Selecting Audit Samples Using Benford's Law

We contribute to digital analysis by developing two mathematical programming models that can assist auditors in selecting more promising audit samples, using Benford's law. One model identifies the smallest subset of nonconforming records in a dataset, given some predefined conformity criteria,...

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Published inAuditing : a journal of practice and theory Vol. 32; no. 2; pp. 53 - 65
Main Authors da Silva, Carlos Gomes, Carreira, Pedro M. R.
Format Journal Article
LanguageEnglish
Published Sarasota American Accounting Association 01.05.2013
Subjects
Auditing
Auditors
Conformity
Manipulation
Mathematical models
Mathematical programming
Studies
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Abstract We contribute to digital analysis by developing two mathematical programming models that can assist auditors in selecting more promising audit samples, using Benford's law. One model identifies the smallest subset of nonconforming records in a dataset, given some predefined conformity criteria, and the other highlights the k most nonconforming records. The models take into account several conformity tests and test statistics simultaneously. The application of the models is illustrated using suggested protocols on a set of simulated data. Finally, the effectiveness of the models in detecting typical data manipulations is assessed under different contamination levels.
AbstractList We contribute to digital analysis by developing two mathematical programming models that can assist auditors in selecting more promising audit samples, using Benford's law. One model identifies the smallest subset of nonconforming records in a dataset, given some predefined conformity criteria, and the other highlights the k most nonconforming records. The models take into account several conformity tests and test statistics simultaneously. The application of the models is illustrated using suggested protocols on a set of simulated data. Finally, the effectiveness of the models in detecting typical data manipulations is assessed under different contamination levels. [PUBLICATION ABSTRACT]
We contribute to digital analysis by developing two mathematical programming models that can assist auditors in selecting more promising audit samples, using Benford's law. One model identifies the smallest subset of nonconforming records in a dataset, given some predefined conformity criteria, and the other highlights the k most nonconforming records. The models take into account several conformity tests and test statistics simultaneously. The application of the models is illustrated using suggested protocols on a set of simulated data. Finally, the effectiveness of the models in detecting typical data manipulations is assessed under different contamination levels.
Author da Silva, Carlos Gomes
Carreira, Pedro M. R.
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10.1016/S0748-5751(00)00008-7
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10.1080/00029890.1994.11997041
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SubjectTerms Auditing
Auditors
Conformity
Manipulation
Mathematical models
Mathematical programming
Studies
Title Selecting Audit Samples Using Benford's Law
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