With any type of fraud, the sooner it’s detected, the more likely losses can be mitigated. Here’s a tool to help clients quickly assess the likelihood of earnings manipulation.
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 financial metrics are designed to capture the effects of earnings manipulation or the preconditions that can prompt a company to engage in earnings manipulation. Each metric is weighted using coefficients. For example, the days sales in receivables index has a positive coefficient because disproportionate increases might indicate an overstatement of receivables to artificially boost revenue.
The economics professor who created the Beneish model admits some important limitations. 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 or to boost revenue prior to a prospective merger.
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.
Because it’s relatively easy to use, the Beneish model can be an efficient screening tool for earnings manipulation. But a high M score doesn’t prove fraud. Rather, it suggests that further investigation is necessary. Contact a forensic accounting expert for more information.