Learning From Failure: Harnessing Gateway Rejection Data to Increase Approvals
We never tire of saying it: Peacock by Pagos, our data aggregation and visualization tool, will provide you with payments data insight you never knew you needed until you have it. Once you’re up and running with Peacock and digging into your payments data, you’ll suddenly understand more about your customers, sales trends, and potential setup issues than you ever thought possible. In a previous blog post, we outlined an example of this insight by showing how Peacock can help you understand the value of your declined transaction data. Today, we’ll explore another important yet often overlooked data point: how many transactions are being blocked due to gateway rejections.
Gateway rejections differ from declined transactions because they represent transactions that were blocked even before reaching the issuers (where they would then be approved or declined based on things such as non-sufficient funds). Payment processors, acquirers and gateways don’t often account for gateway rejections when calculating approval rates, leaving you in the dark as to where a significant portion of your failed transactions may be occurring. To instead provide you with a more accurate representation of your declines, Peacock monitors your blocked and failed transactions, and includes them in all calculations of decline volume and rate. In this blog post, we’re going to break down the different ways you can leverage this important data to reduce and gain insight into these issues.
What Causes a Gateway Rejection?
Gateway rejections happen when a technology provider (e.g. gateway, acquirer, PSP) that sits between your business and the issuer rejects attempted transactions. With these types of transaction failures, it’s not always obvious why they’re happening Why would your payment partner or platform reject a transaction before processing it? What would cause them to deny the customer so early in the payment process?
Common reasons fall into a few main categories:
Rules set by your PSP - The attempted transaction fails to pass the rules your PSP set to protect your business from fraudulent activity
Rules you set - As a merchant, you likely set your own rules through your PSP intended to reduce the potential for fraud or carding attacks, such as requesting 3D Secure for all payments, allowing all payments from your business’s IP address, reviewing payments over a certain amount, or blocking payments from a specific country.
Unreachable card brands - Typically because of an internet connection issue, the PSP can’t reach the appropriate card brand and can’t continue on with the transaction
Why Should You Track Blocked Transactions?
When you monitor gateway rejections in Peacock, you can discover processing issues, track fraudulent activity, and identify if some transactions are being blocked by mistake. More importantly, depending on what you see in your gateway rejection data, you can even plan exactly which actions you’ll need to take in response.
In monitoring blocked transaction trends, you can also identify any places where your gateway is rejecting transactions it shouldn’t. For example, you might notice a subset of transactions is repeatedly blocked, while other similar transactions are not having any issue. This is unusual and unexpected behavior, and could be costing you more potential revenue than you realize—not to mention how frustrating it can be for your customers. Rather than accepting these transactions as a loss, it’s valuable to look into the variables and reasons that could be causing them. That's where Peacock comes in.
Let’s walk through some of the ways you can use Peacock to better understand your gateway declines and what actions you may want to take in response to your own data trends.
Using Peacock’s Dashboards to Understand Gateway Rejections
Under the Decline Code Transactions chart in the Decline Codes dashboard, you’ll find the Share of Transaction Count by Decline Code Category sub-chart. This chart breaks down all your declined transactions by the category of decline code. The category associated with gateway rejections is blocked_by_gateway_or_merchant_rule:
This chart lets you quickly determine how big of an issue gateway rejections are for your business—specifically, how much of your overall decline volume is due to gateway rejections. In the data for the chart pictured above, we see that of the 100,250 declined transactions in the chosen week, 12,030 were in the category of blocked_by_gateway_or_merchant_rule (12% of total declines). If this number concerns you, it’s time to dig in some more!
To learn more about what caused these gateway rejections, you’ll need to download the raw chart data. Click the three dots in the top-right corner, click Download, and then select Raw Data. This will give you a csv file of all the decline data from the chosen week that Peacock used to populate the Decline Code Transactions sub-charts. The response_category column identifies which decline code category each decline fits into; sort your data to only show declines in the blocked_by_gateway_or_merchant_rule category.
Using the pagos_code_short column, you can then identify the actual reason code behind each decline in that category. In our case, we see that all of the gateway declines last week all had the decline response code of processor_risk_rule, meaning the declines resulted from risk rules set by the processor to prevent fraud. Let’s dig a bit more into what you might learn from this discovery!
In most cases, when a processor rejects a transaction because their fraud rules deem it to be unsafe, this is a sign that your fraud rules are doing their job—assuming they’re set up correctly. That being said, it’s important to understand where and how fraud is happening with your business, though, as some of those fraudulent attempts could be preventable or fraud could be moving to new places. Some questions you might ask include:
Are fraudsters using a specific payment method or card type?
Is a particular merchant account receiving the bulk of fraud-related gateway rejections? If so, is the checkout page for that specific site laid out in a way that invites more fraud attempts?
Have fraudsters reverse engineered your rules and are not attempting new attacks from a different country, or on another merchant ID?
To help you answer these questions, you can use the Transaction Response Code filter on any dashboard in Peacock to filter only for transactions with the decline code of processor_risk_rule. This will help you identify trends in the transactions that were gateway rejected due to rules that you set up through your payment service provider. To demonstrate this, let’s continue with the example from the last section and filter the Card Brand Transactions chart to understand the breakdown of our 12,030 gateway rejections by card brand:
Keep in Mind:
While your fraud tools are often working as intended, there are also going to be false rejections—a problem every merchant runs into that can be tricky to solve when you can’t identify how many of your failed transactions are due to your processor risk rules. Luckily, Peacock provides you with insight into how many gateway rejections are due to the rules you have set, so you can monitor for unusually high numbers as an indication that it might be time to review your fraud rules you have set up in your payment service provider gateway.
A fraud rule that sounds useful might have a minor setting that prevents it from working as intended, and simply needs a little tweaking. For example, a common velocity fraud rule will block transactions if the total charges per IP address is greater than a certain number; while this is useful to prevent fraud such as carding attacks, there may be instances where a legitimate customer has a business model that creates legitimate transactions over the threshold you have set.
Ready To Make the Most of Gateway Rejection Data?
Your payment partners probably aren’t going to identify your gateway rejection trends or even include gateway rejections in their decline rate calculations. But without this data, you can’t conduct a comprehensive decline analysis in an attempt to improve approval rates. Peacock by Pagos ensures you never fly blind again; by including gateway rejections in all decline rate calculations and breaking out gateway rejection data into its own decline code category, Pagos gives you all the information you need to identify where gateway issues or too strict fraud rules might be cutting into your bottom line.
Want to go a step further and set up custom data triggers to alert you via email, slack notification, or webhook whenever your gateway rejections spike? Check out Canary by Pagos!