The paper "Benford's Law and its Application in Auditing" is a perfect example of finance and accounting coursework. In recent times various cases of corporate collapses have been reported, including big corporations, such as Worldcom, Enron and HIH. These collapses have mainly been attributed to accounting fraud, which may have been known by auditors or not known. This has brought auditors under sharp focus given that it is their work to certify the true and fair view of the financial statement. One of the main tools the auditors can use to detect accounting malpractices includes Benford's Law.
In this paper, I review the Benford's Law and show how it can be applied to detect accounting fraud using the payables data. Besides, people commit accounting fraud due to various reasons that shall as well be discussed in the last section of the paper followed by a conclusion. Benford's Law and its Application in Auditing Frank Benford, a research physicist at General Electric founded the Benford’ s Law in 1923. In the course of his career, Benford came to realize that the numbers beginning with the digit one was used more often (around 33 per cent of the time) than numbers beginning with digit two to nine.
In general, the frequency kept declining as the numbers progressed from 1 through to 9, as indicated below; The Benford’ s Law is also known as the first – digit law or the law of naturally occurring numbers. Brenford’ s Law can be applied to detect abnormalities in large data sets in various fields. For instance, analysts such as Hal Varian and Mark Nigrini have used the Law to detect possible frauds in socio-economic data, in-forensic accounting and auditing respectively.
In auditing, the law of naturally-occurring numbers can be used to detect accounting frauds in financial data. Lynch and Zhu (2008) state that a set of non– manipulated naturally occurring numbers would display the highest frequency for leading digit as 1 and lowest for 9. The minute this pattern is disturbed at any point in time, auditors can be able to track errors or fraud. This is grounded on the assumption that people who commit accounting fraud are disposed to make up figures that tend to distribute their digits quite evenly.
Therefore, a simple comparison of first digits’ frequency distribution ought to detect the irregular entries. In the following part, the payables data is used to show how Benford’ s Law can be used to detect accounting fraud. The excel ActiveData functionality tool is used for the analysis. The first step is to select ‘ Digital Analysis’ . Under the appearing window, we select ‘ Invoice_amount’ and uncheck ‘ Include Stratified Analysis’ . Then make sure to check ‘ First Digits Test’ and click ‘ Finished’ , as shown below; Excel will generate a series of data and graph representation based on the first-digit test for the analysis of invoice amount as shown below; From the figure above, it is clear that the digit counts of 4, 5 and 6 show a deviation between the payable’ s data proportion and Benford proportion.
Therefore, the payables data contains some erroneous entries, which could point to possible fraud. Notice that the payables data proportion bars do not touch the Benford proportion curve.
Lynch, L., and Zhu, X. (2008). Putting Benford's Law to Work. Retrieved November 22, 2015, from The Institute of Internal Auditors: https://iaonline.theiia.org/putting-benfords-law-to-work
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