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Kazemitabar, J (2021)

Double-Crossing Benford's Law

Preprint arXiv:2105.09812 [stat.AP]; last accessed May 31, 2021.

ISSN/ISBN: Not available at this time. DOI: Not available at this time.

Abstract: Benford's law is widely used for fraud-detection nowadays. The underlying assumption for using the law is that a "regular" dataset follows the significant digit phenomenon. In this paper, we address the scenario where a shrewd fraudster manipulates a list of numbers in such a way that still complies with Benford's law. We develop a general family of distributions that provides several degrees of freedom to such a fraudster such as minimum, maximum, mean and size of the manipulated dataset. The conclusion further corroborates the idea that Benford's law should be used with utmost discretion as a means for fraud detection.

@misc{, title={Double-Crossing Benford's Law}, author={Javad Kazemitabar}, year={2021}, eprint={2105.09812}, archivePrefix={arXiv}, primaryClass={stat.AP}, url = {}, }

Reference Type: Preprint

Subject Area(s): Accounting