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Reducing False Declines, Part I: Happy Customers or Fraudsters?



The new normal enforced by COVID-19 has driven consumers to spend more time online to fulfill their everyday needs. Whether it is out of boredom to compensate for the stay-at-home mandates or out of necessity, consumers are relying heavily on purchases made online. This influx of activity has not gone unnoticed by fraudsters. It is the perfect breeding ground for those who are ready to take advantage of the situation.

It is to no one’s surprise that fraudsters are sophisticated. That is not good for consumers. This is even harder for merchants. Why? Merchants need to put measures in place to minimize fraud losses. It seems straight forward, but in doing so, they face the challenge of rising false declines that affect consumer’s experiences.

In this blog series, we will dive into what false declines are, how to identify them, and how to save revenue by providing a fluid experience for your valued customers. We will also provide resources for you and your team to assess your own fraud model and how to make it more efficient. But first, let’s clearly define what we mean by false declines.

What are False Declines?

False declines are valid transactions that are incorrectly rejected.

For a merchant, false declines can happen along many points of verification and authentication of the payment process. But for consumers, it is a point-in-time experience that may cause a customer to never return. 

For example, Tim, a trusted tech-savvy consumer, was eager to set up his entertainment system at his new home and was excited to find the perfect speakers that are within his budget. He chose accessories, added them to his cart, and entered his payment method for $350. But when he placed his order, it was declined.

ecommerce flow for approvals

Why? The answer is not certain, but one could speculate, given the data that usually comes with fraudulent transactions: his item had a high dollar value, he purchased an item that he does not use (or purchase) on a regular basis, he may have inputted an address that is unknown to the merchant, or he may be using an online retailer for the first time, making him a new (and unknown) customer.

This is just the beginning of a long list of reasons people are regularly rejected for good transactions. It could be that the merchant had placed very strict rules in assessing the riskiness of its customers. Given that the transaction raised a red flag, it was declined. As a result, the business lost the sale and an unhappy Tim who moved on and made the purchase with a competitor.

Taking the Business Elsewhere

$350 lost may not seem like that big of an issue. Unfortunately, it is much more than that. It took a lot more to get Tim to consider buying a product from the company, and there were hopes for Tim to become a loyal customer. There are a lot of variables that could be at play, but the two metrics that are representative are as below:

  • Customer Acquisition Cost (CAC) – Total cost of sales and marketing efforts that are needed to acquire a customer
  • Lifetime Value of a Customer (LTV) – Total worth to a business of a customer over the whole period of their relationship

Generally, at the point of which Tim becomes a customer with his first purchase, the merchant is still making up for the investment spent (CAC) in converting him from a prospect. But at that point, it also ties a projected revenue figure (LTV) for bringing him onboard as a customer.

Merchant potential revenue loss to fraud

Think Twice, Act Once

Merchants need to think about the customer’s transaction experiences, but the lessons learned do not stop there. Merchants also need to think about the impact on their bottom line with the cost associated with every customer churned.

For example, if an average customer will spend $300 over his lifetime, and it costs $100 to acquire that customer, then the average customer is worth $400. We know that 32% of falsely declined customers[1] will never return. 

If that same company does 1.5 million transactions per year, and their fraud models have a 5% false decline rate, the total cost to the business could be nearly $10 million.

Strike a Balance

How do you stop the revenue leakage of false declines? How do you keep fraudsters out without also making customers unhappy and losing revenue? There is a solution, but it is a delicate one. It is imperative to have a sound risk assessment solution to keep fraudsters out. However, it is also imperative to consider false declines, and take measures to minimize them.

Rather than strictly looking at the definitive good or bad, it would be more effective to look at the probability of good or bad, so to adjust to the right tolerance level in letting transactions through. It is true that opening up the door for more transactions to come through may also mean that some fraudulent transactions would slip through the cracks. However, the value of false declines on a good customer or two could be much more damaging than the loss from fraudsters. It would be remiss not to evaluate the impact and find the right balance.

To sum it up, fraud detection solutions need not only to prevent fraud, but also need to deliver a superior experience to the end-consumer. Not all rejected transactions are fraudulent. By acknowledging that some rejected transactions include falsely declined customers is the first step to addressing customer experiences. Then, putting in measures to adjust for those false declines would not only prevent those poor experiences but will also increase the bottom line.

For more information on false declines and how to identify and prevent them, watch our on-demand webinar: Capture Potential Revenue Loss: An Actionable Playbook for Reducing Customer Insult.

[1] Javelin Study 2018

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