A manager of one of a retailer's several retail outlets is stealing cash from cash sales, recording the sales as accounts receivable, and subsequently writing off the fictitious accounts receivable as bad debts. Which of the following comparisons would be most effective in signaling the possibility of such a fraud?
The best way to detect the manager's fraud is to compare bad debt expense as a percentage of sales to that of the other outlets. Doing so provides a direct comparison against similar environments, making any abnormalities more visible. If the manager is stealing cash and recording the sales as accounts receivable, and then writing these off as bad debts, this would cause the bad debt expense ratio to be higher in their specific outlet compared to others. Comparing it to previous years wouldn't be as effective because the fraudulent activity might have been occurring for multiple years, making the current year's comparison less revealing.
Also if the manager has been doing this over the past few years, comparing to other years would not flag, for e.g. a spike
Why A and B
This store has a suspicious actions from the manager, however, fraud cannot be identified if IA compare results to prior years of this give store performance as manager might change. Just one example. It is better to compare performance of the store to other stores owed by the retailer. Hope that helps.
Comparing percentages (C and D) is not a good procedure because the weight of a single entry can be significant. Here, the outlets have similar activities. Thus a simple internal benchmark would make it possible to observe differences (option A). If the thief had been managing several retail outlets for a while, option B would be more appropriate.