Loyalty Fraud: How to Spot it and Stop it

What Is Loyalty Fraud?

Loyalty fraud is the act of cheating in a loyalty program to unfairly earn points or benefits. There are a few different categories of loyalty fraud that might occur at your brand, based on who is committing the fraud and how they are achieving it. You can see a breakdown of the different types of loyalty fraud below.

Account Takeover (ATO) Fraud

ATO fraud happens when hackers bypass security measures or steal login information to takeover loyalty accounts and claim them for their own. They cash in on your customers’ hard-earned loyalty points and use their accounts to earn unauthorized points as well.

Employee Fraud

Loyalty fraud can also come from within your company. An untrustworthy employee with access to the backend of your loyalty software could use their privileges to award themself unearned points, or aid others in stealing points and benefits. Employees might also commit loyalty fraud by claiming customers’ unclaimed loyalty points for themselves.

Customer Fraud

Customers obtain unearned points or benefits when they create multiple accounts for signup benefits, claim points earned by friends or family members, use points from other customers’ receipts, or use their accounts to earn rewards like products and gift cards that they turn around and sell for cash.

Why Is Loyalty Fraud on the Rise?

Between ATO fraud, customer fraud, and employee fraud, there is no shortage of ways that fraudsters might be cheating your loyalty program. It’s estimated that $3.1 billion worth of loyalty points are fraudulently redeemed, according to data from iApp. What’s worse is that loyalty fraud is on the rise. In 2019, Forter Fraud Index reported an 89% increase in loyalty program fraud year-over-year. We can speculate some of the reasons why:

  • Loyalty accounts are not secure enough.
  • Rewards are increasingly easy to sell on the dark web.
  • Hackers can find other personal information within loyalty accounts.
  • Businesses don’t expect loyalty fraud.
  • Fraudsters can easily claim unclaimed rewards for themselves.

Considering the recent spiking rate of loyalty fraud, there’s a good chance that your loyalty program has been hit for one or more of these reasons. Regardless of fraudsters’ motivation to cheat, integrating a machine learning algorithm into your loyalty software can offer a solution to loyalty fraud.

A Clutch-Powered Solution to Loyalty Fraud

Ensuring that your loyalty program is utilized as it should be — by loyal customers — is easier said than done. Fraudsters are always waiting in the wings, ready to seize any opportunity to exploit loopholes in your system. If customers or employees abuse your loyalty policy with fake coupon codes, multiple accounts, or any other unfair strategy, Clutch’s Suspicious Accounts tool is an efficient and effective way to stop them.

Because your loyalty program is unlike any other, the Suspicious Accounts tool is specifically tailored for your company’s use. It examines accounts and transactions in your loyalty program using a feedback loop from your brand to identify irregularities. The algorithm is able to identify outlier accounts based on what a typical account looks like for your brand.

Want to see how a Clutch-powered answer to loyalty fraud might work for your brand? Well, no two loyalty programs are exactly alike, but one of these real-life examples might give you an idea of how the Suspicious Accounts tool could work for you.

Example 1 – Coffee Store Chain

In this coffee brand’s loyalty program, customers can scan receipts for loyalty points. When some customers discard receipts without scanning them, employees and other customers may fraudulently claim the points for their own accounts.  

Oftentimes, fraudulent points are redeemed at an abnormal speed or frequency compared to legitimate points. In this case, Clutch trains the algorithm to look for high-frequency and high-speed redemptions, e.g. 10 receipts in two minutes, or 15 receipts in one day.

Clutch surfaces these accounts, then use the feedback loop from the brand to train the algorithm to understand what is fraudulent and what is not. The outlying accounts are sorted into a segment and the brand can take action per their discretion. Over time, we train the algorithm to recognize lists of accounts as fraudulent and the Suspicious Accounts tool becomes more and more accurate.

Example 2 – National Pet Food Brand

This pet food brand recently launched its loyalty program. The brand’s customers can use a new app to help track milestones related to their pets, like walks, vet visits, and weight loss. They can also scan QR codes from the inside of pet food bags.

Some customers create fake pet profiles (the app allows up to six pets) and max out activities to earn fraudulent points. There is also a risk of some customers scanning extra QR codes from family and friends, or even figuring out numerical patterns to create additional fake codes.

Since this loyalty program is relatively new, the brand doesn’t have a dedicated fraud detection team to monitor it yet. They don’t know much about how legitimate users interact with the program either. Clutch helps by looking at high point earners, high numbers and frequencies of QR code scans, and accounts with six pets and high activity rates. In addition to finding fraudulent accounts, the brand also learns more about customer behaviors from Clutch-powered machine learning models.


Loyalty fraud poses a major threat to brands with loyalty programs, and as the rate of fraud rises, companies can be discouraged from continuing or even creating loyalty programs in the first place. However, machine learning is here to help brands overcome loyalty fraud, and learn more about how honest customers use their loyalty programs at the same time. Even if you weren’t aware of loyalty fraud at your brand, with an automated fraud-detection tool, you can reduce losses due to loyalty fraud and save on staffing costs when you utilize a Clutch-powered solution.

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