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

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....

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Bibliographic Details
Published inJournal of financial crime Vol. 23; no. 4; pp. 798 - 805
Main Authors Carreira, Pedro, Gomes da Silva, Carlos
Format Journal Article
LanguageEnglish
Published London Emerald Group Publishing Limited 03.10.2016
Subjects
Accounting
Authenticity
Conformity
Datasets
Economic models
Mathematical programming
Statistics
Tax evasion
Benford’s law
Digital analysis
Financial crime
Fraud detection
Auditing
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Summary: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.
ISSN:1359-0790
1758-7239
DOI:10.1108/JFC-10-2015-0060