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Your Complete Guide to eCommerce False Declines & How to Recover Them with AI

By Matiss Maliks

Every day, legitimate customers reach checkout and attempt to complete a purchase. They have available funds. Their card is active. They want to buy.

Yet the transaction gets declined.

The customer leaves. The sale disappears.

While most merchants spend thousands of dollars on attracting new customers, a big part of your revenue is hidden in false declines that can and should be recovered.

In this article, we’ll talk about what false declines are in eCommerce, why they occur, and how your declined payments can be be recovered with AI.

What’s a False Decline?

To get a better understanding of a false decline, let’s take a look at a declined payment first.

A declined payment (or a declined transaction) is a legitimate decline, where a legitimate transaction fails for a reason. Examples include:

  • Insufficient funds

  • Lost or stolen cards

  • Expired cards

  • Invalid card details

In these situations, the transaction genuinely cannot be completed.

A false decline occurs when a legitimate transaction is rejected despite the customer being fully capable of completing the purchase.

The customer:

  • Has sufficient funds

  • Owns the card

  • Entered correct information

  • Intends to purchase

Yet the payment still fails.

Behind the scenes, the process typically looks like this:

Traditional payment stacks stop here.

Here's the interesting thing: if everything is okay with your customer and their money, why do false declines happen?

Why False Declines Are Exploding in eCommerce

The reasons why false declines are killing your revenue might be different. We will focus on the most common and most painful ones.

First of all, with the development of digital payments, security in fintech and eCommerce has become more aggressive. Today’s online shoppers buy from multiple countries, use mobile wallets, subscribe to recurring products, and more. Banks are under pressure to reduce fraud at all costs, and in many cases, any unusual activity from legitimate customers looks suspicious to the systems.

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