What Are False Declines and How to Avoid Them

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What Are False Declines and How to Avoid Them

Front-end fraud filters can protect merchants from true fraud disputes, but false declines can be a pain for both customers and retailers. Fraud filters help merchants automatically determine potential criminal activity before it occurs. But the downside of automation is some normal actions taken by a cardholder can cause false positives in fraud detection software.

Simple things like returning to school in professional years or taking an extended vacation can get a card falsely declined. Of course, running an ecommerce business heightens the red flags and risks because of the focus on card-not-present (CNP) fraud. While focusing on preventing true fraud is an important part of a fraud strategy, merchants also need to be aware of false declines and how they can affect their business. This post will discuss what false declines are, how they occur, and how to mitigate the associated risks.

What Are False Declines?

At its most basic, a false decline occurs when a payment card transaction is rejected for no reason. They're also known as false positives. This happens because of connection issues, technical glitches, or inaccurate fraud filters. For example, a customer currently traveling for business can get declined because their IP address is in a different area as their billing/shipping address. They are a legitimate customer, but because one thing is off, they get declined.

CNP transactions already create an elevated risk, so e-retailers take the hardest hits when a transaction is incorrectly labeled as fraudulent. This is because it's assumed that fraud is more likely to occur without a secure chipped card present. Unfortunately, what's meant to be an industry safeguard is hurting merchants.

Why and How Do False Positives Happen?

Financial institutions and merchants use front-end fraud protection, such as fraud filters, to help automatically assess if a transaction is fraudulent or not. Fraud filters are customizable and should be based on your industry, customer behavior, and other factors. There are many layers or filters that companies can add on top of each other and in a specific order. These filters can include:

A Daily Velocity Filter: This filter limits the number of transactions that can be processed in a day from the same IP address.

Shipping and Billing Mismatch Filter: This filter identifies a transaction that is submitted with different shipping and billing addresses.

High Ticket Purchase Filter: This filter notifies when a purchase is above a set threshold.

IP Address and Shipping Address Mismatch Filter: Which compares where the order is coming from compared to the shipping address provided.

Those are just examples of a few of the possible filters that can be put in place. A filter can trigger a couple of actions to happen, depending on how the merchant sets it up. A filter can instantly reject the purchase from happening, it can send it in to a manual review, it can accept the purchase, or it may just send it to the next layer of filters.

When set up correctly, fraud filters can be extremely helpful in preventing true fraud disputes while still letting legitimate customers in. When fraud filters are set up incorrectly is when false declines happen. For example, a merchant may have their fraud filters set up to be too strict. Instead of sending transactions to manual review, the filters decline any transaction that has anything off about it. Something as simple as a cardholder shipping the product to their work instead of a home can reject the purchase. Without well-thought-out and analyzed fraud filters, merchants are losing revenue and customers to false declines.

Money is the bottom line of any business, so it's essential to understand the direct costs inflicted on your business from false positives. Let's talk about how these problems affect your bottom line.

How Do False Positives Affect Merchants?

Just one false decline can cost a merchant revenue from a transaction and a loyal customer. Your company put all the time and resources into attracting a customer. The customer loved your product enough to commit to the purchase, and you turned them away. This all happens because your front-end fraud review system is not fine-tuned.

When a customer gets declined, they go elsewhere to purchase the product. Or if the customer decides to try again, there's a possibility the transaction will continue to be declined. These repeated false declines could place a hold on their card. They must then call the card issuer to resolve the issue. Meanwhile, the card issuer is paying for the call center to verify the customer. Not only was the cardholder not able to make the purchase they wanted to, but they also had to go through the hassle of calling their bank and resolving a larger problem.

In the end, false declines cost merchants revenue, customer satisfaction, and a negative image from the standpoint of the customer. So how can merchants lower their false declines?

How Can Merchants Lower False Declines?

Removing automated fraud filters isn't the answer. These are put into place to protect your business, and you would be exposing yourself to true fraud. What you need are smarter filters that are more capable of recognizing fraud and understanding the context.

To create better filters, merchants need to analyze data surrounding transactions and disputes. By finding similarities and correlations between transactions that end in true fraud disputes, merchants can create precise fraud filters. Merchants should be vigilant about updating and analyzing their filter's performance. For example, a merchant runs a massive promotional deal to attract new customers. If the marketing team and fraud team are not aligned, the increase in brand new cardholders can be flagged by the fraud filters, and the new customers will be turned away.

The more data analysis and context you can put into your filters, the more accurate they will be.

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