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arXiv · 2105.09812

Double-Crossing Benford's Law

Javad Kazemitabar
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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.

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Javad Kazemitabar. 2021-05-20. Double-Crossing Benford's Law. https://arxiv.org/abs/2105.09812

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