Benford's law in forensic analysis of registered turnover

Abstract

Forensic accounting in scientific sense is the part of accounting that assumes the practice of scientific techniques and methods in conducting investigations and detecting criminal activities in financial statements, business statements and companies. One such tool in detecting anomalies in accounting records is the Benford’s Law, which gives the expected pattern of digit frequencies in numeric data sets according to their position in numbers. Because of this property, Benford's law has become a significant forensic tool for the detection of anomalies, especially in financial business. One of the most important sources is account turnover data in the observed period, which has a debt and credit side. A classic way of analyzing these liabilities is to merge them and then look for a pattern of leading digits. In such approach, it is not possible to properly determine the source of anomalies, which are a guide to deeper analysis. For such purposes, a variant of the Hosmer-Lemeshow test is designed.

(Previously published on Sciendo: https://sciendo.com/article/10.2478/jfap-2021-0004, pod licencom CC BY-NC-ND 4.0)