First-Party Fraud in Ecommerce: How to Identify, Prevent, and Reduce Fraud Risks

Fraud losses do not always involve stolen credit cards. In some cases, the customer is a legitimate account holder using a valid payment method with no history of suspicious activity. Mastercard estimated that first-party fraud accounted for about one in five disputed payments in 2025.

First-party fraud (FPF) is different from fraud involving stolen payment credentials because the person behind the transaction is the legitimate account holder. The customer may dispute a legitimate charge, falsely claim goods were never delivered, or abuse a return policy. The key difference is that the transaction looks legitimate at checkout, so the fraud is not flagged until after the sale.

This guide covers what first-party fraud is, how it differs from third-party fraud, warning signs, detection methods, and where identity verification fits in.

What Is First-Party Fraud in Ecommerce?

First-party fraud is sometimes referred to as “friendly fraud,” particularly when a legitimate cardholder disputes a transaction they actually authorized. However, the terms aren’t always interchangeable.

In any case, it reflects that the source of the fraud is the account holder rather than an outside attacker. Simply put, the customer intentionally provides false information to the merchant or bank to retain goods, obtain a refund, or avoid paying for a legitimate transaction.

Common examples of first-party fraud include:

• The customer claims they have not received the ordered goods, despite evidence of delivery.
• A customer buys an item, uses it, and then returns it for a full refund (“wardrobing”).
• The customer disputes the purchase and opts for chargebacks rather than contacting the merchant for a refund.
• A customer opens multiple accounts at once, all connected to a single internet protocol (IP) address, to use promo codes multiple times.

First-Party Fraud vs. Third-Party Fraud

These are often grouped by merchants under the generic label of “ecommerce fraud,” but they differ in nature and behavior, and hence in the protection against them.

Let’s take a closer look:

How Does First-Party Fraud Work?

The mechanics follow the same five-step pattern almost every time:

1. Legit Account Creation: A user joins with valid information; no red flags are visible on the account, as it is not fake.

2. Normal Purchase: They place an order using their own credit card, with no stolen information and no suspicious activity during checkout.

3. Abuse Trigger: After the goods arrive, they file a false non-delivery claim, dispute the charge as unauthorized, or return the item outside policy.

4. The Merchant Bears the Loss: The store absorbs the cost of the product, the chargeback fee, and often the payment processor’s fee.

5. Pattern Repeats: With no way to flag the account, the same customer runs the same play on the next order.

Types of First-Party Fraud

First-party fraud can appear in several forms, such as:

• Chargeback Abuse (Friendly Fraud): The practice of consumers making false claims about unauthorized transactions to obtain a refund, even after receiving goods or services, results in losses for businesses.
• Return Fraud: Practices such as “wardrobing,” where customers buy items, use them, and then return them for a full refund, are becoming more common. This behavior can be especially prevalent during special events, such as weddings, where individuals want to look their best without incurring the full cost of clothing.
• Gift Card Fraud: Scammers often use stolen credit cards to purchase gift cards, which are then easily resold or used for personal gain. Additionally, they may falsely claim that they never received the gift cards they bought, attempting to get a refund or replacement. This type of fraud can be particularly difficult to track and resolve, causing significant financial losses.



• Lost in Transit Fraud: This type of fraud occurs when customers claim they never received their order, even though tracking information shows it was delivered. However, the thing is that they have received the product but are attempting to get a refund or replacement by falsely reporting it as lost.
• Item Not as Ordered Fraud:This type of fraud occurs when customers falsely claim they never received their order, even though tracking information confirms delivery. In some cases, fraudsters may also use tactics like pay for shipping scams to deceive customers and create disputes, allowing them to obtain refunds, replacements, or other financial benefits by making false claims.
• Ghost Funding: Fake accounts are created to manipulate payment systems or exploit promotions. These accounts can make unauthorized transactions and misuse discounts meant for real users.

Why Solving First-Party Fraud Is So Difficult

First-party fraud detection and prevention present special challenges because they operate in the gray zone between accidental error and fraud. Unlike other forms of fraud, it poses three main challenges that make it difficult to solve.

• Valid Checkouts: Traditional fraud detection tools often focus on signals such as stolen payment credentials, incorrect CVVs, or suspicious identities; however, in this case, all user information is legitimate. Since standard risk engines may see few obvious warning signs at checkout, the transaction sails right through approval.
• Delayed Intent: The buyer acts like a normal, genuine customer at the time of purchase and only turns dishonest later during the fulfillment, delivery, or return stages.
• Issuer Bias: Consumer protection rules often heavily favor cardholders, forcing banks to issue provisional credits before an investigation even begins.

How Weak Verification in Ecommerce Enables FPF

Weak verification systems in ecommerce open the door for fraudulent activities such as Fraud-as-a-Service attacks targeting retailers that exploit weak identity checks and enable organized fraud operations:

• Insufficient identity verification during account creation allows for fake accounts.
• Lack of strong transaction monitoring allows suspicious activities to be overlooked.
• Weak return policies allow fraudsters to easily commit return fraud.
• Inadequate delivery confirmation processes lead to lost-in-transit fraud claims.

The need for stronger customer verification methods is urgent, and digital age verification offers a promising solution.

Warning Signs and Behavioral Patterns of First-Party Fraud

First-party fraud is not theft. When the purchaser uses their own account and card, the purchase can be processed smoothly.

This fraud only surfaces once the delivery or billing process is over. Early identification of these warning signals is the only way to differentiate between a dissatisfied consumer and a fraudster.

Common behavioral indicators include:

• High Rate of Return Purchases: Customers who always purchase several products at once but end up returning almost all of them, generating shipping and processing expenses while not retaining any stock.
• Repeated Complaints About Non-delivery for Delivered Orders: Clients who file repeated non-delivery claims even when delivery has been confirmed by the carrier and made to the proper destination.
• Several Accounts Associated with the Same Address, Device, or Payment Details: Users who open new accounts with different names just to use special sign-up promotions or discounts.
• Quick Chargebacks after Delivery of Goods: Now, customers can skip the merchant’s customer service and open a chargeback case directly with their bank.
• Promo Code Usage Patterns: Accounts that become active only when a new discount code becomes available, place one discounted purchase, and then disappear.

How to Detect First-Party Fraud in Ecommerce

Normal transaction rules cannot detect first-party fraud, as there is nothing abnormal in the transaction from a records point of view. Detecting this kind of fraud requires looking beyond the transaction and understanding the customer behavior patterns.

Here is how modern e-commerce companies detect the first-party abuse:

Behavioral Analytics and Customer Risk Profiling

Rather than focusing on individual transaction history, merchants monitor users’ past behavior. The use of risk profiling helps the merchant identify high-risk users based on parameters such as purchase rate, deviation in order value, and return patterns.

Device Fingerprinting and Account Linking

Even when the fraudster gets a new identity or a different credit card, his digital footprint remains the same. The device fingerprinting technology associates browser parameters, hardware configuration, and IP data with the device, revealing the network of secondary accounts used for promotion schemes or ban evasion.

Delivery/Tracking Evidence Collection

To protect against false claims of non-delivery, delivery telemetry is crucial for the retailer. Gathering information through carrier scans, geolocation of the delivery picture, and direct signatures establishes an irrefutable evidentiary chain, making any false chargebacks invalid.

AI-Powered Models for Repeat Fraudster Detection

Fraudsters operating as first parties are unlikely to do it once; they will move from one store to another using similar methods. Machine learning algorithms search for the signature of fraud across transaction datasets by looking for similarities in dispute patterns and returns.

Cross-Merchant Fraud Intelligence Sharing

Since professionals in first-party fraud exist in several storefronts, the isolated merchant will be at a disadvantage. Intelligence communities can help the retailer combine anonymous risk indicators, and the moment you receive a customer known to be a fraudster elsewhere, your system will receive a signal.

What Rights Do Retailers Have When Customers Dispute a Transaction?

Consumers are protected in some unauthorized transactions, yet retailers are not obligated to accept all disputes. Merchants can contest some claims using the appropriate procedure for handling such disputes, together with supporting evidence.

Retailers Can Challenge Certain Disputed Transactions

Regulation E gives consumers specific error-resolution protections for qualifying electronic fund transfers, including reported unauthorized transactions.

When a consumer reports an error, the financial institution is generally required to investigate the claim, review the transaction details, and determine whether the charge was authorized. If the investigation cannot be completed within the required timeframe, the institution may also be required to provide provisional credit while the case is being reviewed.

Visa CE 3.0 Gives Merchants a Way to Fight Certain Fraud Claims

Visa CE 3.0 allows merchants to provide compelling evidence for Visa card-not-present fraud disputes that meet Dispute Condition 10.4. Merchants can rely on valid evidence from past transactions to establish a link between the disputed transaction and the customer’s previous activities.

Such evidence includes account information, IP addresses, device information, delivery information, and transaction history, among others, per Visa requirements.

Historical Evidence Can Help Expose Friendly Fraud

First-party fraud can easily slip through checkout because the transaction appears legitimate, with the customer using their own account and payment method before disputing the purchase later.

Retailers can counter this by using historical transaction and customer data to link the disputed purchase to prior legitimate activity. Identity verification can strengthen this evidence trail by establishing a verified link between the customer and their account.

How Does Identity Verification Help Reduce First-Party Fraud Risk?

Identity verification does not prevent legitimate customers from creating delivery disputes, which is a claims issue, but it helps prevent entry points for first-party fraud and provides documentation when disputes do occur.

Verifying Real Customers

There’s no customer waiting at your counter for payment, so that is precisely how the fraud works. Liveness detection helps fill that gap by verifying the customer’s live identity rather than a photo, a mask, or a deepfake.

If fraud rings use AI-generated deepfakes to bypass the selfie test, 3D liveness detection helps determine whether the face is real or synthetic. In FTx Identity, liveness detection is integrated into the account-matching process, in which the selfie is compared with the government ID image to verify the account holder’s identity.

Reducing Chargeback Abuse and Strengthening Disputes

A verified ID provides evidence linking the account to the person who completed the verification. This can be especially helpful when a consumer disputes a transaction or when billing and delivery information don’t match. FTx Identity stores documentation of completed identity verification behind the scenes, giving merchants supporting evidence to reference during the dispute process.

Cutting Down on LIT and Return Fraud

Lost in transit (LIT) fraud and return fraud both share the same weakness: a merchant who cannot be sure whether this is the first or the fifth time the customer has reported that the goods have not been delivered.

FTx Identity verifies the account holder’s age and identity by checking documents against government-issued IDs. This helps make the pattern visible and can discourage fraudulent LIT or return claims, since the account cannot simply be closed and reopened.

Cutting Down on Guest Checkout Abuse

Guest checkout is convenient, but it doesn’t have any account history to compare against either. It’s easy to avoid return restrictions simply by never signing up for an account, so you won’t have an account that could be flagged. Asking customers to register in a verified way is a prerequisite for those measures to be effective, rather than a fraud-detection measure itself.

Conclusion

Fighting first-party fraud is essential for protecting the financial health and reputation of ecommerce businesses. Using strong verification methods, such as digital age verification solutions like FTx Identity, businesses can greatly lower the risk of fraud, improve their dispute processes, and protect their revenue.