Journal of Theoretical and Applied Information Technology 100(14), pp. 5300-5305 .
ISSN/ISBN: Not available at this time. DOI: Not available at this time.
Abstract: Currently, fraud related to financial statement fraud is increasingly happening. The parties who are harmed are investors and creditors who make decisions based on the financial statements. Benford's Law is here as one of the tools to detect fraudulent financial statements. Benford's law is the study of the frequency of the principal digits contained in numerical data. It is also commonly used in predicting the occurrence of numbers in numerical data, including auditing financial statements. When an Auditor chooses a method of detecting fraud / material misstatement of data, he should first consider which types of accounts that may be analyzed by the Benford method are expected to be effective or not, While most of the accounting data sets related to the Benford distribution are in accordance with the Benford distribution because digital analysis is only effective when applied to the appropriate data set. Auditors need to consider in advance the expectations for the use of the Benford method distribution before conducting digital analysis. The purpose of this study is that we want to demonstrate the effectiveness of the Benford Law method in assisting the auditing process. Our research result show that Benford Law method is still effective in helping auditors detect fraud. It can be seen from the results that we get we can assess the size of the anomaly, the risk of fraud, and changes in deviation so that it gives rise to indications of fraud in Total Assets, Total Liability, and Total Equity by using the Benford Law method, namely First Digit Test, First Two-Digit Test, and Chi-Square Test.
Bibtex:
@article{,
author = {Aryanti Wardaya Pupokusumo and Bambang Leo Handoko and Willy and Ricky and 5edwin Hendra},
title = {Benford’s Law as a Tool in Detecting Financial Statement Fraud},
year = {2022},
journal = {Journal of Theoretical and Applied Information Technology},
volume = {100},
number = {14},
pages = {5300--5305},
url = {http://www.jatit.org/volumes/Vol100No14/23Vol100No14.pdf},
}
Reference Type: Journal Article
Subject Area(s): Accounting