scholarly journals FRAUD DETECTION BY TESTING THE CONFORMITY TO BENFORD’S LAW IN THE CASE OF WHOLESALE ENTERPRISES

2017 ◽  
Vol 16 (1) ◽  
pp. 115-126 ◽  
Author(s):  
Domicián Máté ◽  
Rabeea Sadaf ◽  
Tibor Tarnóczi ◽  
Veronika Fenyves
Keyword(s):  
Fraud Detection ◽  
Benford’S Law ◽  
Benford's Law

scholarly journals Benford’s Law as an Instrument for Fraud Detection in Surveys Using the Data of the Socio-Economic Panel (SOEP)

2011 ◽  
Vol 231 (5-6) ◽  
Author(s):  
Jörg-Peter Schräpler
Keyword(s):  
Probability Function ◽  
Fraud Detection ◽  
Numerical Data ◽  
Benford’S Law ◽  
Continuous Data ◽  
Data Set ◽  
Benford's Law ◽  
User Data

SummaryThis paper focuses on fraud detection in surveys using Socio-Economic Panel (SOEP) data as an example for testing newly methods proposed here. A statistical theorem referred to as Benford’s Law states that in many sets of numerical data, the significant digits are not uniformly distributed, as one might expect, but adhere to a certain logarithmic probability function. In order to detect fraud, we derive several requirements that should, according to this law, be fulfilled in the case of survey data.We show that in several SOEP subsamples, Benford’s Law holds for the available continuous data. For this analysis, we developed a measure that reflects the plausibility of the digit distribution in interviewer clusters. We are thus able to demonstrate that several interviews that were known to have been fabricated and therefore deleted in the original user data set can now be detected using this method. Furthermore, in one subsample, we use this method to identify a case of an interviewer falsifying ten interviews not previously detected by the fieldwork organization.

scholarly journals Benford’s Law and Fraud Detection: Facts and Legends

2010 ◽  
Vol 11 (3) ◽  
pp. 397-401 ◽  
Author(s):  
Andreas Diekmann ◽  
Ben Jann
Keyword(s):  
Fraud Detection ◽  
Scientific Data ◽  
False Positives ◽  
Benford’S Law ◽  
Test Results ◽  
False Negatives ◽  
Benford's Law ◽  
Valid Test

Abstract Is Benford’s law a good instrument to detect fraud in reports of statistical and scientific data? For a valid test, the probability of ‘false positives’ and ‘false negatives’ has to be low. However, it is very doubtful whether the Benford distribution is an appropriate tool to discriminate between manipulated and non-manipulated estimates. Further research should focus more on the validity of the test and test results should be interpreted more carefully.

scholarly journals The Application of Benford’s Law in Fraud Detection: A Systematic Methodology

2019 ◽  
Vol 12 (10) ◽  
pp. 1
Author(s):  
Nirosh Kuruppu
Keyword(s):  
Fraud Detection ◽  
Benford’S Law ◽  
Financial Fraud ◽  
Spreadsheet Program ◽  
Naturally Occurring ◽  
Systematic Methodology ◽  
Benford's Law ◽  
The Cost ◽  
Financial Transactions

Benford’s Law relies on a recently proven mathematical distribution about the frequencies of naturally occurring numbers that can be efficiently applied to the detection of financial fraud. Despite the value of Benford’s Law for detecting fraud, most financial professionals are often unaware of its existence and how to best utilise the method for fraud detection. The purpose of this paper is therefore to present a systematic methodology for incorporating Benford’s Law for detecting and flagging potentially fraudulent financial transactions, that can be further investigated. This paper describes the development of Benford’s Law and demonstrates how it can be implemented systematically through a spreadsheet program to detect potential fraud. Given that the cost of financial fraud is significant with firms losing up to a tenth of their revenues, the methodology presented in this paper for implementing Benford’s Law can be a valuable tool for auditors and other financial professionals for detecting fraud.

scholarly journals On the authenticity of COVID-19 case figures

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243123
Author(s):  
Adrian Patrick Kennedy ◽  
Sheung Chi Phillip Yam
Keyword(s):  
Empirical Evidence ◽  
Fraud Detection ◽  
Zipf’S Law ◽  
World Health ◽  
Benford’S Law ◽  
Surveillance Systems ◽  
Zipf's Law ◽  
Benford's Law ◽  
Formal Statistical Analysis ◽  
Health Organization

In this article, we study the applicability of Benford’s law and Zipf’s law to national COVID-19 case figures with the aim of establishing guidelines upon which methods of fraud detection in epidemiology, based on formal statistical analysis, can be developed. Moreover, these approaches may also be used in evaluating the performance of public health surveillance systems. We provide theoretical arguments for why the empirical laws should hold in the early stages of an epidemic, along with preliminary empirical evidence in support of these claims. Based on data published by the World Health Organization and various national governments, we find empirical evidence that suggests that both Benford’s law and Zipf’s law largely hold across countries, and deviations can be readily explained. To the best of our knowledge, this paper is among the first to present a practical application of Zipf’s law to fraud detection.

Benford's Law for Fraud Detection

2020 ◽  
pp. 175-191
Author(s):  
Adriana Nunes ◽  
Helena Inácio ◽  
Rui Pedro Figueiredo Marques
Keyword(s):  
Fraud Detection ◽  
Benford’S Law ◽  
Benford's Law

In order to detect evidence of fraud effectively, it is essential for the auditor to be aware of new and differentiated methods. Thus, the auditor can identify and assess the risks of material misstatement so that auditing is as reliable as possible. In this sense, the relevance of the application of the Benford's Law arises in order to demonstrate that the identification of situations of greater risk of fraud is appropriate in auditing. The objective of this study is to analyze the behavior of 27,058 Portuguese companies.

Applications of Benford's Law

2015 ◽  
Author(s):  
Arno Berger ◽  
Theodore P. Hill
Keyword(s):  
Computer Science ◽  
Cross Section ◽  
Ad Hoc ◽  
Fraud Detection ◽  
Benford’S Law ◽  
Natural Phenomena ◽  
Pedagogical Tool ◽  
Practical Applications ◽  
Benford's Law ◽  
Main Ideas

This chapter provides a overview of the practical applications of Benford's law. These include fraud detection, detection of natural phenomena, diagnostics and design, computations and computer science, and as a pedagogical tool. In contrast to the rest of the book, this chapter is necessarily expository and informal. It has been organized into a handful of ad hoc categories, which the authors hope will help illuminate the main ideas. None of the conclusions of the experiments or data presented here have been scrutinized or verified by the authors of this book, since the intent here is not to promote or critique any specific application. Rather the goal is to offer a representative cross-section of the related scientific literature, in the hopes that this might continue to facilitate research in both the theory and practical applications of Benford's law.

Sign in / Sign up

Export Citation Format

Share Document