Journal of Accountancy 196(2), pp. 58-60.
ISSN/ISBN: Not available at this time. DOI: Not available at this time.
Abstract: This article presents information on how to use Benford's Law to detect irregularities in large data sets in Microsoft Excel, while customizing Excel to perform sophisticated digital analyses that can uncover errors and fraud. Benford's Law predicts the occurrence of digits in large sets of numbers. Simply put, it states that one can expect some digits to occur more often than others. For example, the numeral 1 should occur as the first digit in any multiple-digit number about 31% of the time, while 9 should occur as the first digit only 5% of the time. One also can apply the law to determine the expected occurrence of the second digit of a number, the first two digits of a number and other combinations. Benford's Law is not effective for all financial data. If the data set is small, the law becomes less accurate because there are not enough items in the sample and so the rules of randomness don't apply or at least apply with less predictability. Also, if the data include built-in minimums and maximums, they also might not conform well to the law's predictions.
Bibtex:
@article{,
title={Turn Excel into a financial sleuth},
author={Rose, Anna M and Rose, Jacob M},
journal={JOURNAL OF ACCOUNTANCY-NEW YORK-},
volume={196},
number={2},
pages={58--62},
year={2003},
publisher={AICPA AMERICAN INSTITUTE OF CERTIFIED}
}
Reference Type: Journal Article
Subject Area(s): Accounting