Araştırma Makalesi
BibTex RIS Kaynak Göster

YAPAY ZEKA ALGORİTMALARI İLE DÖNÜŞÜM GEÇİRECEK DENETİM MESLEĞİNİN GELECEĞİ ÜZERİNDE BİR DEĞERLENDİRME

Yıl 2022, Cilt: 8 Sayı: 2, 1 - 19, 08.03.2023

Öz

Yapay zekâ (YZ) uygulamalarıyla birlikte gelişen yenilikçi teknolojiler nedeniyle Sayıştay ve teftiş mekanizmaları dahil olmak üzere tüm iç ve dış denetim mesleğinin bir bütün olarak elde ettiği birtakım kolaylıklarla birlikte bazı zorluklar ile de karşı karşıya kalmaktadır. Veri analitiğini kullanmak da dahil olmak üzere sürekli hale gelen denetim süreçlerinde teknolojiden yararlanmada daha etkin ve verimli uygulamalara ihtiyaç vardır. Aslında, yıkıcı yeniliklerden bu durum zamanla bir zorunluluk hale gelebilecekken birçok iç/dış denetim departmanı iyi BT denetçileri bulmakta zorlandıklarını kabul etmektedirler. Büyük veriden dolayı yavaş işleyen denetim, örneklemeye dayalı denetim planlaması ve anahtar kelime aramalarına güvenme, denetim görevlerini hızlandırmak için akıllı otomasyonun gerekli olduğunun birer göstergeleridir. Bu çalışmada YZ tabanlı denetim otomasyon uygulamalarının denetçinin yerine geçerek değil, aslında insan merkezli denetim planlama, programlama, yürütme, test, raporlama ve izleme süreçlerine değer katarak sürecine yardımcı olunduğu ortaya konulmaktadır. Bu husustaki makul çözümler, genelde tüm denetim meslekleri ve özelde ise iç denetim süreçlerini daha akıllı, hızlı ve etkin hale getirebilen YZ modellerinin benimsenmesini içerir. Bunun için de kurumsal süreçlerin yeniden yapılandırılması, yerli ve milli ürün ve standartların geliştirilmesi ve teknik insan kaynağı yetkinliğinin yükseltilmesi bağlamında hazırlıkların yapılması gerekmektedir.

Kaynakça

  • Alina, C.M., Cerasela, S.E., Gabriela, G., et al. (2018) Internal audit role in artificial intelligence. Ovidius University Annals, Economic Sciences Series 18(1) 441–445
  • Appelbaum, D.A., Kogan, A., Vasarhelyi, M.A. (2018) Analytical procedures in external auditing: A comprehensive literature survey and framework for external audit analytics. Journal of Accounting Literature 40 83–101
  • Bhattacharya, U., Rahut, A., De, S. (2013) Audit maturity model. Computer Science Information Technology 4 (12)
  • Blackline (2019) Mistrust In The Numbers, BlackLine Study into the Potential Global Scale of Financial Data Inaccuracies, https://www.blackline.com/assets/docs/uploads/ Mistrust_in_the_Numbers_Feb_2019.pdf
  • Bao, Y. and Hilary, G. and Ke, B. (2020). Artificial Intelligence and Fraud Detection, Babich V, Birge J, Hilary G (eds) Innovative Technology at the interface of Finance and Operations. Springer Series in Supply Chain Management, forthcoming, Springer Nature, Available at SSRN: https://ssrn.com/abstract=3738618
  • Brennan B, Baccala M., Flynn M., (2017) “Artificial Intelligence Comes to Financial Statement Audits,” CFO.com, Feb. 2, http://bit.ly/2Jx3CYO).
  • Celayir, D. & Celayir, Ç. (2020). Dijitalleşmenin denetim mesleğine yansımaları. Avrasya Sosyal ve Ekonomi Araştırmaları Dergisi, 7 (6), 128-148. Retrieved from https://dergipark.org.tr/tr/pub/asead/issue/55211/742693
  • CFR, (1996), United States Public Law: Quality System Regulation. 21 CFR part 820
  • CFR, (2011) United States Public Law: Prospectus summary, risk factors, and ratio of earnings to fixed charges (Item 503). 17 CFR part 229.503
  • Cowle, E., Rowe, S.P. (2019) Don’t make me look bad: How the audit market penalizes auditors for doing their job. (September) Available at SSRN: https://ssrn.com/abstract=3228321
  • Dotel, RP, (2020) Artificial Intelligence: Preparing For The Future Of Audit, INTOSAI Journal, http://intosaijournal.org/artificial-intelligence-preparing-for-the-future-of-audit/
  • Dönerçark, M. & Tecim, V. (2020). Kurumsal Karar Destek Sistemlerinde Yapay Zekâ Kullanımı: Tasarım Ve Uygulama. Yönetim Bilişim Sistemleri Dergisi, 6 (2), 77-103. Retrieved from https://dergipark.org.tr/tr/pub/ybs/issue/58550/821708
  • Eulerich, M., Masli, A. (2019) The use of technology-based audit techniques in the internal audit function–is there an improvement in efficiency and effectiveness? Available at SSRN 3444119
  • Fathi, E., (2020) AI in finance: Helping professionals shift from hindsight to insight to foresight, MindBridge, https://www.mindbridge.ai/blog/ai-finance-professional-insight/
  • Fay R., Montague N. R., (2015) “I’m Not Biased, Am I?” Journal of Accountancy, Feb. 1, http://bit.ly/2JBjM3f
  • Goodwin, S. (1996) Data rich, information poor (drip) syndrome: is there a treatment? Radiology management 18(3) 45–49
  • Gunderson, C., (2019) Artificial Intelligence and Machine Learning, https://www.protiviti.com/sites/default/files/united_states/insights/ai-ml-global-study-protiviti.pdf
  • Hashimoto, K., (2020) What to expect from audit software in 2021 to 2022, MindBridge, https://www.mindbridge.ai/blog/audit-software-2021-2022-trends/
  • Huang, M.-H., & Rust, R. T. (2018). Artificial Intelligence in Service. Journal of Service Research, 21(2), 155–172. https://doi.org/10.1177/1094670517752459
  • IIA, (2017). The Institute of Internal Auditors, International Standards for the Professional Practice of Internal Auditing (Standards)
  • Issa H., Sun T., Vasarhelyi M., (2016) “Research Ideas for Artificial Intelligence in Auditing, The Formalization of Audit and Workforce Supplementation,” Journal of Emerging Technologies in Accounting, Fall, http://bit.ly/2VVIF0j
  • Jiang F, Jiang Y, Zhi H, et al. (2017) Artificial intelligence in healthcare: past, present and futureStroke and Vascular Neurology;2: doi: 10.1136/svn-2017-000101
  • Jorgensen, B.N., Kirschenheiter, M.T. (2003) Discretionary risk disclosures. The Accounting Review 78(2) 449–469
  • Joshi N., (2019) “Robotic Process Automation Just Got ‘Intelligent’ Thanks to Machine Learning,” Forbes, Jan, 29,http://bit.ly/2JLadPh
  • Kandemir, Ş. (2021). Bankacılık ve Finansın Denetiminde Denetim Teknolojisi (SupTech)ve Yapay Zekâ . Çağ Üniversitesi Sosyal Bilimler Dergisi , 18 (1) , 59-81 . Retrieved from https://dergipark.org.tr/tr/pub/cagsbd/issue/63182/959751
  • Kahyaoglu S.B., Aksoy T. (2021) Artificial Intelligence in Internal Audit and Risk Assessment. In: Hacioglu U., Aksoy T. (eds) Financial Ecosystem and Strategy in the Digital Era. Contributions to Finance and Accounting. Springer, Cham. https://doi.org/10.1007/978-3-030-72624-9_8
  • Kepes B., (2016) “Big Four Accounting Firms Delve into Artificial Intelligence,” Computerworld, Mar. 16, http://bit.ly/30jYmxo
  • Kokina, J., Davenport, T.H. (2017) The emergence of artificial intelligence: How automation is changing auditing. Journal of Emerging Technologies in Accounting 14(1) 115–122
  • Kravet, T., Muslu, V. (2013) Textual risk disclosures and investors’ risk perceptions. Review of Accounting Studies 18(4) 1088–1122
  • Kuenkaikaew, S., Vasarhelyi, M.A. (2013) The predictive audit framework. The International Journal of Digital Accounting Research 13(19) 37–71
  • Mogg T., (2019) “McDonald’s to Use AI to Tempt You into Extra Purchases at the Drive-thru,” DigitalTrends.com, Mar. 26,http://bit.ly/2w43BDF
  • Newmark R., Dickey G., and Wilcox W., (2018) “Agility in Audit: Could Scrum Improve the Audit Process?” Current Issues in Auditing, Spring, http://bit.ly/2HlcnUt
  • Nithiyuwith, T., & Treenuntharath, T. (2020). The Development of Thai Artificial Intelligence Chatbot For Supporting Academic Consultancy For Tertiary Students. Life Sciences and Environment Journal, 21(2), 453-467. Retrieved from https://ph01.tci-thaijo.org/index.php/psru/article/view/242312
  • Puhan S., Panda D. and Mishra B. K., (2020) Energy Efficiency for Cloud Computing Applications: A Survey on the Recent Trends and Future Scopes, 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA), pp. 1-6, doi: 10.1109/ICCSEA49143.2020.9132878.
  • Sapphiro, D., (2020) Artificial Intelligence for Internal Audit and Risk Management Dragging Assessments Into the Modern Era, Towards Data Science, https://towardsdatascience.com/artificial-intelligence-for-internal-audit-and-risk-management-94e509129d49#2402
  • Schrand, C.M., Elliott, J.A. (1998) Risk and financial reporting: A summary of the discussion at the 1997 aaa/fasb conference. Accounting Horizons 12(3) 271
  • Seethamraju, R. C. and Hecimovic, A., (2020). Impact of Artificial Intelligence on Auditing - An Exploratory Study" AMCIS 2020 Proceedings. 8. https://aisel.aisnet.org/amcis2020/accounting_info_systems/accounting_info_systems/8
  • Serçemeli, M , Orhan, M . (2016) Sürekli Denetim ve Denetimin Geleceğine Bakiş Üzerine Bist-100 Şirketlerinde Bir Araştirma. Sayıştay Dergisi, (101), 31-50. https://dergipark.org.tr/tr/pub/sayistay/issue/61557/919191
  • Softwareworld, (2021) Top Audit Management Software of 2021, https://www.softwareworld.co/ best-audit-management-software/
  • Solaimani, R., Mohammed, S., Rashed, F., Elkelish, W., (2020) The Impact of Artificial Intelligence on Corporate Control. Corporate Ownership & Control, 17(3), 171-178., Available at SSRN: https://ssrn.com/abstract=3576777
  • Struthers-Kennedy, A., (2019) Protivity- 2019 IT Audit Benchmarking Study, https://www.protiviti.com/US-en/insights/it-audit-benchmarking-survey
  • Struthers-Kennedy A., Nesgood K., (2020) Artificial Intelligence and Internal Audit: A Pragmatic Perspective, Protivity, https://blog.protiviti.com/2020/01/02/artificial-intelligence-and-internal-audit-a-pragmatic-perspective/
  • Sun T. Vasarhelyi M. (2017) “Deep Learning and the Future of Auditing: How an Evolving Technology Could Transform Analysis and Improve Judgment,” CPA Journal, June, http://bit.ly/2VYCI2r
  • Sun, T., Vasarhelyi, M.A., et al. (2018) Embracing textual data analytics in auditing with deep learning. Universidad de Huelva.
  • Sutton S., Holt M., Arnold V., (2016) “The Reports of My Death Are Greatly Exaggerated: Artificial Intelligence Research in Accounting,” International Journal of Accounting Information Systems, September, http://bit.ly/2JCgnBu
  • Thabit, T. (2019) Determining the effectiveness of internal controls in enterprise risk management based on COSO recommendations. In: International Conference on Accounting, Business Economics and Politics.
  • Vasarhelyi M. and Rozario A., (2018) “How Robotic Process Automation Is Transforming Accounting and Auditing,” CPA Journal, June, https://bit.ly/2F7t5aE
  • Wang, Z. (2021). Abnormal Financial Transaction Detection via AI Technology. International Journal of Distributed Systems and Technologies (IJDST), 12(2), 24-34. http://doi.org/10.4018/IJDST.2021040103
  • Wyatt, J., (2019), The Next Generation of Internal Auditing- Are you ready? https://www.protiviti.com/sites/default/files/united_states/insights/next-generation-internal-audit.pdf
  • Yoon K., (2016) Three Essays on Unorthodox Audit Evidence, doctoral dissertation, Rutgers University, https://bit.ly/2VmN4VJ
Toplam 50 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Ahmet Efe 0000-0002-2691-7517

Erken Görünüm Tarihi 8 Mart 2023
Yayımlanma Tarihi 8 Mart 2023
Yayımlandığı Sayı Yıl 2022 Cilt: 8 Sayı: 2

Kaynak Göster

APA Efe, A. (2023). YAPAY ZEKA ALGORİTMALARI İLE DÖNÜŞÜM GEÇİRECEK DENETİM MESLEĞİNİN GELECEĞİ ÜZERİNDE BİR DEĞERLENDİRME. Yönetim Bilişim Sistemleri Dergisi, 8(2), 1-19.