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.

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

Auditing A Journal of Practice & Theory ◽

10.2308/aud.2009.28.2.305 ◽

2009 ◽

Vol 28 (2) ◽

pp. 305-324 ◽

Cited By ~ 30

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.

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Benford’s Law in Forensic Analysis of Income Statements of Economic Entities in Bosnia and Herzegovina

10.15179/ces.23.1.2 ◽

2021 ◽

Vol 23 (1) ◽

pp. 31-61

Author(s):

Ševala Isaković-Kaplan ◽

◽

Lejla Demirović ◽

Mahir Proho ◽

◽

...

Keyword(s):

Bosnia And Herzegovina ◽

Financial Statements ◽

Forensic Analysis ◽

Financial Statement ◽

Benford’S Law ◽

Business Decisions ◽

Full Disclosure ◽

Wide Range ◽

Benford's Law ◽

And Performance

The objective of preparing and presenting financial statements is to provide information about the financial position and performance of an entity, which is useful to a wide range of users of financial statements for business decisions. If information presented in the financial statements is not full disclosure and/or is incorrect, the presented image of the business entity will be wrong, as well as business decisions made on the basis of such financial statements. Unfortunately, many entities knowingly manipulate revenues and expenses to manage earnings in a way that suits the entity management. Detecting frauds in financial statements is the primary task of forensic accountants. This paper analyzes the possibilities of applying Benford’s law in the forensic analysis of income statements of economic entities in Bosnia and Herzegovina, to detect possible earnings manipulation. The results of the research confirm that the positions of revenues and expenses in the income statements of economic entities in Bosnia and Herzegovina generally follow Benford’s law, but also stress the need to increase attention and conduct additional forensic investigations for certain items as indicators of financial statement manipulation.

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The Application of Benford's Law in Forensic Accounting: An Analysis of Credit Bureau Data

SSRN Electronic Journal ◽

10.2139/ssrn.1626696 ◽

2010 ◽

Cited By ~ 1

Author(s):

Syed Azfar Hussain

Keyword(s):

Benford’S Law ◽

Forensic Accounting ◽

Benford's Law ◽

Credit Bureau

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Reliability of Financial Information from the Perspective of Benford’s Law

Entropy ◽

10.3390/e23050557 ◽

2021 ◽

Vol 23 (5) ◽

pp. 557

Author(s):

Ionel Jianu ◽

Iulia Jianu

Keyword(s):

Financial Reporting ◽

Capital Market ◽

Financial Statements ◽

Financial Information ◽

Benford’S Law ◽

Professional Judgment ◽

Reporting Standards ◽

Financial Reporting Standards ◽

Benford's Law ◽

Before And After

This study investigates the conformity to Benford’s Law of the information disclosed in financial statements. Using the first digit test of Benford’s Law, the study analyses the reliability of financial information provided by listed companies on an emerging capital market before and after the implementation of International Financial Reporting Standards (IFRS). The results of the study confirm the increase of reliability on the information disclosed in the financial statements after IFRS implementation. The study contributes to the existing literature by bringing new insights into the types of financial information that do not comply with Benford’s Law such as the amounts determined by estimates or by applying professional judgment.

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Abiding by the Law? Using Benford’s Law to Examine the Accuracy of Nonprofit Financial Reports

Nonprofit and Voluntary Sector Quarterly ◽

10.1177/0899764019881510 ◽

2019 ◽

Vol 49 (3) ◽

pp. 548-570 ◽

Cited By ~ 1

Author(s):

Heng Qu ◽

Richard Steinberg ◽

Ronelle Burger

Keyword(s):

Statistical Methods ◽

Organizational Level ◽

Benford’S Law ◽

Financial Reports ◽

Forensic Accounting ◽

Data Form ◽

Benford's Law ◽

Natural Data ◽

The Individual ◽

Academic Study

Benford’s Law asserts that the leading digit 1 appears more frequently than 9 in natural data. It has been widely used in forensic accounting and auditing to detect potential fraud, but its application to nonprofit data is limited. As the first academic study that applies Benford’s Law to U.S. nonprofit data (Form 990), we assess its usefulness in prioritizing suspicious filings for further investigation. We find close conformity with Benford’s Law for the whole sample, but at the individual organizational level, 34% of the organizations do not conform. Deviations from Benford’s law are smaller for organizations that are more professional, that report positive fundraising and administration expenses, and that face stronger funder oversight. We suggest improved statistical methods and experiment with a new measure of the extent of deviation from Benford’s Law that has promise as a more discriminating screening metric.

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Benford's Law Verification on Local Government Financial Statements

Korean Governmental Accounting Review ◽

10.15710/kgar.2021.19.1.137 ◽

2021 ◽

Vol 19 (1) ◽

pp. 137-166

Author(s):

Ho-Nam Moon ◽

◽

Dong-Wuk Kim

Keyword(s):

Local Government ◽

Financial Statements ◽

Benford’S Law ◽

Benford's Law

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Benfordʼs Law Geometry

Benford's Law ◽

10.23943/princeton/9780691147611.003.0004 ◽

2015 ◽

Author(s):

Lawrence Leemis

Keyword(s):

Empirical Data ◽

Probability Distributions ◽

Benford’S Law ◽

Data Sets ◽

Normal Distributions ◽

Benford's Law ◽

Using Data

This chapter switches from the traditional analysis of Benford's law using data sets to a search for probability distributions that obey Benford's law. It begins by briefly discussing the origins of Benford's law through the independent efforts of Simon Newcomb (1835–1909) and Frank Benford, Jr. (1883–1948), both of whom made their discoveries through empirical data. Although Benford's law applies to a wide variety of data sets, none of the popular parametric distributions, such as the exponential and normal distributions, agree exactly with Benford's law. The chapter thus highlights the failures of several of these well-known probability distributions in conforming to Benford's law, considers what types of probability distributions might produce data that obey Benford's law, and looks at some of the geometry associated with these probability distributions.

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