Financial statement manipulation is the costliest type of occupational fraud. The latest Report to the Nations published by the Association of Certified Fraud Examiners found that the median loss from financial statement fraud was $800,000, compared to median losses of $114,000 for asset misappropriation and $250,000 for corruption.
With any type of fraud, the sooner it’s detected, the more likely losses can be mitigated. One tool management and fraud experts might use to assess the likelihood of earnings manipulation is the Beneish model.
The Beneish model measures the probability that a company’s revenue has been inflated and its expenses have been understated. The model generally computes an “M score” from comparisons between consecutive financial reporting periods of various metrics, including:
These metrics are designed to capture the effects of earnings manipulation or preconditions that can prompt a company to engage in earnings manipulation.
The economics professor who created the Beneish model admits there are some important limitations to the technique. Notably, the model can’t reliably be applied to privately held businesses because it was developed using public company data. Additionally, his sample involved manipulation to overstate earnings. Therefore, the model isn’t useful in circumstances where it could prove advantageous to reduce earnings — for example, to push revenue into the next quarter to help meet a target for that quarter.
Some distortions in financial statement data also could have a cause that’s unrelated to earnings manipulation. A metric might be distorted by, say, a material acquisition during the period examined, a material shift in the company’s strategy for maximizing value or a significant change in the relevant economic environment.
Simply a red flag
Because it’s relatively easy to use, the Beneish model can be an efficient screening tool for earnings manipulation. It’s important to note, however, that a high M score doesn’t prove fraud. Rather, it suggests that further investigation, preferably by forensic accounting experts, is necessary.
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