The Risks and Limitations of Chargeback Approve and Deny Lists

These lists could have some value, but a more thorough fraud prevention strategy is necessary to keep retailers safe.

Modern fraud is incredibly sophisticated, putting online retailers under a significant amount of pressure. These shops have to figure out how to keep chargebacks under control without rejecting legitimate orders, as false declines could have a negative impact on the customer experience and drive shoppers away.

The numbers show just how significant this problem is, too. The FTC reports that consumers lost $12.5 billion to fraud in 2024, which equals a 25% increase over the previous year. Fraud is changing faster than many traditional prevention tools can keep up with, putting retailers of all types at risk.

Many merchants still rely on deny lists and approve lists to help deal with fraud. These lists are often used to automatically block known fraudsters or fast-track trusted customers.

This approach does make some sense, as it's inexpensive and easy to implement. However, relying too heavily on static lists can introduce new risks like:

• False declines that reject real customers
• Fraud attempts that get past outdated methods
• Lost revenue from abandoned purchases
• Higher exposure to chargebacks and compliance issues

As a result, merchants have to ask an important question when creating a fraud-prevention strategy:

Are deny lists and approve lists actually helping prevent fraud, or are they creating new problems that put revenue and customer relationships at risk?

Here's a look at how deny and approve lists work, and whether they provide any benefit to retailers in 2026.

What Are Chargeback Deny Lists and Approve Lists?

Deny lists and approve lists are fraud prevention tools that have been around for decades. They help retailers make quick decisions about which transactions to approve and which to reject.

Both approaches help businesses manage risk, but they serve very different purposes.

What Is a Fraud Deny List?

A fraud deny list is a database of information that a company keeps to help identify suspicious or fraudulent activity. Transactions may be automatically declined or routed for additional review when a new order matches information on the organization's deny list.

Every company will include different information on its deny lists, but common examples include:

• Customer names
• Email addresses
• Shipping addresses
• Device IDs
• IP addresses
• Phone numbers
• Payment credentials that have previously been linked to fraud

The goal when collecting and storing this information is to prevent known bad actors from placing future orders.

For example, if someone makes a purchase with a stolen credit card and that later results in a chargeback, the merchant may add identifying information from that transaction to a deny list. Future orders containing the same information can then be blocked automatically, limiting the chance of fraud.

What Is a Fraud Approve List?

An approve list takes the opposite approach. It doesn't identify potentially risky activity; rather, it identifies customers and accounts that are trustworthy.

For instance, a retailer could approve loyal customers, returning buyers, previously approved payment methods or devices that have a history of legitimate purchases.

Transactions that match an approve list entry will move through the approval process very quickly. The goal here is to give trusted shoppers a smoother customer experience that keeps them coming back.

Why Merchants Use These Lists

It's easy to understand why retailers like deny lists and approve lists.

After all, these lists are relatively simple to implement and inexpensive to maintain. They can also help retailers make fast approvals because they identify familiar patterns and automate routine decisions.

The challenge is that fraud isn't the same as it was in previous generations. What worked well in a simpler ecommerce environment doesn't always work well today.

Why Might Deny Lists Create More Problems Than They Solve?

Retailers can use deny lists to identify repeat offenders. However, their value is limited because they aren't a proactive solution.

Modern fraudsters understand this weakness and constantly adapt their tactics to avoid detection. In simple terms, they won't use the same information twice.

Fraudsters Constantly Change Identities

Modern fraud is well-organized and highly adaptable. A fraudster who is blocked today may return tomorrow using:

• A different credit card
• A new email address
• A VPN that conceals their location
• An entirely different device

Some criminals go even further by creating synthetic identities that combine real and fabricated information, making them difficult to connect with previous fraudulent activity.

As a result, deny lists are inherently reactive. They show retailers where fraud occurred yesterday, but they don't provide much value if the fraudster is using new information.

Deny Lists Increase False Positives

Another challenge is that deny lists matches don't always mean there is fraud. The reason is that legitimate customers could have the same data points that appear on a deny list.

For instance:

• Family members often use the same devices and addresses.
• Employees may share corporate networks.
• Phone numbers are recycled.
• IP addresses can be used by multiple individuals over time.

Legitimate transactions can be flagged or declined even though the customer has done nothing wrong in these situations.

These scenarios could be rare, but they still pop up from time to time, costing the company revenue in the process.

Deny Lists Can Reduce Revenue

Every false decline comes with a cost.

A rejected transaction will cost the company revenue, but the impact doesn't end there. Customers who experience an unjustified decline are more likely to abandon their cart or lose trust in the brand altogether, reducing their lifetime value.

In fact, 42% of shoppers say they’ll never shop at a brand again after a false decline.

The reality is that blocking a legitimate customer can sometimes be more expensive than stopping a single fraudulent transaction. Retailers will have to find a balance between fraud prevention and customer experience, which will require more than a static list of known risks.

What Risks Come With Relying on Approve Lists?

Approve lists are supposed to make life easier for merchants and customers because they automatically approve trusted buyers. The theory is that businesses can make customers happier by creating a faster checkout, bringing these customers back for more in the future.

The problem is that trust is not always permanent.

Good Customers Can Become Risky Customers

A customer who has been legitimate for years can suddenly become a fraud risk if their account is compromised.

Account takeover attacks or stolen login credentials can turn a trusted account into a fraudulent one, all without the retailer knowing about it. The customer has not changed in these situations, but the security of the account has.

If the account remains on an approve list, fraudulent transactions may be approved with little resistance.

Approve Lists Create Blind Spots

Approve lists can also create a false sense of security.

When transactions receive automatic approval based on past behavior, they may not undergo the same level of scrutiny as other purchases. Important warning signs can be missed simply because the customer has a history of legitimate activity.

Fraudsters understand this dynamic and actively look for opportunities to exploit it by gaining access to long-term accounts. They may use credential stuffing attacks or manipulate customers through phishing and social engineering tactics to get this access. From there, they inherit the trust that has already been established between the customer and the retailer.

That trust makes an approve list account especially attractive targets for criminals.

How Do Deny Lists and Approve Lists Affect Chargeback Rates?

It might look like deny lists and approve lists are solid chargeback prevention tools. After all, they help retailers decide which transactions to approve and which to reject, and they work very quickly.

The reality is more complicated, though, because of the weaknesses of this system. These approaches can contribute to chargeback problems in different ways when used as the main decision-making tool for online retailers.

Deny List Problems

Deny lists can block risk, but they also create issues for legitimate customers. These customers will end up frustrated if they're incorrectly declined because of a shared IP address or a mistaken match, and that could influence the trust they have in a business.

False declines can damage customer relationships and create the kind of negative experiences that increase dispute and chargeback risk, which is another issue retailers will have to consider.

Approve List Problems

Approve lists present the opposite challenge because transactions that receive less scrutiny could allow fraudulent transactions to slip through the cracks. A criminal who gains access to a legitimate customer's account may be able to place orders that appear completely trustworthy, which can result in unauthorized purchases.

From there, chargebacks are likely to follow.

New Compliance Pressures

The stakes are even higher today because card networks are paying closer attention to merchant fraud and dispute performance.

In April 2025, Visa consolidated several fraud-monitoring initiatives into the Visa Acquirer Monitoring Program (VAMP). The program creates a more unified framework for tracking fraud and dispute activity.

Visa further tightened merchant thresholds in April 2026, increasing pressure on businesses to keep fraud and chargeback rates low.

Retailers that go beyond these thresholds may face increased monitoring or financial penalties, creating even more problems for the business moving forward.

Poor fraud decisions affect more than individual transactions, as they have massive financial and operational consequences for the business as a whole.

Modern Fraud Prevention Requires More Than Deny Lists and Approve Lists

Deny lists and approve lists have value as fraud signals, but they aren't good enough as standalone fraud prevention strategies.

Deny lists can help identify known fraudsters, and approve lists can improve the customer experience, but they're highly limited solutions that don't do enough to limit fraud.

ClearSale provides a complete solution that uses advanced analytics, machine learning, behavioral signals, and human expertise to assess the overall trustworthiness of each transaction. We don't focus on a single data point; instead, we examine the broader context surrounding every purchase. The result is fewer false declines and less overall fraud.

Contact ClearSale today to request a demo and learn how a modern fraud prevention strategy can protect revenue without relying on outdated lists.

FAQ: Chargeback Deny Lists and Appove Lists

What Are Fraud Deny Lists and Approve Lists?

A fraud deny list is a database with information about past fraudulent activity. This data could include email addresses, shipping addresses, devices, or payment credentials. Approve lists work in the opposite way by identifying customers or payment methods that are trustworthy and may receive faster approval.

Why Can Deny Lists Sometimes Cause More Harm Than Good?

Deny lists identify fraud only after the fact. They can also produce false positives when legitimate customers share data points with previously flagged transactions.

What Are the Biggest Risks of Using Approve Lists?

Approve lists are risky because trusted accounts can be compromised. Account takeover attacks and other forms of fraud can allow criminals to exploit an account on an approve list, creating blind spots that may allow fraudulent transactions to bypass normal scrutiny.

How Can Deny Lists and Approve Lists Impact Chargeback Rates?

Both tools can contribute to chargeback issues when used as a company's main fraud controls. Overly aggressive deny lists may create customer dissatisfaction and false declines, while overly permissive approve lists can allow unauthorized transactions that later result in fraud-related chargebacks.

What Does Modern Fraud Prevention Involve?

Modern fraud prevention uses a combination of advanced analytics, machine learning, behavioral data and human expertise. It doesn't rely on static rules or lists, but it instead evaluates the full context of a transaction to make more accurate risk decisions.