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 Uncovering Financial Shenanigans: Benford’s Law as a Computer Assisted Analytical Procedure

2020 ◽  
Vol 15 (7) ◽  
pp. 37
Author(s):  
Nirosh Kuruppu
Keyword(s):  
Analytical Procedure ◽  
Fraud Detection ◽  
Cost Effective ◽  
Economic Crime ◽  
Benford’S Law ◽  
Financial Fraud ◽  
Computer Assisted ◽  
Annual Survey ◽  
Benford's Law ◽  
Annual Turnover

PricewaterhouseCoopers (2020) has reported the highest level of economic crime in their comprehensive annual survey of the issue since it launched more than twenty years ago. Two thirds of respondents indicated that the costs of fraud can reach up to a million dollars each, amounting to approximately ten percent of their annual turnover. Inside perpetrators such as employees commit about 37 percent of these frauds. In this context, a technique known as Benford’s Law can be cost-effectively applied to detect financial fraud which can be invaluable to auditors and other financial professionals. Benford’s technique is founded on the mathematical distribution of integers found in nature and has been shown to be particularly efficient and cost-effective in financial fraud detection. The technique can swiftly flag suspicious transactions from lists of numbers that comprise millions of records when employed as a computer assisted auditing procedure. Despite this, Benford’s Law is not widely used in accounting and finance. One of the key reasons for its limited use is because fraud investigators are often incognizant and unfamiliar with the method, and how it can be implemented in a fraud detection workflow. This paper set forth a concise and organised approach for implementing Benford’s technique as an analytical procedure through the well-known IDEA generalised audit software to flag suspicious transactions, which can then be further investigated. Both the application of the method and its interpretation in situations of both compliance and non-compliance is discussed. The methodology proposed in this paper can be an indispensable aid for fraud investigators in view of the considerable costs associated with economic crime.

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 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.

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 A Relative Investigation of Various Algorithms for Online Financial Fraud Detection Techniques

2021 ◽  
Author(s):  
C Pallavi ◽  
Girija R ◽  
Vedhapriyavadhana R ◽  
Barnali Dey ◽  
Rajiv Vincent
Keyword(s):  
Credit Card ◽  
Detection System ◽  
Geographical Area ◽  
Fraud Detection ◽  
Location Analysis ◽  
Financial Fraud ◽  
Detection Techniques ◽  
Spending Patterns ◽  
Efficient Data ◽  
Financial Transactions

Online financial transactions play a crucial role in today’s economy. It becomes an unavoidable part of the business and global activities. Transaction fraud executes thoughtful intimidations to e-commerce spending. Now-a-days, the online contract or business is fetching additional sound by knowing the types of online transaction frauds associated with, these are raising which disturbs the currency accompanying business. It has the capability to confine and encumber the contract accomplished by the intruder from an honest consumer’s credit card information. In order to avoid such a problem, the proposed system is established transaction limit for the customers. Efficient data is only considered for detecting fraudulent user action and it happens only at the time of registration. Transaction which is happening for any individual is not at all known to any FDS (Fraud Detection System) consecutively at the bank which mainly issues credit cards to customers. To speak out this problem, BLA (Behaviour and Location Analysis) is executed. The FDS tracks at a credit card provided by bank. All the inbound business is directed to the FDS aimed at confirmation, authentication and verification. FDS catches the card particulars and matter to confirm that the operation is fake or genuine. The pick-up merchandises are unknown to Fraud Detection System. If the transaction is assumed to be fraud, then the corresponding bank declines it. In order to verify the individuality, uniqueness or originality, it uses spending patterns and geographical area. In case, if any suspicious pattern is identified or detected, the FDS system needs verification. The information which is already registered by the user, the system identifies infrequent outlines in the disbursement method. After three invalid attempts, the system will hinder the user. In this proposed system, most of the algorithms are checked and investigated for online financial fraud detection techniques.

Sign in / Sign up

Export Citation Format

Share Document