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ADLİ MUHASEBEDE HİLELERİN TESPİTİNDE YAPAY SİNİR AĞI MODELİNİN KULLANIMI

Year 2015, Issue: 14, 0 - , 20.04.2015
https://doi.org/10.18092/ijeas.86151

Abstract

Hile, finansal tablolarda yapılan kasti hatalardır. Hilede bir kişi ya da grubun yararına başka bir kişi/grubun zararına olan bir aldatma faaliyeti söz konusudur. Hileler, çalışan hileleri ve hileli finansal raporlama olarak iki grupta sınıflandırılabilir. Sertifikalı Hile Araştırmacıları Birliği’nin 2012 raporuna göre şirketler, finansal tablo hileleri yoluyla ortalama 1 milyon $’dan daha fazla finansal zararlara uğramakta-dır. Bundan dolayı adli muhasebe, davalarda hukuki destek verebilmek amacıyla finansal tablo hilelerinin tespitinde önemli bir rol oynamaktadır.
Bu çalışmanın amacı, adli muhasebede hilelerin tespitinde kullanılan yapay sinir ağı modelinin kullanımını göstermektir. Bu amaçla Borsa İstanbul’da ampirik bir araştırma yapılmıştır. Yapılan çalışmada oluşturulan yapay sinir ağı modelinin doğru sınıflandırma başarısı %100 olarak belirlenmiştir.

References

  • AKTAŞ, H., KULOĞLU, G. (2008). “Adli Muhasebe ve Adli Muhasebecilik Mesleği”, Muhasebe ve Denetime Bakış, 8(25), 101-120.
  • ALBRECHT, W. S., ALBRECHT, C., ALBRECHT, C.C. (2008), “Current Trends in Fraud and Its Detection”, Information Security Journal: A Global Perspective, 17 (2-12), 2-12.
  • ATA, H.A., SEYREK, İ.H. (2009), “The Use of Data Mining Techniques in Detecting Fraudulent Financial Statements: An Application on Manufacturing Firms”, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 14(2), 157-170.
  • ATMACA, M., TERZİ, S. (2012), Adli Muhasebe, 1.Baskı, İstanbul: Yaylım Yayıncılık.
  • BHASIN, M. (2007), “Forensic Accounting: A New Paradigm for Niche Consulting”, Accounting and Auditing, January, 1000-1010. http://www.icai.org/resource_file/97231000-1010.pdf (Erişim Tarihi:14.04.2012)
  • BOZKURT, N. (2000). “Muhasebe ve Denetim Mesleğinde Yeni Bir Alan: Adli Muhasebecilik”, Yaklaşım Dergisi, 94, 56-61.
  • CERULLO, M. J., CERULLO, M. V. (2006), “Using Neural Network Soft-ware As A Forensic Accounting Tool”, ISACA Journal, 2, 1-5. http://www.isaca.org/Journal/Past-Issues/2006/Volume-2/Pages/Using-Neural-Network-Software-as-a-Forensic-Accounting-Tool1.aspx (Erişim Tarihi: 14.02.201)
  • CHRISTENSEN, J.A., BYINGTON, J.R., BLALOCK, T.J. (2005), “Sarbanes-Oxley: Will You Need A Forensic Accountant?”, Journal of Corporate Accounting & Finance, March-April, 16(3), 69-75. CRUMBLEY, D.L., APOSTOLOU, N. (2002), “Forensic Accounting: A New Growth Area in Accounting”, The Ohio CPA Journal, 61(3), 16-20. Crumbley, D. Larry, (2001), “Forensic Accounting: Older Than You Think”, Journal of Forensic Accounting, .2, 181-202. COAKLEY, J.R., BROWN, C.E. (2000), “Artificial Neural Networks in Accounting and Finance: Modeling Issues”, International Journal of Intelligent Systems in Accounting, Finance & Management, 9(2), 119-144. ÇELİK, M.K. (2010), “Bankaların Finansal Başarısızlıklarının Geleneksel ve Yeni Yöntemlerle Öngörüsü”, Yönetim ve Ekonomi Dergisi, 17(2), 129-143.
  • FANNING, K.M., COGGER, K.O. (1998), “Neural Network Detection of Management Fraud Using Published Financial Data”, International Journal of Intelligent Systems in Accounting, Finance & Management, 7(1), 21-41.
  • GAGANIS, C. (2009), “Classification Techniques for the Identification of Falsified Financial Statements: A Comparative Analysis”, Intelligent Systems In Accounting, Finance and Management, 16(3), 207-229.
  • KASUM, A.S.B. (2009), “The Relevance of Forensic Accounting to Financial Crimes in Private and Public Sectors of Third World Economies: A Study From Nigeria”, Proceedings of The 1st International Conference on Governance Fraud Ethics and Social Responsibility, June 11-13, 2009, Trakya Üniversitesi, Türkiye, http://www.unilorin.edu.ng/publications/kasumas/Forensic%20Accounting %20pdf.pdf (Erişim Tarihi: 02.04.2012)
  • KIRKOS, E., SPATHİS, C., MANOLOPOULOS, Y. (2007), “Data Mining Techniques for the Detection of Fraudulent Financial Statements”, Expert Systems with Applications, 32, 995-1003.
  • KIYMETLİ ŞEN, İ., TERZİ, S. (2012), “Detecting Falsified Financial Statements Using Data Mining: Emprical Research on Finance Sector in Turkey”, Maliye Finans Yazıları Dergisi, 26(96): 67-82.
  • KRSTIĆ, J. (2009), “The Role of Forensic Accountants in Detecting Frauds in Financial Statements”, Economics and Organization, 6(3), 295-302.
  • KÜÇÜKKOCAOĞLU, G., BENLİ, Y.K., KÜÇÜKSÖZEN, C. (2007), “Fi-nansal Bilgi Manipülasyonunun Tespitinde Yapay Sinir Ağı Modelinin Kullanımı”, İMKB Dergisi, 9(36), 1-30.
  • LIOU, F.M. (2008), “Fraudulent Financial Reporting Detection and Business Failure Prediction Models: A Comparison”, Managerial Auditing Journal, 23(7), 650-662.
  • MEIER, H.H., KAMATH, R.R., HE, Y. (2010), “Courses on Forensics and Fraud Examination in the Accounting Curriculum”, Journal of Leadership, Accountability and Ethics,8(1), 25-33.
  • MCKITTRICK, C. (2009), “Forensic Accounting - It’s Broader Than You Might Think and İt Can Help Your Organization”, Forensic Accounting, 1, 1-3.
  • OBERHOLZER, C. (2002), “Quality Management in Forensic Accounting”, The Gordon Institute of Business Science, University of Pretoria, The Degree of Master of Business Administration.
  • PANIGRAHI, P.K. (2006), “Discovering Fraud in Forensic Accounting Using Data Mining Techniques”, The Chartered Accountant, 1426-1430. http://220.227.161.86/102541426-1430.pdf (Erişim Tarihi: 14.04.2012)
  • PAZARÇEVİREN, S.Y. (2005), “Adli Muhasebecilik Mesleği”, ZKÜ Sosyal Bilimler Dergisi, 1(2), 1-19.
  • PEARSON, T.A., SİNGLETON, T.W. (2008), “Fraud and Forensic Accounting in the Digital Environment”, Issues in Accounting Education, 23(4), 545-559.
  • RAVISANKAR, P., RAVI, V., RAO, G.R., BOSE, I. (2011), “Detection of Financial Statement Fraud and Feature Selection using Data Mining Techniques”, Decision Support Systems, 50(2), 491-500.
  • RENZHOU, D. (2011), “Research on Legal Procedural Functions Of Forensic Accounting”, Energy Procedia, 5, 2147-2151.
  • VARICI, İ. (2012), “Hileli Finansal Raporlama Açısından Denetçinin Sorumluluğu: İMKB’de Faaliyet Gösteren İşletmelerin Denetim Raporlarının İncelenme-si”, Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü, 3(5), 122-144.
  • SPATHIS, C.T. (2002), “Detecting false Financial Statements Using Pub-lished Data: Some Evidence from Greece”, Managerial Auditing Journal, 17(4), 179-191.
  • TERZİ, S., KASAP, M. (2007), “Hile Denetiminde Benford Yasasının Kul-lanımı”, Dayanışma Dergisi, 100, 117-125.
  • TERZİ, S. (2012a), “Detection of Fraudulent Financial Statements Through the Use of Publicly Available Data: A Research on Manufacturing Companies”, Muhasebe Bilim Dünyası Dergisi, 14(4): 175-191.
  • TERZİ, S. (2012b), Hileli Finansal Raporlama: Önleme ve Tespit, 1.Baskı, İstanbul: Beta Yayıncılık.

-

Year 2015, Issue: 14, 0 - , 20.04.2015
https://doi.org/10.18092/ijeas.86151

Abstract

Fraud is an intentional action in the financial statements. Fraud can be defined as an act of deception where an individual or a group obtains benefits in return for damaging another individual or group. Frauds can be classified as employee fraud and the fraudulent financial reporting. According to the 2012 report of Association of Certified Fraud Examiners, companies lose averagely more than 1 million dollars due to financial statement fraud. Therefore, forensic accounting has an important role in determining financial statemet frauds in order to provide legal support in lawsuits

References

  • AKTAŞ, H., KULOĞLU, G. (2008). “Adli Muhasebe ve Adli Muhasebecilik Mesleği”, Muhasebe ve Denetime Bakış, 8(25), 101-120.
  • ALBRECHT, W. S., ALBRECHT, C., ALBRECHT, C.C. (2008), “Current Trends in Fraud and Its Detection”, Information Security Journal: A Global Perspective, 17 (2-12), 2-12.
  • ATA, H.A., SEYREK, İ.H. (2009), “The Use of Data Mining Techniques in Detecting Fraudulent Financial Statements: An Application on Manufacturing Firms”, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 14(2), 157-170.
  • ATMACA, M., TERZİ, S. (2012), Adli Muhasebe, 1.Baskı, İstanbul: Yaylım Yayıncılık.
  • BHASIN, M. (2007), “Forensic Accounting: A New Paradigm for Niche Consulting”, Accounting and Auditing, January, 1000-1010. http://www.icai.org/resource_file/97231000-1010.pdf (Erişim Tarihi:14.04.2012)
  • BOZKURT, N. (2000). “Muhasebe ve Denetim Mesleğinde Yeni Bir Alan: Adli Muhasebecilik”, Yaklaşım Dergisi, 94, 56-61.
  • CERULLO, M. J., CERULLO, M. V. (2006), “Using Neural Network Soft-ware As A Forensic Accounting Tool”, ISACA Journal, 2, 1-5. http://www.isaca.org/Journal/Past-Issues/2006/Volume-2/Pages/Using-Neural-Network-Software-as-a-Forensic-Accounting-Tool1.aspx (Erişim Tarihi: 14.02.201)
  • CHRISTENSEN, J.A., BYINGTON, J.R., BLALOCK, T.J. (2005), “Sarbanes-Oxley: Will You Need A Forensic Accountant?”, Journal of Corporate Accounting & Finance, March-April, 16(3), 69-75. CRUMBLEY, D.L., APOSTOLOU, N. (2002), “Forensic Accounting: A New Growth Area in Accounting”, The Ohio CPA Journal, 61(3), 16-20. Crumbley, D. Larry, (2001), “Forensic Accounting: Older Than You Think”, Journal of Forensic Accounting, .2, 181-202. COAKLEY, J.R., BROWN, C.E. (2000), “Artificial Neural Networks in Accounting and Finance: Modeling Issues”, International Journal of Intelligent Systems in Accounting, Finance & Management, 9(2), 119-144. ÇELİK, M.K. (2010), “Bankaların Finansal Başarısızlıklarının Geleneksel ve Yeni Yöntemlerle Öngörüsü”, Yönetim ve Ekonomi Dergisi, 17(2), 129-143.
  • FANNING, K.M., COGGER, K.O. (1998), “Neural Network Detection of Management Fraud Using Published Financial Data”, International Journal of Intelligent Systems in Accounting, Finance & Management, 7(1), 21-41.
  • GAGANIS, C. (2009), “Classification Techniques for the Identification of Falsified Financial Statements: A Comparative Analysis”, Intelligent Systems In Accounting, Finance and Management, 16(3), 207-229.
  • KASUM, A.S.B. (2009), “The Relevance of Forensic Accounting to Financial Crimes in Private and Public Sectors of Third World Economies: A Study From Nigeria”, Proceedings of The 1st International Conference on Governance Fraud Ethics and Social Responsibility, June 11-13, 2009, Trakya Üniversitesi, Türkiye, http://www.unilorin.edu.ng/publications/kasumas/Forensic%20Accounting %20pdf.pdf (Erişim Tarihi: 02.04.2012)
  • KIRKOS, E., SPATHİS, C., MANOLOPOULOS, Y. (2007), “Data Mining Techniques for the Detection of Fraudulent Financial Statements”, Expert Systems with Applications, 32, 995-1003.
  • KIYMETLİ ŞEN, İ., TERZİ, S. (2012), “Detecting Falsified Financial Statements Using Data Mining: Emprical Research on Finance Sector in Turkey”, Maliye Finans Yazıları Dergisi, 26(96): 67-82.
  • KRSTIĆ, J. (2009), “The Role of Forensic Accountants in Detecting Frauds in Financial Statements”, Economics and Organization, 6(3), 295-302.
  • KÜÇÜKKOCAOĞLU, G., BENLİ, Y.K., KÜÇÜKSÖZEN, C. (2007), “Fi-nansal Bilgi Manipülasyonunun Tespitinde Yapay Sinir Ağı Modelinin Kullanımı”, İMKB Dergisi, 9(36), 1-30.
  • LIOU, F.M. (2008), “Fraudulent Financial Reporting Detection and Business Failure Prediction Models: A Comparison”, Managerial Auditing Journal, 23(7), 650-662.
  • MEIER, H.H., KAMATH, R.R., HE, Y. (2010), “Courses on Forensics and Fraud Examination in the Accounting Curriculum”, Journal of Leadership, Accountability and Ethics,8(1), 25-33.
  • MCKITTRICK, C. (2009), “Forensic Accounting - It’s Broader Than You Might Think and İt Can Help Your Organization”, Forensic Accounting, 1, 1-3.
  • OBERHOLZER, C. (2002), “Quality Management in Forensic Accounting”, The Gordon Institute of Business Science, University of Pretoria, The Degree of Master of Business Administration.
  • PANIGRAHI, P.K. (2006), “Discovering Fraud in Forensic Accounting Using Data Mining Techniques”, The Chartered Accountant, 1426-1430. http://220.227.161.86/102541426-1430.pdf (Erişim Tarihi: 14.04.2012)
  • PAZARÇEVİREN, S.Y. (2005), “Adli Muhasebecilik Mesleği”, ZKÜ Sosyal Bilimler Dergisi, 1(2), 1-19.
  • PEARSON, T.A., SİNGLETON, T.W. (2008), “Fraud and Forensic Accounting in the Digital Environment”, Issues in Accounting Education, 23(4), 545-559.
  • RAVISANKAR, P., RAVI, V., RAO, G.R., BOSE, I. (2011), “Detection of Financial Statement Fraud and Feature Selection using Data Mining Techniques”, Decision Support Systems, 50(2), 491-500.
  • RENZHOU, D. (2011), “Research on Legal Procedural Functions Of Forensic Accounting”, Energy Procedia, 5, 2147-2151.
  • VARICI, İ. (2012), “Hileli Finansal Raporlama Açısından Denetçinin Sorumluluğu: İMKB’de Faaliyet Gösteren İşletmelerin Denetim Raporlarının İncelenme-si”, Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü, 3(5), 122-144.
  • SPATHIS, C.T. (2002), “Detecting false Financial Statements Using Pub-lished Data: Some Evidence from Greece”, Managerial Auditing Journal, 17(4), 179-191.
  • TERZİ, S., KASAP, M. (2007), “Hile Denetiminde Benford Yasasının Kul-lanımı”, Dayanışma Dergisi, 100, 117-125.
  • TERZİ, S. (2012a), “Detection of Fraudulent Financial Statements Through the Use of Publicly Available Data: A Research on Manufacturing Companies”, Muhasebe Bilim Dünyası Dergisi, 14(4): 175-191.
  • TERZİ, S. (2012b), Hileli Finansal Raporlama: Önleme ve Tespit, 1.Baskı, İstanbul: Beta Yayıncılık.
There are 29 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Serkan Terzi This is me

İlker Kıymetli Şen This is me

Publication Date April 20, 2015
Published in Issue Year 2015 Issue: 14

Cite

APA Terzi, S., & Kıymetli Şen, İ. (2015). ADLİ MUHASEBEDE HİLELERİN TESPİTİNDE YAPAY SİNİR AĞI MODELİNİN KULLANIMI. Uluslararası İktisadi Ve İdari İncelemeler Dergisi(14). https://doi.org/10.18092/ijeas.86151

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Address: Karadeniz Technical University Department of Economics Room Number 213  

61080 Trabzon / Turkey

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