The Application of Benford’s Law in Fraud Detection: A Systematic Methodology
- Nirosh Kuruppu
Abstract
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.
- Full Text: PDF
- DOI:10.5539/ibr.v12n10p1
Journal Metrics
h-index (January 2024): 102
i10-index (January 2024): 947
h5-index (January 2024): N/A
h5-median(January 2024): N/A
( The data was calculated based on Google Scholar Citations. Click Here to Learn More. )
Index
- Academic Journals Database
- ACNP
- ANVUR (Italian National Agency for the Evaluation of Universities and Research Institutes)
- CNKI Scholar
- COPAC
- CrossRef
- EBSCOhost
- EconBiz
- ECONIS
- EconPapers
- Elektronische Zeitschriftenbibliothek (EZB)
- EuroPub Database
- Excellence in Research for Australia (ERA)
- Genamics JournalSeek
- Google Scholar
- Harvard Library
- IBZ Online
- IDEAS
- Infotrieve
- Kobson
- LOCKSS
- Mendeley
- MIAR
- Norwegian Centre for Research Data (NSD)
- PKP Open Archives Harvester
- Publons
- Qualis/CAPES
- RePEc
- ResearchGate
- ROAD
- Scilit
- SHERPA/RoMEO
- SocioRePEc
- Technische Informationsbibliothek (TIB)
- The Keepers Registry
- UCR Library
- Universe Digital Library
- ZBW-German National Library of Economics
- Zeitschriften Daten Bank (ZDB)
Contact
- Kevin DuranEditorial Assistant
- ibr@ccsenet.org