Assessing the omission of records from a data set using Benford’s law

Pedro Carreira and Carlos Gomes da Silva

Journal of Financial Crime, 2016, vol. 23, issue 4, 798-805

Abstract: Purpose - The purpose of this paper is to propose a methodology to estimate the number of records that were omitted from a data set, and to assess its effectiveness. Design/methodology/approach - The procedure to estimate the number of records that were omitted from a data set is based on Benford’s law. Empirical experiments are performed to illustrate the application of the procedure. In detail, two simulated Benford-conforming data sets are distorted and the procedure is then used to recover the original patterns of the data sets. Findings - The effectiveness of the procedure seems to increase with the degree of conformity of the original data set with Benford’s law. Practical implications - This work can be useful in auditing and economic crime detection, namely in identifying tax evasion. Originality/value - This work is the first to propose Benford’s law as a tool to detect data evasion.

Keywords: Financial crime; Auditing; Benford’s law; Digital analysis; Fraud detection (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:eme:jfcpps:jfc-10-2015-0060

DOI: 10.1108/JFC-10-2015-0060

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