Gift card fraud: the quiet revenue leak in retail and ecommerce

Gift cards are built for convenience. They are easy to buy, easy to send and easy to redeem. For retailers, they bring revenue forward and can introduce new customers to the brand. For fraudsters, many of those same characteristics make them an attractive target.

Once a gift card number and PIN are compromised, the value can often be spent without the identity and payment checks involved in a standard ecommerce transaction. Digital gift cards make the process even faster, as they can be delivered and redeemed within minutes.

The resulting losses are not always recorded as gift card fraud. They may appear as customer service credits, disputed purchases, drained balances, promotional abuse or general programme costs. When those losses sit across different teams and reporting categories, the scale of the problem becomes difficult to see.

Understanding how gift card fraud develops across purchase, balance check and redemption is therefore essential to protecting the programme without adding unnecessary friction for legitimate customers.

Why gift cards create a different fraud problem

Several characteristics make gift card programmes particularly attractive to attackers.

Limited identity checks at redemption. A customer may go through payment and fraud controls when purchasing a gift card, but redemption can require little more than a valid card number and PIN. The controls protecting the original purchase do not necessarily follow the value through the rest of its lifecycle.

Fast access to value. Digital gift cards can be delivered and redeemed almost immediately. This leaves a much shorter window to identify suspicious activity before the value moves.

Accessible balance checks. Balance-check pages are useful for customers, but they can also become a testing ground for automated attacks when repeated queries can be made with limited scrutiny.

Easy transferability. Gift cards can move between people, accounts and channels with relatively little information attached to each transfer. This makes it harder to establish who is ultimately behind the activity.

These characteristics do not make fraud inevitable, but they do mean that controls designed around conventional ecommerce purchases may not be enough.

Five ways gift card programmes are exploited

1. Balance enumeration and draining

Balance enumeration starts with automated attempts to identify active gift cards.

Attackers generate combinations of gift card numbers and PINs and test them against balance-check endpoints. Most attempts fail. When a valid combination returns an available balance, the card can be drained before the legitimate recipient has a chance to use it.

Traditional IP-based rate limits provide only part of the picture. Automated requests can be distributed across residential proxy networks, devices and sessions, making individual sources appear relatively normal.

Session-level intelligence adds more context. Device and browser characteristics, network information, automation indicators and behavioural signals can help distinguish a genuine customer checking a balance from coordinated activity spread across thousands of requests.

The objective is to identify the operation behind the traffic, not simply count how many requests originate from one IP address.

2. Buying gift cards with stolen payment details

Gift cards can provide a fast route from compromised payment credentials to transferable value.

A stolen card is used to purchase a digital gift card, the gift card is spent or transferred, and the original payment may only be disputed later.

Digital gift cards can make this particularly challenging. There may be no physical delivery address to assess and no fulfilment period during which suspicious activity can be reviewed.

This makes the buyer's digital footprint more relevant.

Email intelligence can reveal signals such as disposable addresses, unusual account characteristics or a limited online presence. Phone intelligence can provide information about number validity, carrier, line type and connected services. IP and device intelligence can add network, location and session context.

Combined with transaction data, these signals can contribute to a more complete risk score even when the customer has no previous purchase history.

3. Physical gift card tampering

Some gift card attacks begin before the card is purchased.

Physical cards displayed in stores can be compromised by copying or exposing their codes and then returning them to the shelf. The attacker waits for a legitimate customer to activate the card and attempts to spend the balance shortly afterwards.

The customer only discovers the problem when the card is used or given to someone else.

This type of fraud is primarily a retail operations and packaging issue rather than a digital identity problem. Distinguishing it from online attacks is important because the controls required are different.

If every drained balance is classified in the same way, the actual source of losses becomes harder to identify.

4. Gift cards and store credit as part of organised fraud

Gift cards can also form one stage of a broader fraud operation.

Compromised accounts or stolen payment methods can be used to acquire stored value. That value can then move through gift cards, store credit, refunds or subsequent purchases before being converted into goods or transferred elsewhere.

Each individual action may look legitimate. The pattern becomes clearer when the accounts behind those actions are connected.

Accounts that appear unrelated may share device characteristics, network infrastructure, phone attributes, email patterns or other digital signals.

Linking those signals can reveal coordinated activity that would be difficult to identify by assessing every transaction or account independently.

5. Bulk and corporate gift card fraud

Corporate gift card programmes introduce another layer of risk.

Businesses often purchase gift cards in bulk for employee rewards, customer incentives and promotional campaigns. These transactions can involve substantially more value than an individual consumer purchase.

Compromised corporate accounts, impersonation and fraudulent business identities can therefore result in large amounts of digital value being issued in a single transaction.

Risk assessment in this channel should consider more than the payment itself. Email, domain, phone, IP and other digital signals can provide additional context about the person or organisation behind a high-value request before it is approved.

Where gift card fraud prevention should happen

Treat the balance-check endpoint like a login page

A balance-check endpoint may look like a simple customer service feature, but from a fraud perspective it confirms two valuable pieces of information: whether a credential is valid and whether value is available.

That makes the interaction itself worth protecting.

Device and browser characteristics, automation indicators, network information and behavioural patterns can help identify abnormal activity without relying exclusively on IP-based rate limits.

Failed and successful balance queries should also be analysed together. A high volume of failed attempts followed by a small number of successful queries may indicate a very different pattern from ordinary customers checking cards they already own.

Score the buyer, not only the transaction

Gift card purchases often involve customers with little or no previous transaction history. This is particularly common during peak periods, when first-time buyers account for a larger share of ecommerce traffic.

Lack of purchase history does not mean lack of information.

An email address, phone number, IP address and device all carry digital signals that can be assessed from the first interaction. These signals can help establish whether the identity has a consistent digital footprint, whether the connection shows suspicious characteristics and whether different attributes support or contradict each other.

That intelligence can feed into a risk score before a meaningful transaction history exists.

For digital gift cards, this is especially useful because traditional ecommerce signals such as shipping address, delivery history or previous orders may be unavailable.

Watch redemption as well as purchase

Many fraud controls concentrate on the point at which a gift card is purchased. Redemption can provide equally important information.

Patterns may only become visible once the value starts moving. Multiple cards redeemed within the same session, repeated balance queries before redemption, unusual geographic changes or several apparently unrelated cards converging on the same device can all indicate suspicious activity.

Connecting purchase, balance-check and redemption signals creates a more complete view of the gift card lifecycle than assessing each event separately.

Link accounts that claim no relationship

Organised gift card abuse depends on scale, and scale often requires multiple accounts.

Individually, those accounts may look legitimate. Together, they can reveal a much clearer pattern.

Shared device characteristics, network origins, phone attributes, email patterns and other identity signals can expose relationships between accounts that present themselves as unrelated customers.

This shifts the analysis from individual transactions to the wider network behind them.

Reducing fraud without adding friction to every purchase

Gift cards work because they are simple to buy and easy to use. Adding the same verification steps to every purchase can undermine that experience, particularly during high-volume periods when many legitimate customers are buying gift cards for the first time.

Stronger fraud prevention does not have to mean more friction for everyone.

Digital signals can help determine where additional scrutiny is justified. Low-risk interactions can continue without unnecessary interruption, while stronger controls can be reserved for sessions where the available evidence indicates higher risk.

For a first-time buyer, this can mean looking at the consistency of the email and phone identity, the characteristics of the IP connection, the device and browser being used, and the behaviour of the session itself.

The objective is selective friction: applying additional verification because the signals justify it, rather than simply because the customer is new.

Where Trustfull fits

Gift card fraud frequently occurs where traditional transaction history provides limited context: a first purchase, a newly created account, a balance check or a digital card that can be redeemed almost immediately.

Trustfull adds risk intelligence earlier in that journey.

The platform analyses digital signals associated with email addresses, phone numbers, IP addresses, devices, browsers and sessions in real time. These signals can be combined into risk scores and reason codes that help identify suspicious identities and behaviours without requiring additional input from the customer.

For gift card programmes, this intelligence can support several stages of the lifecycle.

At signup and purchase, digital footprint analysis provides context about first-time buyers when account and transaction history are unavailable.

At balance check and redemption, device, network, browser and session signals can help identify automated or suspicious activity around stored value.

Across multiple accounts, identity linkage can surface connections between customers that appear unrelated when analysed individually.

The result is a more selective approach to gift card fraud prevention. Risk scores and digital signals can help determine which interactions require additional scrutiny while allowing legitimate customers to continue with minimal friction.

Talk to our team about strengthening fraud prevention across the gift card lifecycle.

Frequently asked questions about gift card fraud

What is gift card fraud?

Gift card fraud refers to the theft, unauthorised use or fraudulent acquisition of gift card value. It can occur at different stages of the lifecycle, including purchase, balance checking, activation and redemption.

How do fraudsters steal gift card balances?

Fraudsters may obtain gift card credentials through automated enumeration, phishing, account compromise, physical card tampering or stolen payment information. Once a valid card number and PIN are identified, the available balance can often be redeemed quickly.

What is gift card balance enumeration?

Gift card balance enumeration is an automated technique in which attackers test large numbers of gift card numbers and PIN combinations against balance-check systems. Successful attempts can reveal active cards and their available value.

Why are digital gift cards attractive to fraudsters?

Digital gift cards provide fast access to transferable value and can often be delivered and redeemed within minutes. They may also involve fewer traditional ecommerce signals, such as shipping addresses or delivery history, making suspicious purchases harder to assess using transaction data alone.

How can retailers detect gift card fraud?

Retailers can combine transaction data with signals from email addresses, phone numbers, IP connections, devices, browsers and user behaviour. Analysing purchase, balance-check and redemption activity together can help identify suspicious patterns that may not be visible from individual transactions.

Can gift card fraud be prevented without adding friction for legitimate customers?

Yes. Risk-based controls can apply additional verification only when digital signals or behavioural patterns indicate elevated risk. Lower-risk interactions can continue normally, while suspicious sessions can be challenged, reviewed or blocked.

How does Trustfull help prevent gift card fraud?

Trustfull analyses digital signals linked to email addresses, phone numbers, IP addresses, devices, browsers and sessions. These signals can support risk assessment during signup, purchase, balance checking and redemption, and can also help identify connections between apparently unrelated accounts.