The Impact of Artificial Intelligence, Blockchain and Other New Technologies on Detecting Fraudulent Financial Reporting: A Qualitative Analysis

Öz

Technological developments are radically transforming many areas, including independent auditing. Technologies such as blockchain, machine learning, robotic process automation and artificial intelligence are among the prominent tools in this transformation. This study aims to examine the effects of developing technologies (blockchain, robotic process automation, machine learning, and artificial intelligence) on independent auditing processes and the detection of fraudulent financial reporting. In accordance with the qualitative research design, semi-structured interviews were conducted with 10 independent auditing experts in Türkiye and the obtained data were analyzed using MAXQDA 2024 Pro software. The findings show that blockchain technology can enable the transition from retrospective auditing to continuous auditing; robotic process automation can increase audit efficiency by reducing repetitive processes; and artificial intelligence applications can increase quality by reducing audit time and cost. This study contributes to the literature by providing a qualitative framework on how the independent auditing profession is reshaped in the digital transformation process.

Anahtar Kelimeler

• Fraudulent Financial Reporting
• Blockchain
• Machine Learning
• Robotic Process Automation
• Artificial Intelligence

Yapay Zekâ, Blok Zinciri ve Diğer Yeni Teknolojilerin Hileli Finansal Raporlamanın Tespitine Etkisi: Nitel Bir Analiz

Öz

Teknolojik gelişmeler, bağımsız denetim de dâhil olmak üzere birçok alanı köklü biçimde dönüştürmektedir. Blok zinciri, makine öğrenimi, robotik süreç otomasyonu ve yapay zekâ gibi teknolojiler bu dönüşümde öne çıkan araçlar arasında yer almaktadır. Bu çalışma, gelişen teknolojilerin (blok zinciri, robotik süreç otomasyonu, makine öğrenimi ve yapay zekâ) bağımsız denetim süreçleri ile hileli finansal raporlamanın tespitindeki etkilerini incelemeyi amaçlamaktadır. Nitel araştırma desenine uygun olarak, Türkiye'de bağımsız denetim alanında uzman 10 kişiyle yarı yapılandırılmış görüşmeler gerçekleştirilmiş ve elde edilen veriler MAXQDA 2024 Pro yazılımı aracılığıyla analiz edilmiştir. Bulgular, blok zinciri teknolojisinin geçmişe dönük denetimden sürekli denetime geçişi mümkün kılabileceğini; robotik süreç otomasyonunun tekrarlayan işlemleri azaltarak denetim verimliliğini artırabileceğini; yapay zekâ uygulamalarının ise denetim süresini ve maliyetini azaltarak kaliteyi artırabileceğini göstermektedir. Bu çalışma, bağımsız denetim mesleğinin dijital dönüşüm sürecinde nasıl yeniden şekillendiğine dair nitel bir çerçeve sunarak literatüre katkı sağlamaktadır.

Anahtar Kelimeler

• Hileli Finansal Raporlama
• Blok Zinciri
• Makine Öğrenimi
• Robotik Süreç Otomasyonu
• Yapay Zekâ

Kaynakça

1. Aksoy, Barış. (2021). “Finansal Tablo Hileleri’nin makine öğrenmesi yöntemleri ve lojistik regresyon kullanılarak tahmin edilmesi: Borsa İstanbul örneği”. Maliye Finans Yazıları, 115, 27–58.
2. Bakarich, Kathleen. M. - O’brien, Patrick E. (2021). “The robots are coming …But aren’t here yet: The use of artificial ıntelligence technologies in the public accounting profession”. Journal of Emerging Technologies in Accounting, 18(1), 27–43.
3. Baltacı, Ali. (2019). “Nitel araştırma süreci: Nitel bir araştırma nasıl yapılır?”. Ahi Evran Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 5(2), 368–388.
4. Biçer, Ali Altuğ- Aydın, Osman. (2015). “Denetimde bilgisayar destekli denetim tekniklerinin (BDDT) kullanımı ve bu yöntem ile bir suistimal vakasının tespiti”. İstanbul Ticaret Üniversitesi Sosyal Bilimleri Dergisi, 28, 213-229.
5. Boillet, Jeanne. (2018). “How artificial ıntelligence will transform the audit”. EY. https://www.ey.com/en_tr/assurance/how-artificial-intelligence-will-transform-the-audit (Erişim Tarihi: 08.08.2024).
6. Brennan, Bill. - Flynn, Mike. - Baccala, Mike. (2017). “Artificial intelligence comes to financial statement audits”.
7. CFO, https://www.cfo.com/accounting-tax/2017/02/artificial-intelligence-audits/ (Erişim Tarihi: 19.08.2024).
8. Cho, Soohyun. - Vasarhelyi, Miklos. A. - Sun, Ting. - Zhang, Chanyuan. (2020). “Learning from machine learning in accounting and assurance”. Journal of Emerging Technologies in Accounting, 17(1), 1–10.

9. Cohen, Michael. - Rozario, Andrea. M. - Zhang, Chanyuan. (Abigail). (2019). “Exploring the use of robotic process automation (RPA) in substantive audit procedures”. The CPA Journal, https://www.cpajournal.com/2019/08/14/exploring-the-use-of-robotic-process-automation-rpa-in-substantive-audit-procedures/ (Erişim Tarihi: 08.08.2024).
10. CPA - AICPA. (2020). “The data-driven audit: How automation and aı are changing the audit and the role of the auditor”. https://www.aicpa.org/content/dam/aicpa/interestareas/frc/assuranceadvisoryservices/downloadabledocuments/the-data-driven-audit.pdf (Erişim Tarihi: 01.08.2024).
11. Dede, Adnan. (2024). “Yapay zeka teknolojilerinin, bağımsız denetim uygulamalarına etkileri”. The Premium E-Journal of Social Sciences, 8(46), 1210–1221.
12. Deloitte. (2017). “Blockchain technology and ıts potential ımpact on the audit and assurance profession”. https://www.aicpa.org/content/dam/aicpa/interestareas/frc/assuranceadvisoryservices/downloadabledocuments/blockchain-technology-and-its-potential-impact-on-the-audit-and-assurance-profession.pdf (Erişim Tarihi: 08.08.2024).
13. Dickey, Gabe. - Blanke, Sandra. - Seaton, Lyoyd. (2019). “Machine learning in auditing current and future applications”. The CPA Journal, https://www.cpajournal.com/2020/07/16/icymi-machine-learning-in-auditing/ (Erişim Tarihi: 19.08.2024).
14. EY. (2016). “Robotic process automation - automation’s next frontier”. In Ernst & Young, http://www.ey.com/Publication/vwLUAssets/ey-robotic-process automation/$FILE/ey-robotic-procegss-automation.pdf (Erişim Tarihi: 08.08.2024).
15. Gülten, Selçuk. (2020). “Bağımsız denetimde yapay zekâ kullanımı”. Denetimde Seçme Konular 5, Gazi Kitabevi, Ankara.
16. Kestane, Ali. - Kurnaz, Niyazi. (2021). “Bağımsız denetimde akıllı süreç otomasyonu uygulamaları”. Denetimde Seçme Konular 7, Gazi Kitabevi, Ankara.
17. Kokina, Julia.- Blanchette, Shay.- Davenport, Thomas. H.- Pachamanova, Dessislava. (2025). “Challenges and opportunities for artificial intelligence in auditing: Evidence from the field”. International Journal of Accounting Information Systems, 56, 1-22.
18. Kokina, Julia. - Davenport, Thomas. H. (2017). “The emergence of artificial intelligence: How automation is changing auditing”. Journal of Emerging Technologies in Accounting, 14(1), 115–122.
19. KPMG. (2021). “KPMG’ s Dynamic audit technology content series : Robotic process automation”. Kpmg, https://assets.kpmg.com/content/dam/kpmg/za/pdf/2021/robotic-process-automation.pdf (Erişim Tarihi: 27.06.2024).
20. Law, Kelvin. K., - Shen, Michael. (2025). “How does artificial intelligence shape audit firms?”. Management Science, 71(5), 3641-3666.
21. Maffei, Marco. - Casciello, Raffaela. - Meucci, Fiorenza. (2021). “Blockchain technology: uninvestigated ıssues emerging from an ıntegrated view within accounting and auditing practices”. Journal of Organizational Change Management, 34(2), 462–476.
22. Mahbod, Reza. - Hinton, Captain Darius. (2019). “Blockchain : The future of the auditing and assurance profession”. Armed Forces Comptroller, 64(1), 23–27.
23. Marjaei, Seyedhadi. - Yazdi, Fahimeh Ahmadian. - Chandrashekara, M. (2019). “MAXQDA and its application to LIS research”. Library Philosophy and Practice, 1–9.
24. Mejia, Niccolo. (2019). “What is RPA (robotic process automation)?”. Emerj the AL Research and Advisory Company, https://emerj.com/ai-glossary-terms/what-is-rpa/ (Erişim Tarihi: 27.06.2024).
25. Owonifari, Victor Olufemi.- Igbekoyi, Olusola Esther.- Awotomilusi, Niyi Solomon. -Dagunduro, Muyiwa Emmanuel. (2023). “Evaluation of artificial intelligence and efficacy of audit practice in Nigeria”. Asian Journal of Economics, Business and Accounting, 23(16), 1-14.
26. PwC. (2017). “Sizing The prize what’s the real value of aı for your business and how can you capitalise?”. PwC, https://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf (Erişim Tarihi: 03.07.2024).
27. Sadu, Israel. (2018). “Auditing blockchain”. Internal Auditor, 75(6), 17-19.
28. Seethamraju, Ravi. - Hecimovic, Angela. (2022). “Adoption of artificial intelligence in auditing: An exploratory study”. Australian Journal of Management, 1–21.
29. Smith, Sean Stein. - Castonguay, John Jack. (2020). “Blockchain and accounting governance: Emerging issues and considerations for accounting and assurance professionals”. Journal of Emerging Technologies in Accounting, 17(1), 119–131.
30. Tiberius, Victor. - Hirth, Stefanie. (2019). “Impacts of digitization on auditing: A delphi study for Germany”. Journal of International Accounting, Auditing and Taxation, 37, 1-14.
31. Tommervag, Arild Samuelsen. - Bach, Terje. - Jager, Bjorn. (2022). “Leveraging the competition: Robotic process automation (RPA) enabling competitive small and medium sized auditing firms”. IEEE/SICE International Symposium on System Integration, SII 2022, 833–837.
32. Vetter, Amy. (2018). “What CPAs should know about machine learning vs. deep learning”. Journal of Accountancy, https://www.journalofaccountancy.com/newsletters/2018/oct/artificial-intelligence-terminology/ (Erişim Tarihi: 09.06.2024).
33. Wang, Yunsen. - Kogan, Alexander. (2018). “Designing confidentiality-preserving blockchain-based transaction processing systems”. International Journal of Accounting Information Systems, 30, 1–18.
34. WEF. (2015). “Deep shift: Technology tipping points and societal impact”. World Economic Forum, http://www3.weforum.org/docs/WEF_GAC15_Technological_Tipping_Points_ report_2015.pdf (Erişim Tarihi: 23.06.2024).
35. Rezaee, Zabihollah.- Elam, Rick. - Sharbatoghlie, Ahmad. (2001). “Continuous auditing: The audit of the future”. Managerial Auditing Journal, 16(3), 150-158.