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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Penerbit Universiti Kebangsaan Malaysia
2016
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| Online Access: | http://journalarticle.ukm.my/10753/ http://journalarticle.ukm.my/10753/1/11847-43528-1-PB.pdf |
| _version_ | 1848812493486424064 |
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| author | Shabnam Fazli Aghghaleh, Zakiah Muhammaddun Mohamed, Mohd Mohid Rahmat, |
| author_facet | Shabnam Fazli Aghghaleh, Zakiah Muhammaddun Mohamed, Mohd Mohid Rahmat, |
| author_sort | Shabnam Fazli Aghghaleh, |
| building | UKM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T00:03:10Z |
| format | Article |
| id | oai:generic.eprints.org:10753 |
| institution | Universiti Kebangasaan Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T00:03:10Z |
| publishDate | 2016 |
| publisher | Penerbit Universiti Kebangsaan Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:generic.eprints.org: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 |
| spellingShingle | Shabnam Fazli Aghghaleh, Zakiah Muhammaddun Mohamed, Mohd Mohid Rahmat, Detecting financial statement frauds in Malaysia: comparing the abilities of Beneish and Dechow models |
| title | 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_short | 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 |
| url | http://journalarticle.ukm.my/10753/ http://journalarticle.ukm.my/10753/ http://journalarticle.ukm.my/10753/1/11847-43528-1-PB.pdf |