Digital Transformation in Audit: Opportunities and Challenges of Artificial Intelligence in Audit

Yıl 2025, Cilt: 5 Sayı: 1, 49 - 61, 31.01.2025

Osman Nuri Şahin , Nimet Evdilek

Öz

Over the last decade, artificial intelligence (AI) has made a significant impact in the accounting and financial auditing fields. In particular, the role of AI in fraud detection, automation processes in financial reporting, and data analysis is addressed. These innovations are factors that have deeply affected both professional practices and academic research and are shaping the future of the sector. This study has examined in detail the effects of artificial intelligence (AI) technologies in the accounting and financial auditing fields. The research shows that AI plays an important role in improving auditing processes as well as data processing and analysis capabilities. AI offers advantages such as fast data processing, improved fraud detection, and increased accuracy of financial reporting. However, these technological advances also bring with them challenges such as data security, ethical concerns, and the need for a qualified workforce. The research emphasizes the need for continuous development and adaptation to AI technologies to be used effectively in the accounting and financial auditing fields. This process plays a critical role in shaping the future of the sector and is vital for accounting professionals and businesses to compete and succeed in the ever-changing business world.

Anahtar Kelimeler

Artificial Intelligence, Accounting, Auditing, Digital Transformation, Technology

Muhasebe Denetiminde Dijital Dönüşüm: Denetimde Yapay Zekanın Fırsat ve Zorlukları

Öz

Son on yıl içinde, yapay zekâ (YZ), muhasebe ve finansal denetim alanlarında dikkate değer bir etki yaratmıştır. Özellikle, yapay zekanın hile tespiti, finansal raporlamadaki otomasyon süreçleri ve veri analizindeki rolü ele alınmaktadır. Bu yenilikler hem profesyonel uygulamaları hem de akademik araştırmaları derinden etkileyen ve sektörün geleceğini şekillendiren faktörlerdir. Bu çalışma, yapay zekâ (AI) teknolojilerinin muhasebe ve finansal denetim alanlarındaki etkilerini detaylı bir şekilde incelemiştir. Araştırma, AI'nın veri işleme ve analiz yeteneklerinin yanı sıra denetim süreçlerini iyileştirme konusunda önemli rol oynadığını göstermektedir. AI, hızlı veri işleme, dolandırıcılık tespitinde iyileştirme ve finansal raporlamanın doğruluğunu artırma gibi avantajlar sunmaktadır. Ancak, bu teknolojik ilerlemeler, veri güvenliği, etik kaygılar ve nitelikli işgücü ihtiyacı gibi zorlukları da beraberinde getirmektedir. Araştırma, AI teknolojilerinin muhasebe ve finansal denetim alanlarında etkin bir şekilde kullanılabilmesi için sürekli gelişim ve adaptasyonun gerekliliğini vurgulamaktadır. Bu süreç, sektörün geleceğini şekillendirmede kritik bir rol oynamakta ve muhasebe profesyonelleri ile işletmeler için rekabet edebilmek ve sürekli değişen iş dünyasında başarılı olmak açısından hayati önem taşımaktadır.

Anahtar Kelimeler

Yapay Zekâ, Muhasebe, Denetim, Dijital Dönüşüm, Teknoloji

Kaynakça

• AICPA. (2020). CPAs as Data Analysts: How Louisiana Accountants Respond to Data-Driven Business Paradigms, Retrieved from https://www.proquest.com/docview/2386340052?pq-origsite=gscholar&fromopenview=true&sourcetype=Dissertations%20&%20Theses
• Bak, M., Madai, V. I., Fritzsche, M. C., Mayrhofer, M. T. ve McLennan, S. (2022). You can’t have AI both ways: balancing health data privacy and access fairly. Frontiers in Genetics, 13. https://doi.org/10.3389/fgene.2022.929453.
• Bao, Y., Hilary, G., ve Ke, B. (2022). Artificial intelligence and fraud detection. In V. Babich, J. R. Birge, & G. Hilary (Eds.), Innovative technology at the interface of finance and operations, 1, (223–247), Springer Series in Supply Chain Management. https://doi.org/10.1007/978-3-030-86086-4_10.
• Batal, M. S. (2016). Yapay zeka uygulamaları ve yapay zekanın geleceği(Yüksek Lisans Tezi). Uluslararası Sunhıll Üniversitesi, Filipinler.
• Boillet, J. (2018). Why AI is both a risk and a way to manage risk. Retrieved from EY: https://www. ey. com/en_us/assurance/why-ai-is-both-a-risk-and-a-way-tomanage-risk.
• Bozkurt, P. (2016). Denetim Kavramı Ve Denetim Anlayışındaki Gelişmeler. Denetişim, (12), 56-62.
• Byrnes, P. E., Al-Awadhi, A., Gullvist, B., Brown-Liburd, H., Teeter, R., Warren Jr, J. D., ve Vasarhelyi, M. (2018). Evolution of auditing: From the traditional approach to the future audit. In Continuous auditing: Theory and application, 285-297.
• Chan, D. Y., ve Vasarhelyi, M. A. (2018). Innovation and practice of continuous auditing. In Continuous Auditing, 271-283.
• Chinnasamy, P., Deepalakshmi, P., Dutta, A. K., You, J., ve Joshi, G. P. (2021). Ciphertext-policy attribute-based encryption for cloud storage: Toward data privacy and authentication in AI-enabled IoT system. Mathematics, 10(1), 68.
• Couceiro, B., Pedrosa, I., ve Marini, A. (2020, June). State of the art of artificial intelligence in internal audit context. In 2020 15th Iberian Conference on Information Systems and Technologies (CISTI), 1-7.
• Curigliano, G., Burstein, H. J., Winer, E. P., Gnant, M., Dubsky, P., Loibl, S. ve Xu, B. (2017). De-escalating and escalating treatments for early-stage breast cancer: the St. Gallen International Expert Consensus Conference on the Primary Therapy of Early Breast Cancer 2017. Annals of Oncology, 28(8), 1700-1712.
• Deloitte (2024, December 12). Deloitte wins ‘Audit Innovation of the Year’ at 2015 International Accounting Bulletin awards. Deloitte Türkiye. https://www2.deloitte.com/tr/en/pages/about-deloitte/articles/deloitte-wins-audit-innovation-of-the-year.html.
• Dike, H. U., Zhou, Y., Deveerasetty, K. K. ve Wu, Q. (2018, October). Unsupervised learning based on artificial neural network: A review. In 2018 IEEE International Conference on Cyborg and Bionic Systems (CBS), 322-327.
• Efe, A. (2022). Yapay zeka algoritmalarının denetim mesleği üzerindeki potansiyel etkileri. 8(2), 1- 19 Erdoğan, M. (2019). Denetim 4.0 ve ötesi. Journal of Accounting and Taxation Studies, 12(3), 809-834.
• Fedyk, A., Hodson, J., Khimich, N., ve Fedyk, T. (2022). Is artificial intelligence improving the audit process?. Review of Accounting Studies, 27(3), 938-985.
• Göksel-Canbek, N., ve Mutlu, M. E. (2016). Sayısal gelecekte yeni adım: akıllı kişisel yardımcılar. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 2(1), 114-129.
• Gotthardt, M., Koivulaakso, D., Paksoy, O., Saramo, C., Martikainen, M., ve Lehner, O. (2020). Current state and challenges in the implementation of smart robotic process automation in accounting and auditing. ACRN Journal of Finance and Risk Perspectives.
• Hashimoto, K. (2022). Audit software trends for 2021-2022. MindBridge. Retrieved from https://www.mindbridge.ai/blog/audit-software-2021-2022-trends/.
• Huang, M. H., ve Rust, R. T. (2018). Artificial intelligence in service. Journal of service research, 21(2), 155-172.
• İmamoğlu, S. Z., Erat, S., ve İnce, H. (2023). Yönetim biliminde yapay zekâ. Nobel Akademik Yayıncılık.
• Issa, H., Sun, T., ve Vasarhelyi, M. A. (2016). Research ideas for artificial intelligence in auditing: The formalization of audit and workforce supplementation. Journal of Emerging Technologies in Accounting, 13(2), 1-20.
• Karabınar, S., ve Yılmaz, E. (2012). XBRL (genişletilebilir işletme raporlama dili) ve geleneksel finansal raporlama sistemlerindeki sorunların çözümüne katkıları. Muhasebe ve Vergi Uygulamaları Dergisi, 5, 2.
• Kayahan, T. Ü. M. (2015). Muhasebe Hilelerinin Önlenmesinde İç Kontrol Sisteminin Önemi Üzerine Bir Araştırma. Giresun Üniversitesi İktisadi ve İdari Bilimler Dergisi, 1(1), 105-128.
• Kokina, J., ve Davenport, T. H. (2017). The emergence of artificial intelligence: How automation is changing auditing. Journal of emerging technologies in accounting, 14(1), 115-122.
• KPMG (2024, November 3). KPMG Clara. https://kpmg.com/tr/tr/home/hizmetlerimiz/audit-services/kpmg-clara.html.
• Lison, P. (2015). An introduction to machine learning. Language Technology Group (LTG), 1(35), 1-35.
• Lokanan, M., Tran, V., ve Vuong, N. H. (2019). Detecting anomalies in financial statements using machine learning algorithm: The case of Vietnamese listed firms. Asian Journal of Accounting Research, 4(2), 181-201.
• Majumdar, S., Madi, T., Wang, Y., Tabiban, A., Oqaily, M., Alimohammadifar, A., ... ve Debbabi, M. (2019). Cloud security auditing. Springer.
• Moudud-Ul-Huq, S. (2014). The role of artificial intelligence in the development of accounting systems: a review. IUP Journal of Accounting Research & Audit Practices, 13(2).
• Munoko, I., Brown-Liburd, H. L., ve Vasarhelyi, M. (2020). The ethical implications of using artificial intelligence in auditing. Journal of Business Ethics, 167, 209-234.
• Ng, C., ve Alarcon, J. (2020). Artificial intelligence in accounting: Practical applications. Routledge.
• Nithiyuwith, T., ve 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.
• Noordin, N. A., Hussainey, K., ve Hayek, A. F. (2022). The use of artificial intelligence and audit quality: An analysis from the perspectives of external auditors in the UAE. Journal of Risk and Financial Management, 15(8), 339.
• Polii, B. D., ve Permana, D. E. (2021). The implementation of local wisdom-based vocational hospitality curriculum development model. International Journal of Tourism and Hospitality in Asia Pasific (IJTHAP), 4(1), 97-111.
• Puhan, S., Panda, D., ve Mishra, B. K. (2020). Energy efficiency for cloud computing applications: A survey on the recent trends and future scopes. In 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA), 1-6, IEEE.
• PWC (2024, December 12). Audit and General Ledger Analysis using Halo | PwC Mauritius. PwC. https://www.pwc.com/mu/en/services/crs/tech-assurance/general-ledger-audit.html.
• Raghavan, M., Barocas, S., Kleinberg, J., ve Levy, K. (2020). Mitigating bias in algorithmic hiring: Evaluating claims and practices. In Proceedings of the 2020 conference on fairness, accountability, and transparency, 469-481.
• Sağlar, J. (2009). İşletmelerde iç denetim fonksiyonunun bağımsız dış denetim maliyeti üzerindeki etkileri. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 18(1), 343-358.
• Sanal, R. (2002). Türkiye'de yönetsel denetim ve devlet denetleme kurulu. TODAİE, Türkiye ve Orta Doğu Amme İdaresi Enstitüsü Yayınları, 314.
• Seethamraju, R. C., ve Hecimovic, A. (2020). Impact of Artificial Intelligence on Auditing-An Exploratory Study. Şentürk, Ö. (2023). İç denetim faaliyetlerinde yapay zekadan beklentiler: chatgpt uygulaması örneği. Tıde AcademIA Research, 4(2), 51-82.
• Sevim, A., ve Bülbül, S. (2017). Kurumsal kaynak planlaması (enterprise resource planning erp) sistemlerinin sürekli denetiminde yapay zekâ kullanımı. Journal of Aksaray University Faculty of Economics & Administrative Sciences/Aksaray Üniversitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi, 9(1).
• Smith, S. S. (2018). Digitization and financial reporting–how technology innovation may drive the shift toward continuous accounting. Accounting and Finance Research, 7(3), 240-250.
• Solaimani, R., Mohammed, S., Rashed, F., ve Elkelish, W. (2020). The impact of artificial intelligence on corporate control. Corporate Ownership & Control, 17(3), 171-178.
• Struthers-Kennedy, A., ve Nesgood, K. (2020). Artificial intelligence and internal audit: A pragmatic perspective. Protiviti. Retrieved from https://blog.protiviti.com/2020/01/02/artificial-intelligence-and-internal-audit-a-pragmatic-perspective/
• Tiron-Tudor, A., ve Deliu, D. (2022). Reflections on the human-algorithm complex duality perspectives in the auditing process. Qualitative Research in Accounting & Management, 19(3), 255-285.
• Ukpong, E. G., Udoh, I. I., ve Essien, I. T. (2019). Artificial intelligence: opportunities, issues and applications in banking, accounting, and auditing in Nigeria. Asian Journal of Economics, Business and Accounting, 10(1), 1-6.
• Van Eck, M. L., Firat, M., Nuijten, W. P., Sidorova, N., ve van der Aalst, W. M. (2017). Human performance-aware scheduling and routing of a multi-skilled workforce. Complex Systems Informatics and Modeling Quarterly, 68(12), 1-21.
• Wang, Z. (2021). Abnormal financial transaction detection via AI technology. International Journal of Distributed Systems and Technologies (IJDST), 12(2), 24-34.