If segmenting your refund and chargeback data helps you identify the primary targets of fraudsters, then finding new ways to segment your data is always worth your time. One way to do this is with metadata. Metadata is a transaction-level label communicated via a merchant's processor at the time of the transaction. Businesses typically assign metadata for custom transaction categorization, for example by a specific product line, customer acquisition channel, or customer cohort. By assigning metadata to your transactions, you can identify the segments of your business most susceptible to first-party misuse.
A good example of this is using metadata to tag purchases of specific products; with these tags, you can analyze fraud trends at the product level. You may find that a specific popular product (e.g. a trendy insulated cup or style of sunglasses) has above average refund and chargeback rates when compared to the rest of your transaction volume. To combat this, you may impose stricter rules around refunds for these particular items or increase your communication with customers who purchase them, thereby arming your business against potential chargebacks.
The Pagos Enrichment API gives you the power to attach custom metadata to every transaction you import into Pagos Insights, making it easier than ever to segment your payments data by metadata tags and perform an analysis of this sort.
Incorporating Data Into Other Workflows
One of the greatest benefits of Pagos is our ability to ingest all your payments data across each processor or gateway you use and harmonize it into a single data feed. With Insights, you can view all that data in one place and dig in to find concerning spikes or trends in refund and chargeback volume. But that’s not the only powerful product we have to join in your battle against first-party misuse—we also have transaction-level data export capabilities.
By downloading your clean, Pagos-harmonized payments data, you can integrate it into your existing systems and workflows. For example, you can integrate this data into your call center traffic, essentially powering any call center data analysis with purchase information. You may then identify specific customers who request returns and chargebacks at an unusual rate and bar them from making any future purchases. This also gives you a way to identify the timing difference between when a transaction occurs and when the associated refund request comes into your call center; the longer this time period, the more likely the return is fraudulent.
You can even enrich your refund and chargeback data exports with data collected outside of the checkout process. If you ask your customers to provide a reason for their returns during the refund process, for example, you can tag associated refunds with these anecdotal return reasons. With all your data in one place, it’s easier for you to identify trends in shady behavior, such as the same customer requesting multiple returns for the same reason, or a large number of customers using the same excuses to abuse your refund or return policies.
Take Action Today!
Fighting first-party fraud comes down to establishing a feedback loop so you can make the necessary adjustments to your return processes, fraud rules, and chargeback operations. That feedback loop is created by:
Leveraging your data
Establishing baselines
Systematically breaking it down by key data segments
Comparing across different time frames
Integrating those data points into your workflows and configurations
Fraud is intimidating and fighting it can be hard, but making your data an asset in your fight can reduce your costs and losses. Pagos is here to help. Contact us to discuss how our solutions fit your business’ needs.