Web‐Based Contracts: You Could Be Burned!

Durtschi, Cindy; Hillison, William A.; Pacini, Carl J.

doi:10.1002/jcaf.10080

Cited by 24 publications

(28 citation statements)

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“…Since the pioneering works of Newcomb and Benford, a large number of works related to Benford's law have been reported in various contexts (for a fascinating history of Benford's law, see [3][4][5]). For example, it's presence and applicability have been investigated in various domains, like astrophysics [6,7], geography [8], biology [9][10][11], seismography [12], stock market and accounting [13,14]. Interestingly, violation of Benford's law has been found to be capable of detecting cases of tax fraud [15] and election fraud [16], and it's routinely used by accounting professionals to detect financial irregularities.…”

Section: Introductionmentioning

confidence: 99%

Benford’s Distribution in Extrasolar World: Do the Exoplanets Follow Benford’s Distribution?

2017

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In many real life situations, it is observed that the first digits (i.e., 1, 2, . . . , 9) of a numerical data-set, which is expressed using decimal system, do not follow a random distribution. Instead, the probability of occurrence of these digits decreases in almost exponential fashion starting from 30.1% for 1 to 4.6% for 9. Specifically, smaller numbers are favoured by nature in accordance with a logarithmic distribution law, which is referred to as Benford's law. The existence and applicability of this empirical law have been extensively studied by physicists, accountants, computer scientists, mathematicians, statisticians, etc., and it has been observed that a large number of data-sets related to diverse problems follow this distribution. However, except two recent works related to astronomy, applicability of Benford's law has not been tested for extrasolar objects. Motivated by this fact, this paper investigates the existence of Benford's distribution in the extrasolar world using Kepler data for exoplanets. The investigation has revealed the presence of Benford's distribution in various physical properties of these exoplanets. Further, Benford goodness parameters are computed to provide a quantitative measure of coincidence of real data with the ideal values obtained from Benford's distribution. The quantitative analysis and the plots have revealed that several physical parameters associated with the exoplanets (e.g., mass, volume, density, orbital semi-major axis, orbital period, and radial velocity) nicely follow Benford's distribution, whereas some physical parameters (e.g., total proper motion, stellar age and stellar distance) moderately follow the distribution, and some others (e.g., longitude, radius, and effective temperature) do not follow Benford's distribution. Further, some specific comments have been made on the possible generalizations of the obtained result, its potential applications in analyzing data-set of candidate exoplanets, and how interested readers can perform similar investigations on other interesting data-sets.

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Section: Introductionmentioning

confidence: 99%

Benford’s Distribution in Extrasolar World: Do the Exoplanets Follow Benford’s Distribution?

2017

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“…Drake and Nigrini 19 developed the digital analysis techniques for audit usage. Durtschi et al 20 , on the other hand, pointed out that the BL is less effective when the deviated transaction number is relatively low in the data set, and although the data set is not in conformity with BL distribution, there is no fraud.…”

Section: Literaturementioning

confidence: 99%

Is Benford’s Law Effective in Fraud Detection for Expense Cycle?

Ergin

Erturan

2020

Marmara Üniversitesi İktisadi Ve İdari Bilimler Dergisi

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Despite measures taken by firms to prevent fraud, it has been found in recent studies that losses derived from fraudulent activities are increasing on a global basis. International standards on auditing do not define which analytical approaches and technological tools to be used in performing audit. Decisions are left on the auditor's judgment. Auditors try to use digital techniques to deal with mass data sets generated by firms. Academic research may mislead practitioners as controversial outcomes exist in literature concerning empirical research. Benford's Law (BL) is one of the methods used frequently in digital analysis. Although some researchers defend the use of BL in audit, especially in fraud detection, this paper disputes its effectiveness for expense cycle. Different firm's data are tested to conclude that the use of BL is not appropriate for expense items. The reasons of this deficiency are explained in this paper.

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“… Determining the plausibility of the given triangle/trapezoid;  detecting fraud in the given data (cf. Durtschi et al [6] or Diekmann & Jann [5] );  detecting outliers (this might be helpful for further analysis).…”

Section: Possible Reasons For Checking This Can Bementioning

confidence: 99%

Empirical Analysis of Claims Development Trapezoids following Benford’s Law

Heberle¹,

Gummersbach²

2018

FSJ

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In this paper we make an empirical analysis of a wide range of claims developmenttrapezoids following Benford’s law. In particular we determine Benfors’s law fordifferent characteristic factors depending on claims development triangles/trapezoids.These characteristic factors are the cumulative claims payments, the incrementalclaims payments and the individual development factors. For each characteristic factor hypothesis testing is done for verifying/rejecting Benford’s law.

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Web‐Based Contracts: You Could Be Burned!

Abstract: The Internet is the new Wild West for companies venturing into Web‐based commerce. Someone can consent to complex electronic agreements with a simple mouse click. But what must you know so you don't get burned? © 2002 Wiley Periodicals, Inc.

Cited by 24 publications

References 0 publications

Benford’s Distribution in Extrasolar World: Do the Exoplanets Follow Benford’s Distribution?

Benford’s Distribution in Extrasolar World: Do the Exoplanets Follow Benford’s Distribution?

Is Benford’s Law Effective in Fraud Detection for Expense Cycle?

Empirical Analysis of Claims Development Trapezoids following Benford’s Law

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