scholarly journals LEI DE NEWCOMB BENFORD E AUDITORIA CONTÁBIL: UMA REVISÃO SISTEMÁTICA DE LITERATURA

2020 ◽  
Vol 17 (2) ◽  
pp. 111
Author(s):  
Caroline De Oliveira Orth ◽  
Anna Tamires Michaelsen ◽  
Arthur Frederico Lerner
Keyword(s):  
Systematic Review ◽  
Literature Review ◽  
Corporate Finance ◽  
Natural Number ◽  
Benford’S Law ◽  
Audit Tool ◽  
Research Gaps ◽  
Accounting Data ◽  
Benford's Law ◽  
Logarithmic Distribution

Lei de Newcomb Benford - LNB, foi concebida pelo astrônomo e matemático Simon Newcomb, em 1881. Seus estudos demonstraram que a ocorrência de um número natural, de modo espontâneo ou aleatório, não se dava na proporção esperada de 1/9, mas segundo uma distribuição logarítmica. Desde então, esta lei vem sendo testada em muitas áreas do conhecimento. Em finanças corporativas, os estudiosos têm testado a lei para investigar fraudes em dados contábeis. Contudo, ainda não há consenso sobre a eficácia da LNB nesse âmbito. Assim, o objetivo deste artigo é identificar os argumentos favoráveis e contrários, bem como os métodos de pesquisa e os principais achados das pesquisas sobre a aplicação da LNB como ferramenta de auditoria. Para tanto, aplicou-se uma Revisão Sistemática de Literatura, seguindo os passos de Levy e Ellis (2006). Deste modo, além de informações sobre autoria, modelos utilizados pelos autores para suportar suas conclusões e seus principais achados, apresentam-se lacunas de pesquisa, e as implicações para o futuro da pesquisa são discutidas.Palavras-chave: Lei de Newcomb Benford. Revisão sistemática. Auditoria contábil.ABSTRACTNewcomb Benford’s Law - LNB, was conceived by the astronomer and mathematician Simon Newcomb, in 1881. His studies showed that the occurrence of a natural number, spontaneously or randomly, did not occur in the expected proportion of 1/9, but according to a logarithmic distribution. Since then, this law has been tested in many areas of knowledge. In corporate finance, scholars have tested the law to investigate fraud in accounting data. However, there is still no consensus on the effectiveness of LNB in this area. Thus, the objective of this article is to identify the arguments for and against, as well as the research methods and the main findings of research on the application of LNB as an audit tool. For that, a Systematic Literature Review was applied, following the steps of Levy and Ellis (2006). Thus, in addition to information on authorship, models used by the authors to support their conclusions and main findings, research gaps are presented, and the implications for the future of research are discussed.Keywords: Newcomb Benford’s law. Systematic review. Accounting audit..

scholarly journals A Note on Distributions of True versus Fabricated Data

1996 ◽  
Vol 83 (3) ◽  
pp. 776-778 ◽  
Author(s):  
Theodore P. Hill
Keyword(s):  
Empirical Evidence ◽  
Case Studies ◽  
Goodness Of Fit ◽  
Recent Case ◽  
Benford’S Law ◽  
Accounting Data ◽  
Goodness Of Fit Tests ◽  
Benford's Law

New empirical evidence and statistical derivations of Benford's Law have led to successful goodness-of-fit tests to detect fraud in accounting data. Several recent case studies support the hypothesis that fabricated data do not conform to expected true digital frequencies.

scholarly journals FIRST DIGIT DISTRIBUTION OF HADRON FULL WIDTH

2009 ◽  
Vol 24 (40) ◽  
pp. 3275-3282 ◽  
Author(s):  
LIJING SHAO ◽  
BO-QIANG MA
Keyword(s):  
Real World ◽  
Particle Physics ◽  
Benford’S Law ◽  
Full Width ◽  
Scale Invariant ◽  
Benford's Law ◽  
Science Domain ◽  
Logarithmic Distribution ◽  
First Time ◽  
Power Invariant

A phenomenological law, called Benford's law, states that the occurrence of the first digit, i.e. 1, 2,…, 9, of numbers from many real world sources is not uniformly distributed, but instead favors smaller ones according to a logarithmic distribution. We investigate, for the first time, the first digit distribution of the full widths of mesons and baryons in the well-defined science domain of particle physics systematically, and find that they agree excellently with the Benford distribution. We also discuss several general properties of Benford's law, i.e. the law is scale-invariant, base-invariant and power-invariant. This means that the lifetimes of hadrons also follow Benford's law.

scholarly journals Detection of Anomalies in Accounting Data Using Benford’s Law: Evidence from India

2016 ◽  
Vol 4 (1) ◽  
pp. 123 ◽  
Author(s):  
Ramesh Chandra Das ◽  
Chandra Sekhar Mishra ◽  
Prabina Rajib
Keyword(s):  
Business Group ◽  
Financial Accounting ◽  
Benford’S Law ◽  
Accounting Data ◽  
Large Size ◽  
Indian Context ◽  
Fixed Assets ◽  
Benford's Law ◽  
Initial Results ◽  
Direct Tax

This study uses the financial accounting data to examine if they depart from Benford’s Law. Using large sample of Indian public listed companies, the study conducts an analysis of the “first digit analysis”, “second digit analysis”, and “first two digit analysis “of test variables such as total assets, receivables, fixed assets, property, plant and equipment, inventory, current assets, current liabilities, sales, selling and distribution expenses, cost of goods sold, cash, EBIT, direct tax, indirect tax. The initial results find that most of the variables have significant deviation from Benford’s Law distribution. Further analyses indicate that business group firms indulge more data anomalies than standalone firms and small size firms have more data anomalies than large size firms in Indian context.

Introduction

2015 ◽  
Author(s):  
Arno Berger ◽  
Theodore P. Hill
Keyword(s):  
Numerical Data ◽  
Benford’S Law ◽  
Decimal Digit ◽  
Mathematical Framework ◽  
Benford's Law ◽  
History Of ◽  
Logarithmic Distribution ◽  
Benford Law ◽  
Special Case

This introductory chapter provides an overview of Benford' law. Benford's law, also known as the First-digit or Significant-digit law, is the empirical gem of statistical folklore that in many naturally occurring tables of numerical data, the significant digits are not uniformly distributed as might be expected, but instead follow a particular logarithmic distribution. In its most common formulation, the special case of the first significant (i.e., first non-zero) decimal digit, Benford's law asserts that the leading digit is not equally likely to be any one of the nine possible digits 1, 2, … , 9, but is 1 more than 30 percent of the time, and is 9 less than 5 percent of the time, with the probabilities decreasing monotonically in between. The remainder of the chapter covers the history of Benford' law, empirical evidence, early explanations and mathematical framework of Benford' law.

Benford's Law: Analyzing a Decade of Financial Data

2013 ◽  
Vol 10 (1) ◽  
pp. 1-39 ◽  
Author(s):  
Fatima A. Alali ◽  
Silvia Romero
Keyword(s):  
Discretionary Accruals ◽  
Financial Data ◽  
Financial Accounting ◽  
Benford’S Law ◽  
Public Companies ◽  
Accounting Data ◽  
Large Sample ◽  
Big 4 ◽  
Benford's Law

ABSTRACT This study uses a decade of financial accounting data to examine if and how they depart from Benford's Law. Using a large sample of U.S. public companies, we conduct an analysis of the first-two digits of data items generally used in research to measure total accruals and discretionary accruals and where fraud, restatements, and enforcement actions are revealed. We break down a decade of data into six subperiods; pre-SOX Period (2001), SOX 1 Period (2002–2003), SOX 2 Period (2004–2006), SOX 3 Period (2007), Crisis 1 Period (2008), and Crisis 2 Period (2009–2010). We find different indicators of manipulation during the periods studied, as well as differences between small and big companies and companies audited by Big 4 and non-Big 4 firms.

scholarly journals Using Benford’s Law to detect data error and fraud: An examination of companies listed on the Johannesburg Stock Exchange

2014 ◽  
Vol 9 (3) ◽  
pp. 341-354 ◽  
Author(s):  
A Saville
Keyword(s):  
Stock Exchange ◽  
Financial Analysts ◽  
Benford’S Law ◽  
Accounting Data ◽  
Johannesburg Stock Exchange ◽  
Accounting Numbers ◽  
Benford's Law ◽  
Data Error ◽  
The Law ◽  
Private Investors

Accounting numbers generally obey a mathematical law called Benford’s Law, and this outcome is so unexpected that manipulators of information generally fail to observe the law. Armed with this knowledge, it becomes possible to detect the occurrence of accounting data that are presented fraudulently. However, the law also allows for the possibility of detecting instances where data are presented containing errors. Given this backdrop, this paper uses data drawn from companies listed on the Johannesburg Stock Exchange to test the hypothesis that Benford’s Law can be used to identify false or fraudulent reporting of accounting data. The results support the argument that Benford’s Law can be used effectively to detect accounting error and fraud. Accordingly, the findings are of particular relevance to auditors, shareholders, financial analysts, investment managers, private investors and other users of publicly reported accounting data, such as the revenue services

Data Diagnostics Using Second-Order Tests of Benford's Law

2009 ◽  
Vol 28 (2) ◽  
pp. 305-324 ◽  
Author(s):  
Mark J. Nigrini ◽  
Steven J. Miller
Keyword(s):  
Numerical Data ◽  
Second Order ◽  
Benford’S Law ◽  
Data Sets ◽  
Data Set ◽  
Accounting Data ◽  
Benford's Law ◽  
Rounded Data ◽  
Analytical Procedures ◽  
Digit Frequencies

SUMMARY: Auditors are required to use analytical procedures to identify the existence of unusual transactions, events, and trends. Benford's Law gives the expected patterns of the digits in numerical data, and has been advocated as a test for the authenticity and reliability of transaction level accounting data. This paper describes a new second-order test that calculates the digit frequencies of the differences between the ordered (ranked) values in a data set. These digit frequencies approximate the frequencies of Benford's Law for most data sets. The second-order test is applied to four sets of transactional data. The second-order test detected errors in data downloads, rounded data, data generated by statistical procedures, and the inaccurate ordering of data. The test can be applied to any data set and nonconformity usually signals an unusual issue related to data integrity that might not have been easily detectable using traditional analytical procedures.

scholarly journals Do the Financial Statements of Listed Companies on the Ljubljana Stock Exchange Pass the Benford’s Law Test?

2018 ◽  
Vol 12 (1) ◽  
pp. 54
Author(s):  
Natasa Omerzu ◽  
Iztok Kolar
Keyword(s):  
Stock Exchange ◽  
Financial Statements ◽  
Listed Companies ◽  
Financial Data ◽  
Theoretical Distribution ◽  
Benford’S Law ◽  
Digital Analysis ◽  
Accounting Data ◽  
Benford's Law ◽  
Long Time

Currently, we need to think about the risks in using the financial statements. Abroad, for a long time, in the detection of irregularities in the financial statements, Benford's law test has been used, which is a very simple, objective and efficient digital analysis that can help identify controversial areas. Since, in Slovenia, its use is still unknown and in practice, and it is rarely used, we checked whether the financial statements of Slovenian companies listed on the Ljubljana Stock Exchange pass the Benford’s law test. Our study is original, as no one has ever tested the company's financial statements on the Ljubljana Stock Exchange with this test. We found that the tested data very well matched the theoretical distribution according to Benford's law. If the deviation of the analysed data from the theoretical distribution is very large, this does not mean that this is a possible fraud in the used financial data. Benford's law helps us identify the controversial areas that require our attention and the decision on how to proceed with the audit or possible investigation of accounting data.

scholarly journals A Study on Public Blockchain Consensus Algorithms: A Systematic Literature Review

2020 ◽  
Author(s):  
Islahuddin Jalal ◽  
Zarina Shukur ◽  
Khairul Azmi Abu Bakar
Keyword(s):  
Systematic Review ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Relevant Literature ◽  
Review Of The Literature ◽  
Research Gaps ◽  
Consensus Algorithms ◽  
Incentive Strategies ◽  
Future Work

The purpose of this study is to present a systematic review of the literature on public blockchain consensus algorithms. Blockchain consensus algorithms have gain much popularity in last few years especially in the cryptocurrency field. Based on a systematic review of the relevant literature, we provide a classification of blockchain consensus algorithms, philosophy behind creation of blockchain consensus algorithms and as well as the rewards and incentive strategies of various public blockchain consensus algorithms. On the basis of these results, the research gaps and future work directions are identified for further study.

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