Fuzzy Approaches Ability and their Performance Comparison to Fraud Detection in Financial Reporting

The possibility of fraud in the issued financial statements, and its negative impacts on financial markets and the resulting reduction of investment have caused responsible monitoring organizations to detect the frauds and to move seriously against them. This study aimed to investigate the ability o...

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Autores principales:	Abolghasem Massihabadi (Ph.D), Mohammad Sarchami
Formato:	article
Lenguaje:	FA
Publicado:	Shahid Bahonar University of Kerman 2018
Materias:	fuzzy approach fraud financial reporting financial ratio Accounting. Bookkeeping HF5601-5689
Acceso en línea:	https://doaj.org/article/9d85f0467cb24e73801ccefb300a3e5b
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spelling	oai:doaj.org-article:9d85f0467cb24e73801ccefb300a3e5b2021-11-04T19:53:28ZFuzzy Approaches Ability and their Performance Comparison to Fraud Detection in Financial Reporting2008-89142476-292X10.22103/jak.2017.9814.2319https://doaj.org/article/9d85f0467cb24e73801ccefb300a3e5b2018-01-01T00:00:00Zhttps://jak.uk.ac.ir/article_1865_8b0bf37cec1092950980590b8c1a9eca.pdfhttps://doaj.org/toc/2008-8914https://doaj.org/toc/2476-292XThe possibility of fraud in the issued financial statements, and its negative impacts on financial markets and the resulting reduction of investment have caused responsible monitoring organizations to detect the frauds and to move seriously against them. This study aimed to investigate the ability of the fuzzy approaches to fraud detection in financial reporting of the firms in the Tehran Stock Exchange. In this study, three hypotheses were considered. First, the Fuzzy decision tree classifier can detect fraud in financial reporting. Secondly, the Sugeno fuzzy classifier can detect fraud in financial reporting. Thirdly, there is a significant difference between the results of fuzzy decision tree classifier and Sugeno fuzzy classifier. These fuzzy approaches were programmed and used for testing the above hypotheses, using Matlab Software. The average accuracy of the Fuzzy decision tree classifier was 31/312, and of the Sugeno fuzzy classifier was 80/92. In other words, the first hypothesis was rejected and the second and third hypotheses were verified.Abolghasem Massihabadi (Ph.D)Mohammad SarchamiShahid Bahonar University of Kermanarticlefuzzy approachfraudfinancial reportingfinancial ratioAccounting. BookkeepingHF5601-5689FAمجله دانش حسابداری, Vol 8, Iss 4, Pp 161-190 (2018)
institution	DOAJ
collection	DOAJ
language	FA
topic	fuzzy approach fraud financial reporting financial ratio Accounting. Bookkeeping HF5601-5689
spellingShingle	fuzzy approach fraud financial reporting financial ratio Accounting. Bookkeeping HF5601-5689 Abolghasem Massihabadi (Ph.D) Mohammad Sarchami Fuzzy Approaches Ability and their Performance Comparison to Fraud Detection in Financial Reporting
description	The possibility of fraud in the issued financial statements, and its negative impacts on financial markets and the resulting reduction of investment have caused responsible monitoring organizations to detect the frauds and to move seriously against them. This study aimed to investigate the ability of the fuzzy approaches to fraud detection in financial reporting of the firms in the Tehran Stock Exchange. In this study, three hypotheses were considered. First, the Fuzzy decision tree classifier can detect fraud in financial reporting. Secondly, the Sugeno fuzzy classifier can detect fraud in financial reporting. Thirdly, there is a significant difference between the results of fuzzy decision tree classifier and Sugeno fuzzy classifier. These fuzzy approaches were programmed and used for testing the above hypotheses, using Matlab Software. The average accuracy of the Fuzzy decision tree classifier was 31/312, and of the Sugeno fuzzy classifier was 80/92. In other words, the first hypothesis was rejected and the second and third hypotheses were verified.
format	article
author	Abolghasem Massihabadi (Ph.D) Mohammad Sarchami
author_facet	Abolghasem Massihabadi (Ph.D) Mohammad Sarchami
author_sort	Abolghasem Massihabadi (Ph.D)
title	Fuzzy Approaches Ability and their Performance Comparison to Fraud Detection in Financial Reporting
title_short	Fuzzy Approaches Ability and their Performance Comparison to Fraud Detection in Financial Reporting
title_full	Fuzzy Approaches Ability and their Performance Comparison to Fraud Detection in Financial Reporting
title_fullStr	Fuzzy Approaches Ability and their Performance Comparison to Fraud Detection in Financial Reporting
title_full_unstemmed	Fuzzy Approaches Ability and their Performance Comparison to Fraud Detection in Financial Reporting
title_sort	fuzzy approaches ability and their performance comparison to fraud detection in financial reporting
publisher	Shahid Bahonar University of Kerman
publishDate	2018
url	https://doaj.org/article/9d85f0467cb24e73801ccefb300a3e5b
work_keys_str_mv	AT abolghasemmassihabadiphd fuzzyapproachesabilityandtheirperformancecomparisontofrauddetectioninfinancialreporting AT mohammadsarchami fuzzyapproachesabilityandtheirperformancecomparisontofrauddetectioninfinancialreporting
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Fuzzy Approaches Ability and their Performance Comparison to Fraud Detection in Financial Reporting

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