The Detection Of Earning Manipulation

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Professor Messod Beneish created the Beneish M-score Model in 1999 in his research entitled The Detection of Earning Manipulation. He identified that earnings management is important for financial statement users to assess current economic performance, to predict future profitability, and to determine firm value (Jansen et al, 2012)
Beneish tested 74 companies and all COMPUSTAT firms matched by two-digit SIC for period of 1982-1992 and he use 8 variables model in the mathematical model.
The evidence indicates that probability of manipulation increases with:
1. Unusual increases in receivables
2. Deteriorating gross margins
3. Decreasing asset quality (as defined later)
4. Sales growth
5. Increasing accruals

The M-score
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Figure four illustrates four main steps that can be used to detect fraud or earning manipulation in the company’s financial data.

Figure 4 Beniesh Model main four steps

2.2.5 Benford’s Law definition

At the end of the nineteenth century Simon Newcomb stumbled upon what we now call Benford’s law. But in 1937, Frank Benford succinctly pronounced that a certain distribution law applies to numerical data in general, but particularly to random data with regard to leading digits.

In 1881, astronomer and mathematician, Simon Newcomb, published the first known article describing what has become known as Benford’s law in the American Journal of Mathematics. He noticed that books of logarithmic tables with low digits were considerably more dog-eared; but log tables dealing with higher digits were progressively less worn. He inferred from this pattern that fellow scientists used books with tables of lower digits far more often than they used books concerning logarithms whose first digit started with seven, eight, and nine.

In the 1930s Benford clarified this phenomenon. To put it simply, because of the effect of compounding, there are greater frequencies of numbers where the first digit is one, then fewer frequencies of numbers with first digit two, then three, and so on. Consider this example of the number 1.0000 grown at a rate of 10%:

Table 2. 1 Benfords Law digit
Growth Rate

First Digit
Relative Frequency
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