Lassu recently released new research findings regarding employee points fraud within loyalty rewards programs. Between 1.7 and 8 percent of all points earned within rewards programs are not credited to accounts of the customers who made the purchase. About 600 retailers in North America with annual sales of more than $50 million have points-based rewards programs that are vulnerable to points-earning fraud, according to Lassu. The findings released today can be found at redamber.lassu.net in a new ebook titled “How to Identify and Prevent Insider Loyalty Fraud,” by research director, Jim Griffin.
According to Griffin, a program is vulnerable to insider fraud if the method used for earning points is not the same as the method used for payment. For example, if a customer can pay via credit card or debit card or cash and then credit a branded loyalty card to earn points, then that program is susceptible to points-earning fraud. The main source of this type of fraud is cashiers who earn points on a rewards account they control, based on purchases of random non-members. Other types of points-earning fraud occur within various customer service processes, especially points adjustment and points transfer, according to Griffin.
“A program might state that $1 spent will earn 10 points, and 2,000 points can be redeemed for $10 in purchases. This example equates to a 5 percent funding rate,” said Griffin. “In such a case, GAAP dictates that revenue must be reduced by 5 percent when that sale is booked, and a deferred liability must be carried on the books to represent the financial obligation for the points that were awarded on that transaction. This liability is a direct cost to the retailer of employee fraud within their points programs. What retailer would want to reduce their sales by 5 percent with no business benefit?”
Points-earning fraud cannot be detected using standard fraud-detection technology because standard methods seek to verify the “true account holder,” which is a logical approach for blocking a fraudulent purchase, but is not a logical or effective way to detect suspicious points earning.
In addition to significant financial losses from points-earning fraud, another big concern for loyalty programs is the effect of this type of abuse on their data models, notes Griffin. “If demographics of cashiers, or their family and friends become part of a data model for ‘high-value customers,’ and if shopping carts of random non-members are analyzed in order to describe the purchasing habits of the ‘high-value’ group, then marketing models will not function as intended,” notes Griffin. “In some cases, the output of the models ends up being almost meaningless, so the direct and indirect costs of cashier fraud within points programs is quite significant.”
