In today’s retail industry, the monitoring and analysis of POS data by loss prevention specialists is a primary method of fraud detection. An exception-based reporting system like Oracle Retail XBRi Loss Prevention analyzes POS data continuously to look for exceptions or anomalies, finding outliers in regard to refunds, discounts, line or post voids, or other activities that might indicate problem behavior on the part of employees or customers.
What’s less well known is that these same capabilities can also be used to identify and analyze data exceptions and detect fraud in other parts of the business. As more and more retailers explore the possibilities of using XBRi business intelligence capabilities for POS analytics and beyond, they are finding that it can be used to understand operational issues as well as to identify fraud.
For example, one of our customers, an internationally known Fortune 500 manufacturer and retailer, recently tasked their risk management group to review travel expense data, which was being entered into the finance and accounting system through their travel and expense system. The risk management team, not having its own capability to make the desired analysis, went out into the market, identified a software solution—at a significant price—and asked the loss prevention analytic team for their opinion.
“The risk management solution was not a bad tool,” responded the LP team, “but the capability isn’t as robust as what we’re currently using XBRi to do.” Eager to avoid an unnecessary purchase and implementation cycle, the risk management team linked XBRi to the data coming in through their travel and expense system. They immediately found some high-risk situations, one of them involving what is often thought of as a T&E cost control: assigning traveling staff a maximum per diem limit on meals.
XBRi surfaced suspicious recurring per diem expenses every day at the same location—no matter where the employee actually was. Upon investigation, the charges were not from a restaurant but rather a tattoo shop. The employee was using company funds and had made arrangements with the tattoo shop to charge his full per diem allotment every day.
Another great example was anomalies uncovered by XBRi having to do with mileage expenses for a personal vehicle. In one case, a district manager who was responsible for over a dozen stores some of them only a ten mile drive, some much further. According to records, the employee was traveling to the farthest location almost every day, which ultimately was determined to be a great way to pad expenses. In another similar case, a regional manager had given his employees an unapproved, off-the books raise by telling them, “Just put in for a couple of hundred extra miles per week, and I’ll approve it.”
Loss prevention data can also serve as a tool for understanding training and additional support needs. In one particular case a regional manager was making what seemed to be a disproportionate number of trips to a particular store. The store was some distance from the regional manager’s house, and at first the risk management team thought it was another case of expense padding. After comparing the regional manger’s visits with the store’s performance, however, they realized that fraud wasn’t the problem. The regional manager had a weak store manager on his hands, and his trips to the store were made to help the store perform.
POS data coupled with exception-based reporting can provide operational benefits by identifying good anomalies in addition to the bad ones. With POS data, for example, you know which employee is logged onto which POS terminal at any given time; that’s how you spot somebody who’s doing a suspicious number of refunds or voids or whatever it might be. However, it’s also a way to spot somebody who’s doing an unusually good job. One retailer noticed that there were certain stores that were up about five percent a year in sales, for no particular reason: traffic was about the same, the neighborhood demographics hadn’t changed—so why was this happening?
It turned out that in these stores, the employees were very well trained in respect to sourcing inventory at alternate locations when there was an out-of-stock in their own store, and thus saving the sale.
“This is a prime example of an empowered associate who understands how seamless omnichannel retailing is supposed to work,” commented an operations manager at the retailer involved, “but the people still have to do it. By spotting these stores, and these particular associates, the system helped us raise performance across the entire chain.”
Booth 1109 and see how XBRi Loss Prevention Cloud Services can make a measurable impact across the retail enterprise.