Detecting financial statement frauds in Malaysia: comparing the abilities of Beneish and Dechow models

Financial statement frauds (FSF) are becoming rampant phenomena in current economic and financial landscapes. One of the ways to curb FSF is to detect them early so that preventive measures can be applied. This study aims to empirically investigate the abilities of two financial-based models namel...

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Main Authors:	Shabnam Fazli Aghghaleh, Zakiah Muhammaddun Mohamed, Mohd Mohid Rahmat
Format:	Article
Language:	English
Published:	Penerbit Universiti Kebangsaan Malaysia 2016
Online Access:	http://journalarticle.ukm.my/10753/ http://journalarticle.ukm.my/10753/ http://journalarticle.ukm.my/10753/1/11847-43528-1-PB.pdf

id	ukm-10753
recordtype	eprints
spelling	ukm-107532017-10-09T09:27:09Z http://journalarticle.ukm.my/10753/ Detecting financial statement frauds in Malaysia: comparing the abilities of Beneish and Dechow models Shabnam Fazli Aghghaleh, Zakiah Muhammaddun Mohamed, Mohd Mohid Rahmat, Financial statement frauds (FSF) are becoming rampant phenomena in current economic and financial landscapes. One of the ways to curb FSF is to detect them early so that preventive measures can be applied. This study aims to empirically investigate the abilities of two financial-based models namely the Beneish’s M-score and Dechow’s F-score, to detect and predict FSF for Malaysian companies. In addition, this study compares the accuracy including the error rates between the two models. Financial data of Malaysian listed companies from 2001 to 2014 are used using a matched pair in this study. The findings reveal that both Beneish and Dechow models are effective in predicting both the fraudulent and non-fraudulent companies with average accuracy at 73.17% and 76.22%, respectively. The results also indicate that Dechow F-score model outperforms the Beneish M-score model in the sensitivity of predicting fraud cases with 73.17% compared to 69.51%. On the efficiency aspect, the Dechow F Score model is found to have lower type II error (26.83%) than Beneish M Score model (30.49%). This finding suggests that Dechow F Score model is a better model that can be used by the regulators to detect FSF among companies in Malaysia. Penerbit Universiti Kebangsaan Malaysia 2016 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/10753/1/11847-43528-1-PB.pdf Shabnam Fazli Aghghaleh, and Zakiah Muhammaddun Mohamed, and Mohd Mohid Rahmat, (2016) Detecting financial statement frauds in Malaysia: comparing the abilities of Beneish and Dechow models. Asian Journal of Accounting and Governance, 7 . pp. 57-65. ISSN 2180-3838 http://ejournal.ukm.my/ajac/issue/view/868/showToc
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	Financial statement frauds (FSF) are becoming rampant phenomena in current economic and financial landscapes. One of the ways to curb FSF is to detect them early so that preventive measures can be applied. This study aims to empirically investigate the abilities of two financial-based models namely the Beneish’s M-score and Dechow’s F-score, to detect and predict FSF for Malaysian companies. In addition, this study compares the accuracy including the error rates between the two models. Financial data of Malaysian listed companies from 2001 to 2014 are used using a matched pair in this study. The findings reveal that both Beneish and Dechow models are effective in predicting both the fraudulent and non-fraudulent companies with average accuracy at 73.17% and 76.22%, respectively. The results also indicate that Dechow F-score model outperforms the Beneish M-score model in the sensitivity of predicting fraud cases with 73.17% compared to 69.51%. On the efficiency aspect, the Dechow F Score model is found to have lower type II error (26.83%) than Beneish M Score model (30.49%). This finding suggests that Dechow F Score model is a better model that can be used by the regulators to detect FSF among companies in Malaysia.
format	Article
author	Shabnam Fazli Aghghaleh, Zakiah Muhammaddun Mohamed, Mohd Mohid Rahmat,
spellingShingle	Shabnam Fazli Aghghaleh, Zakiah Muhammaddun Mohamed, Mohd Mohid Rahmat, Detecting financial statement frauds in Malaysia: comparing the abilities of Beneish and Dechow models
author_facet	Shabnam Fazli Aghghaleh, Zakiah Muhammaddun Mohamed, Mohd Mohid Rahmat,
author_sort	Shabnam Fazli Aghghaleh,
title	Detecting financial statement frauds in Malaysia: comparing the abilities of Beneish and Dechow models
title_short	Detecting financial statement frauds in Malaysia: comparing the abilities of Beneish and Dechow models
title_full	Detecting financial statement frauds in Malaysia: comparing the abilities of Beneish and Dechow models
title_fullStr	Detecting financial statement frauds in Malaysia: comparing the abilities of Beneish and Dechow models
title_full_unstemmed	Detecting financial statement frauds in Malaysia: comparing the abilities of Beneish and Dechow models
title_sort	detecting financial statement frauds in malaysia: comparing the abilities of beneish and dechow models
publisher	Penerbit Universiti Kebangsaan Malaysia
publishDate	2016
url	http://journalarticle.ukm.my/10753/ http://journalarticle.ukm.my/10753/ http://journalarticle.ukm.my/10753/1/11847-43528-1-PB.pdf
first_indexed	2023-09-18T19:58:21Z
last_indexed	2023-09-18T19:58:21Z
_version_	1777406681436651520

Detecting financial statement frauds in Malaysia: comparing the abilities of Beneish and Dechow models

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