Loyalty firm Lassu Inc. this week released new research findings regarding employee points fraud within loyalty rewards programmes. According to a new e-book from Lassu, about 600 retailers in North America with annual sales of more than $50 million have points-based rewards programmes that are vulnerable to points-earning fraud, with between 1.7% and 8% of all points earned within rewards programmes not credited to accounts of the customers who made the purchase.
The fraud findings can be found in a new Lassu ebook titled �How to Identify and Prevent Insider Loyalty Fraud,� by research director Jim Griffin.
According to Griffin, a programme 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 programme 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. Money quote from Griffin:
�A programme 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% funding rate. In such a case, [Generally Accepted Accounting Principles] (GAAP) dictate that revenue must be reduced by 5% 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 programmes. What retailer would want to reduce their sales by 5% with no business benefit?�
Points-earning fraud cannot be detected using standard fraud-detection technology because standard methods seek to verify the �true accountholder,� 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 programmes 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 analysed 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 programmes is quite significant.�