Protect Yourself from Chargebacks with Fraud Filters
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Every e-commerce merchant has to deal with chargebacks, and their costs and other consequences can put a business at risk if left unchecked. While illegitimate chargebacks can be fought and reversed, those that result from true fraud can't be. That means it's especially important to prevent true fraud chargebacks.
The best way for merchants to protect their bottom line is through the use of fraud filters. These filters identify various indicators of fraud and screen out transactions that are likely illegitimate. However, there are a wide variety of different fraud filters a merchant might use, from the simple to the incredibly complex. What do merchants need to know about the different types of fraud filters and how can they use them to their advantage?
Online retail fraud keeps growing more and more prevalent, costing merchants hundreds of millions of dollars every year.
The COVID-19 pandemic pushed consumers toward e-commerce shopping in even greater numbers, and all that increased activity has caused a commensurate rise in fraud attempts.
When a cardholder finds out that their card has been stolen and used to make unauthorized purchases, their best recourse is to report the fraud to their bank and receive a chargeback.
While chargebacks may be a satisfactory remedy for cardholders, they push the financial liability for fraud onto merchants. To make matters worse, an excessive rate of fraud and chargebacks can get merchants forcibly enrolled in costly mitigation programs or even cause them to lose their merchant accounts.
Therefore, it’s essential for every merchant to use the best tools and resources at their disposal to preemptively stop fraud.
What Are Fraud Filters?
There are several common types of fraud filters used by merchants. Fraud prevention software often includes support for multiple methods of fraud detection, which can be used simultaneously to improve accuracy and reliability. Here are a few of the most common forms of fraud filters:
These filters make sure that the card’s billing address and CVV number are correct before processing the transaction. They can also flag orders where the billing address and the shipping address don’t match.
Many fraudsters test out stolen payment card credentials by making small transactions just to see if the card still works. Velocity filters look for small, frequent transaction attempts and will flag the associated accounts or IP addresses.
Purchase Amount Thresholds
Once a fraudster is sure a card works, they'll be trying to get as much money out of it as possible before the fraud is detected. Some merchants may choose to automatically flag purchases exceeding a certain total price for manual review, which can help prevent the largest potential losses.
Customer Location Filtering
Merchants who know that certain IP addresses or locations are frequent sources of fraud can set up filters that will automatically block or flag transactions originating from these sources.
For example, if there's a pattern of fraudulent orders originating from a particular country in which the merchant doesn't do very much business, they may choose to simply block orders from that country entirely.
The most sophisticated fraud filters analyze multiple data points and assign a score that reflects how likely it is that the transaction is fraudulent. Transactions with a high score can then be filtered out for further review. Many of these filters utilize machine learning and artificial intelligence to improve the accuracy of their scoring algorithms.
How Effective Are Fraud Filters?
Being falsely flagged as a fraudster can be an extremely frustrating experience for a customer, and when you erroneously reject a legitimate order, there’s a chance that the customer will leave and never come back.
While methods like velocity checking and CVV matching may have low false positive rates, these types of filters tend to work only on unskilled, low-effort fraudsters. Experienced fraudsters will often have a complete set of payment credentials and will have done their card testing elsewhere before attempting a large purchase.
These fraudsters are very good at making themselves look like real customers, and that means that setting up fraud filters that can catch them greatly increases your risk of blocking and alienating your actual customers.
What’s the Best Way to Use Fraud Filters?
By analyzing the data from transactions involved in fraud disputes, you can identify the characteristics of the fraud that is actually affecting you.
For example, merchants who sell digital goods or gifts for third parties may find that using AVS filtering doesn’t catch many fraudsters at all, and inconveniences a lot of valid customers.
By using data analytics to profile your fraudsters, you can configure and train your filters with a high degree of specificity.
Also, remember that a flagged transaction doesn’t necessarily need to be rejected—you can subject it to manual review or even contact the customer directly to verify whether or not it’s legitimate.
Fraud filters can be a very effective way to draw your attention to potentially fraudulent transactions before you process them, but you have to be careful about relying on them too heavily. Even the most finely-tuned fraud filters can generate false positives and false negatives, both of which can have adverse consequences for your business.
The best way to use fraud filters is to make them part of a comprehensive strategy for preventing fraud and chargebacks that utilizes various methodologies tailored to your specific circumstances.
Online fraud comes in many forms, and not every merchant will have the same experience with it. Analyzing your fraud data and choosing the right tools for the job will give you the best outcomes for blocking fraud and the chargebacks that follow it.