Conditional probability of actually detecting a financial fraud - A neutrosophic extension to Benford's Law

Sukanto Bhattacharya, Kuldeep Kumar, Florentin Smarandache

Research output: Contribution to journalArticleResearchpeer-review

Abstract

This study actually draws from and builds on an earlier paper (Kumar and
Bhattacharya, 2002). Here we have basically added a neutrosophic dimension to
the problem of determining the conditional probability that a financial fraud has
been actually committed, given that no Type I error occurred while rejecting the
null hypothesis H0: The observed first-digit frequencies approximate a Benford
distribution; and accepting the alternative hypothesis H1: The observed first-digit
frequencies do not approximate a Benford distribution. We have also suggested
a conceptual model to implement such a neutrosophic fraud detection system.
Original languageEnglish
Pages (from-to)7-14
Number of pages8
JournalInternational Journal of Applied Mathematics
Publication statusPublished - 2005

    Fingerprint

Cite this