• Login
    View Item 
    •   NWU-IR Home
    • Electronic Theses and Dissertations (ETDs)
    • Economic and Management Sciences
    • View Item
    •   NWU-IR Home
    • Electronic Theses and Dissertations (ETDs)
    • Economic and Management Sciences
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Evaluating the effectiveness of Benford's law as an investigative tool for forensic accountants

    Thumbnail
    View/Open
    Kellerman_L.pdf (1.093Mb)
    Date
    2014
    Author
    Kellerman, Lizan
    Metadata
    Show full item record
    Abstract
    “Some numbers really are more popular than others.” Mark J. Nigrini (1998a:15) The above idea appears to defy common sense. In a random sequence of numbers drawn from a company’s financial books, every digit from 1 to 9 seems to have a one-in-nine chance of being the leading digit when used in a series of numbers. But, according to a mathematical formula of over 60 years old making its way into the field of accounting, certain numbers are actually more popular than others (Nigrini, 1998a:15). Accounting numbers usually follow a mathematical law, named Benford’s Law, of which the result is so unpredictable that fraudsters and manipulators, as a rule, do not succeed in observing the Law. With this knowledge, the forensic accountant is empowered to detect irregularities, anomalies, errors or fraud that may be present in a financial data set. The main objective of this study was to evaluate the effectiveness of Benford’s Law as a tool for forensic accountants. The empirical research used data from Company X to test the hypothesis that, in the context of financial fraud investigations, a significant difference between the actual and expected frequencies of Benford’s Law could be an indication of an error, fraud or irregularity. The effectiveness of Benford’s Law was evaluated according to findings from the literature review and empirical study. The results indicated that a Benford’s Law analysis was efficient in identifying the target groups in the data set that needed further investigation as their numbers did not match Benford’s Law.
    URI
    http://hdl.handle.net/10394/11729
    Collections
    • Economic and Management Sciences [4104]

    Copyright © North-West University
    Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     

    Browse

    All of NWU-IR Communities & CollectionsBy Issue DateAuthorsTitlesSubjectsAdvisor/SupervisorThesis TypeThis CollectionBy Issue DateAuthorsTitlesSubjectsAdvisor/SupervisorThesis Type

    My Account

    LoginRegister

    Copyright © North-West University
    Contact Us | Send Feedback
    Theme by 
    Atmire NV