A Comparative Analysis on the Relative Success of Mixed-Models for Financial Statement Fraud Risk Estimation
Loses which are caused by financial statement fraud (FSF) revealed the necessity of early warning system in fraud detection. In this context, many models have been improved. The level of success of these models on accurate estimation of financial statement fraud is proved by some empirical studies....
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Gaziantep University
2015-06-01
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| Series: | Gaziantep University Journal of Social Sciences |
| Subjects: | |
| Online Access: | http://dergipark.gov.tr/jss/issue/24224/256778?publisher=gantep |
| _version_ | 1797913154397667328 |
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| author | Mustafa UĞURLU Şerafettin SEVİM |
| author_facet | Mustafa UĞURLU Şerafettin SEVİM |
| author_sort | Mustafa UĞURLU |
| collection | DOAJ |
| description | Loses which are caused by financial statement fraud (FSF) revealed the necessity of early warning system in fraud detection. In this context, many models have been improved. The level of success of these models on accurate estimation of financial statement fraud is proved by some empirical studies. Success level of the models has been discussed in the literature. Main purpose of this study is to reveal relative success of the models which are used in order to estimate FSF by considering the findings in the literature. The findings of this study show that variables of estimation of FSF include variations and also there is not any consensus on this issue in the literature. Additionally, it is concluded that artificial neural network models are more successful than other models in estimation of FSF |
| first_indexed | 2024-04-10T12:07:24Z |
| format | Article |
| id | doaj.art-d4cf21f952b84ff0b99188e210bbef66 |
| institution | Directory Open Access Journal |
| issn | 2149-5459 |
| language | English |
| last_indexed | 2024-04-10T12:07:24Z |
| publishDate | 2015-06-01 |
| publisher | Gaziantep University |
| record_format | Article |
| series | Gaziantep University Journal of Social Sciences |
| spelling | doaj.art-d4cf21f952b84ff0b99188e210bbef662023-02-15T16:16:10ZengGaziantep UniversityGaziantep University Journal of Social Sciences2149-54592015-06-01141658810.21547/jss.256778136A Comparative Analysis on the Relative Success of Mixed-Models for Financial Statement Fraud Risk EstimationMustafa UĞURLU0Şerafettin SEVİM1Gaziantep ÜniversitesiDumlupınar ÜniversitesiLoses which are caused by financial statement fraud (FSF) revealed the necessity of early warning system in fraud detection. In this context, many models have been improved. The level of success of these models on accurate estimation of financial statement fraud is proved by some empirical studies. Success level of the models has been discussed in the literature. Main purpose of this study is to reveal relative success of the models which are used in order to estimate FSF by considering the findings in the literature. The findings of this study show that variables of estimation of FSF include variations and also there is not any consensus on this issue in the literature. Additionally, it is concluded that artificial neural network models are more successful than other models in estimation of FSFhttp://dergipark.gov.tr/jss/issue/24224/256778?publisher=gantepFinansal Tablo Hileleri Hile Riski Hile Riskinin Tahmini Yapay Sinir AğlarıFinancial Statement Fraud Fraud Risk Estimation of Fraud Risk Artificial Neural Network |
| spellingShingle | Mustafa UĞURLU Şerafettin SEVİM A Comparative Analysis on the Relative Success of Mixed-Models for Financial Statement Fraud Risk Estimation Gaziantep University Journal of Social Sciences Finansal Tablo Hileleri Hile Riski Hile Riskinin Tahmini Yapay Sinir Ağları Financial Statement Fraud Fraud Risk Estimation of Fraud Risk Artificial Neural Network |
| title | A Comparative Analysis on the Relative Success of Mixed-Models for Financial Statement Fraud Risk Estimation |
| title_full | A Comparative Analysis on the Relative Success of Mixed-Models for Financial Statement Fraud Risk Estimation |
| title_fullStr | A Comparative Analysis on the Relative Success of Mixed-Models for Financial Statement Fraud Risk Estimation |
| title_full_unstemmed | A Comparative Analysis on the Relative Success of Mixed-Models for Financial Statement Fraud Risk Estimation |
| title_short | A Comparative Analysis on the Relative Success of Mixed-Models for Financial Statement Fraud Risk Estimation |
| title_sort | comparative analysis on the relative success of mixed models for financial statement fraud risk estimation |
| topic | Finansal Tablo Hileleri Hile Riski Hile Riskinin Tahmini Yapay Sinir Ağları Financial Statement Fraud Fraud Risk Estimation of Fraud Risk Artificial Neural Network |
| url | http://dergipark.gov.tr/jss/issue/24224/256778?publisher=gantep |
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