BENFORD'S LAW: an analysis of its applicability in a sample of tax documents presented in the senators’ accountability
Main Article Content
Abstract
Article Details
The journal has exclusive rights over the first publication, printed and/or digital, of this academic text, which does not affect the copyright of the person responsible for the research.
The reproduction (in whole or in part) of the published material depends on the express mention of this journal as the origin, by citing the volume, edition number and the DOI link for cross-reference. For rights purposes, the original publication source must be recorded.
The use of the results published here in other vehicles of scientific divulgation, even if by the authors, depends on the express indication of this journal as a means of original publication, under penalty of characterizing a situation of self-plagiarism.
____________________________________________
Additional information and author statements
(scientific integrity)
Declaration of conflict of interest: The author(s) confirm that there are no conflicts of interest in conducting this research and writing this article.
Authorship statement: All and only researchers who meet the authorship requirements for this article are listed as authors; all co-authors are fully responsible for this work in its entirety.
Declaration of originality: The author(s) guarantee that the text published here has not been previously published elsewhere and that future republication will only be made with express reference to the original place of publication; also certifies that there is no plagiarism of third-party material or self-plagiarism.
____________________________________________
Archiving and distribution
The final published PDF can be archived, without restrictions, on any open access server, indexer, repository or personal page, such as Academia.edu and ResearchGate.
How to Cite
References
BADAL-VALERO, E.; ALVAREZ-JAREÑO, J. A.; PAVÍA, J. M. Combining Benford’s Law and machine learning to detect money laundering. An actual Spanish court case. Forensic Science International, v. 282, pp 24-34, 2018.
BENFORD, F. The law of anomalous numbers. Proceedings of the American Philosophical Society, v. 78, n. 4, p. 551-572, 1938.
BERGER, A.; HILL, T. P. An Introduction to Benford’s Law. United Kingdom: Princeton University Press, 2015.
BRASIL, Senado Federal. Transparência: Dados Abertos – CEAPS. Brasília. (2019). Recuperado de https://www12.senado.leg.br/transparencia/dados-abertos-transparencia/dados-abertos-ceaps.
CARSLAW, C. A. P. N. Anomalies in income numbers: Evidence of goal oriented behavior. The Accounting Review, v. 63, n. 2, p. 321-327, 1988.
DRAKE, P. D.; NIGRINI, M. J. Computer Assisted Analytical Procedures Using Benford’s Law. Journal of Accounting Education, v. 18, n. 2000, 127-146, 2000.
DURTSCHI, C.; HILLISON, W.; PACINI, C. The effective use of Benford's Law to assist in detecting fraud in accounting data. Journal of Forensic Accounting, v. 5, n 1, p. 17-34, 2004.
HILL, T. P. The significant-digit phenomenon. The American Mathematical Monthly, v. 102, n. 4, p. 332-327, 1995.
KRAKAR, Z.; ŽGELA, M. Application of Benford's Law in payment systems auditing. Journal of Information and Organizational Sciences, v. 33, n. 1, p. 39-51, 2009.
MEHTA, A.; BHAVANI, G. Application of forensic tools to detect fraud: The case of Toshiba. Journal of Forensic & Investigative Accounting, v. 9, n. 1, p. 692-710, 2017.
NEWCOMB, S. Note on the frequency of use of the different digits in natural numbers. American Journal of Mathematics, v. 4, n. 1, p. 39-40, 1881.
NIGRINI, M. J. A taxepayer compliance application of Benford's Law. The Journal of American Taxation Association, v. 18, Spring, p. 72-91, 1996.
NIGRINI, M. J.; MILLER, S. J. Data diagnostics using second-order tests of Benford’s Law. Auditing: A Journal of Practice & Theory, v. 28, n. 2, p. 305-324, 2009.
NIGRINI, M. J.; MITTERMAIER, L. J. The use of Benford's Law as an aid in analytical procedures. Auditing: A Journal of Practice & Theory, v. 16, n. 2, p. 52-67, 1997.
PETERSON, B. K. Fraud education for accounting students. Journal of Education for Business, v. 78, n. 5, p. 263-267, 2003.
SHAPIRO, S. D. Collaring the crime, not the criminal: reconsidering the concept of white-collar crime. American Sociological Review, v. 35, n. 3, p. 346-365, 1990.
THOMAS, J. K. Unusual patterns in reported earnings. The Accounting Review, v. 64, n. 4, p. 773-787, 1989.
WHYMAN, G. et al. Revisiting the Benford Law: When the Benford-like distribution of leading digits in sets of numerical data is expectable? Physica A: Statistical Mechanics and its Applications, n. 461, p. 595-601, 2016.
WONG, S.; VENKATRAMAN, V. Financial Accounting Fraud Detection Using Business Intelligence. Asian Economic and Finance Review, v. 5, n. 11, p. 1187-1207, 2015.
YANG, S.; WEI, L. Detecting money laundering using filtering techniques: A multiple-criteria index. Journal of Economic Policy Reform, v. 13, n. 2, p. 159-178, 2010.