(In)efficiency of Beneish M Score model in detecting fraud in financial statements

The creation and application of accounting standards (International Accounting Standards (IAS), International Financial Reporting Standards (IFRS), American Generally Accepted Accounting Principles (GAAP)) that would have universal acceptability was the guiding idea of the most important accounting authorities when they started the process of defining and adopting accounting rules and procedures (standards), which we could call international professional accounting regulation. However, a certain "rigidity" that became immanent in the aforementioned standards was somewhat "depreciated" by prescribing at least two, and often more, permitted procedures, which put accountants in a position where their subjective preference for a certain procedure can, to a greater or lesser extent, influence the height of the periodic result. In this way, the so-called creative accounting, which with its techniques or methods helps managers, (co)owners, and/or accountants in compiling financial reports that are usually prepared in accordance with legal and professional regulations, but contrary to its spirit, results in an asset-financial and profitable position of a business (accounting entity) that deviates to a greater or lesser extent from what could be characterized as true and fair. Checking the "freedom" in the choice of adequate accounting rules and procedures, i.e., checking the correctness and objectivity of the compiled set of financial reports can be done by applying several methods and techniques developed by forensic accountants, as well as experts from other fields. In the continuation of this article, we will try to explain in more detail the essence of Beneish's M-score model for detecting possible inconsistencies in the asset-financial and yield position of the observed accounting entity, the results that confirm its (in)efficiency, as well as the doubts that still exist and that can raise doubts about the (all) possibility of this model in detecting fraud in financial statements.