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YAPAY ZEKA YATIRIMLARI, GERÇEKÇİ RAPORLAR VE FİNANSAL KAYIPLAR

Yıl 2024, Sayı: 31, 117 - 128, 01.12.2024
https://doi.org/10.58348/denetisim.1519501

Öz

Denetim planlaması sırasında denetçiler görev aldıkları firmaların işlerini incelerler ve denetler. Yine de hedef, denetimin gerçek planlanan mali tabloları ile iç denetimlerin özet raporları arasındaki tutarsızlığı en aza indirmektir. Öte yandan Türk firmalarında yapay zekâ harcamaları Ulusal Yapay Strateji belgesine göre arttığından, yapay zekâ, iç denetim faaliyetleri de dahil her organizasyonel sürecin bir parçası haline gelmesi beklenmektedir. Ayrıca bilim yazın, iç denetim ile firmaların sermaye kayıplarının azalması arasında pozitif bir ilişki olduğunu desteklemektedir. Bu nedenle bu araştırma, yapay zekâ harcamaları, iç denetim raporları ve firmaların finansal kayıpları arasındaki ilişkiyi analiz etmeyi amaçlamaktadır. Bu amaca ulaşmak için Ticaret ve Sanayi Odası/Tekirdağ/Türkiye'ye üye 732 anonim şirketten elde edilen veriler incelenmiş ve uygun olanları analiz edilmiştir. Yapısal eşitlik modellemesi sonuçları, yapay zekâ yatırımlarının mali tablolar ile iç denetim raporları arasındaki farkı azalttığını göstermektedir (β=-0,045). Öte yandan iç denetim raporlarında gerçek mali tablolarla karşılaştırıldığında ortaya çıkan farklılıklar, daha açık bir ifadeyle mali tablolar ile iç denetim raporları arasındaki artan farklılıklar, firmaların mali kayıplarını neredeyse %10 (β=0,118) oranında artırmaktadır. Başka bir deyişle, yapay zekaya yatırım yapmak daha gerçekçi finansal raporlara katkıda bulunarak daha az finansal kayıpla sonuçlanır. Bu açıdan bakıldığında bu çalışma, yapay zekâ yatırımını iç denetimlere ve Türk firmalarının finansal performansına bağlayan önde gelen çalışmalardan biridir.

Kaynakça

  • Al-Baity, H. H. (2023). The Artificial Intelligence Revolution in Digital Finance in Saudi Arabia: A Comprehensive Review and Proposed Framework. Sustainability, 15(18), 13725. https://doi.org/10.3390/su151813725
  • Alina, C. M., Cerasela, S. E., & Gabriela, G. (2018). Internal Audit Role in Artificial Intelligence. Ovidius University Annals: Economic Sciences Series, XVIII(1), 441–445.
  • Almufadda, G., & Almezeini, N. A. (2022). Artificial Intelligence Applications in the Auditing Profession: A Literature Review. Journal of Emerging Technologies in Accounting, 19(2), 29–42. https://doi.org/10.2308/JETA-2020-083
  • Alwadie, A. (2024). Impact of Technology on Auditing: Evidence in Developing Countries. International Journal for Scientific Research, 3(2), 29–48. https://doi.org/10.59992/IJSR.2024.v3n2p2
  • Amiq, B., Prawesthi, W., Taufik, M., Widodo, H., Seti, S., & Aranggraeni, R. (2024). Increasing Internal Auditor Accountability in Law of State Financial Management. Journal of Law and Sustainable Development, 12(1), e2877. https://doi.org/10.55908/sdgs.v12i1.2877
  • Askary, S., Abu-Ghazaleh, N., & Tahat, Y. A. (2018). Artificial Intelligence and Reliability of Accounting Information. In S. A. Al-Sharhan, A. C. Simintiras, Y. K. Dwivedi, M. Janssen, M. Mäntymäki, L. Tahat, I. Moughrabi, T. M. Ali, & N. P. Rana (Eds.), Challenges and Opportunities in the Digital Era (Vol. 11195, pp. 315–324). Springer International Publishing. https://doi.org/10.1007/978-3-030-02131-3_28
  • Azzam, M. J., Alrabba, H. M., AlQudah, A. M., & Mansur, H. M. A. (2020). A study on the relationship between internal and external audits on financial reporting quality ,. Management Science Letters, 937–942. https://doi.org/10.5267/j.msl.2019.10.001
  • Badem, M. (2024). Agricultural Structure of Tekirdağ Province and Evaluation of Agricultural Supports. International Journal of Innovative Approaches in Agricultural Research, 8(1), 45–61. https://doi.org/10.29329/ijiaar.2024.656.5
  • Brown, A., & Maydeu-Olivares, A. (2011). Item Response Modeling of Forced-Choice Questionnaires. Educational and Psychological Measurement, 71(3), 460–502. https://doi.org/10.1177/0013164410375112
  • Buaton, R., Muhammad, Z., Elviwani, & Dilham, A. (2022). Optimization of Higher Education Internal Quality Audits Based on Artificial Intelligence. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 1(2), 158–161. https://doi.org/10.59934/jaiea.v1i2.83
  • Byrne, B. M. (2010). Structural Equation Modeling with AMOS Basic Concepts, Applications, and Programming. Routledge.
  • Collins Kindzeka, K. (2023). Impact of Artificial Intelligence on Accounting, Auditing and Financial Reporting. American Journal of Computing and Engineering, 6(1), 29–34. https://doi.org/10.47672/ajce.1433
  • Commerford, B. P., Dennis, S. A., Joe, J. R., & Wang, J. (2020). Man Versus Machine: Complex Estimates and Auditor Reliance on Artificial Intelligence. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3422591
  • Dagunduro, M. E., Falana, G. A., Adewara, Y. M., & Busayo, T. O. (2023). Application of Artificial Intelligence and Audit Quality in Nigeria. Advances in Multidisciplinary and Scientific Research Journal Publication, 11(1), 39–56. https://doi.org/10.22624/AIMS/HUMANITIES/V11N1P4
  • Dazok Donald Jambol, Oludayo Olatoye Sofoluwe, Ayemere Ukato, & Obinna Joshua Ochulor. (2024). Transforming equipment management in oil and gas with AI-Driven predictive maintenance. Computer Science & IT Research Journal, 5(5), 1090–1112. https://doi.org/10.51594/csitrj.v5i5.1117
  • Deribe, W. J., & Regasa, D. G. (2014). Factors Determining Internal Audit Quality: Empirical Evidence from Ethiopian Commercial Banks. Research Journal of Finance and Accounting, 5, 86–94.
  • Felix, Jr., W. L., Gramling, A. A., & Maletta, M. J. (2001). The Contribution of Internal Audit as a Determinant of External Audit Fees and Factors Influencing This Contribution. Journal of Accounting Research, 39(3), 513–534. https://doi.org/10.1111/1475-679X.00026
  • Ganapathy, V. (2023). AI in Auditing: A Comprehensive Review of Applications, Benefits and Challenges. Shodh Sari-An International Multidisciplinary Journal, 02(04), 328–343. https://doi.org/10.59231/SARI7643
  • Gebrayel, E., Jarrar, H., Salloum, C., & Lefebvre, Q. (2018). Effective association between audit committees and the internal audit function and its impact on financial reporting quality: Empirical evidence from Omani listed firms. International Journal of Auditing, 22(2), 197–213. https://doi.org/10.1111/ijau.12113
  • Glory Ugochi Ebirim, Beryl Odonkor, Ese Eigbadon Oshioste, Kehinde Feranmi Awonuga, Nduniuisi Leonard Ndubuisi, & Odunayo Adewunmi Adelekan. (2024). Evolving trends in corporate auditing: A systematic review of practices and regulations in the United States. World Journal of Advanced Research and Reviews, 21(1), 2250–2262. https://doi.org/10.30574/wjarr.2024.21.1.0312
  • Hair, J. F. (Ed.). (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (Second edition). Sage.
  • Hergan, K. (2022). Challenges implementing and running an AI-Lab: Experience and Literature Review. Biomedical Journal of Scientific & Technical Research, 45(4). https://doi.org/10.26717/BJSTR.2022.45.007222
  • Hoffman, B. J., Blair, C. A., Meriac, J. P., & Woehr, D. J. (2007). Expanding the criterion domain? A quantitative review of the OCB literature. Journal of Applied Psychology, 92(2), 555–566. https://doi.org/10/cvdk6n
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10/dbt
  • Ibrahim, G., Mansor, N., & Ahmad, A. U. (2020). The Mediating Effect Of Internal Audit Committee On The Relationship Between Firms Financial Audits And Real Earnings Management. International Journal of Scientific & Technology Research, 9, 816–822.
  • Ikhsan, W. M., Ednoer, E. H., Kridantika, W. S., & Firmansyah, A. (2022). FRAUD DETECTION AUTOMATION THROUGH DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE. Riset, 4(2), 103–119. https://doi.org/10.37641/riset.v4i2.166
  • Iman Supriadi. (2024). The audit revolution: Integrating artificial intelligence in detecting accounting fraud. Akuntansi Dan Teknologi Informasi, 17(1), 48–61. https://doi.org/10.24123/jati.v17i1.6279
  • Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or Not, AI Comes—An Interview Study of Organizational AI Readiness Factors. Business & Information Systems Engineering, 63(1), 5–20. https://doi.org/10.1007/s12599-020-00676-7
  • K. Johl, S., Kaur Johl, S., Subramaniam, N., & Cooper, B. (2013). Internal audit function, board quality and financial reporting quality: Evidence from Malaysia. Managerial Auditing Journal, 28(9), 780–814. https://doi.org/10.1108/MAJ-06-2013-0886
  • Kabakci, G. E., & Ince, Y. (2023). Artificial Intelligence’s Impact on SMEs: AI in Practice Restructuring Small and Medium-Sized Businesses. Proceeding Book of 2nd International Conference on Frontiers in Academic Research ICFAR 2023, 153–160. https://doi.org/10.59287/as-proceedings.456
  • Kahyaoglu, S. B., & Aksoy, T. (2021). Artificial Intelligence in Internal Audit and Risk Assessment. In U. Hacioglu & T. Aksoy (Eds.), Financial Ecosystem and Strategy in the Digital Era (pp. 179–192). Springer International Publishing. https://doi.org/10.1007/978-3-030-72624-9_8
  • Karaboga, U., & Vardarlier, P. (2020). Examining the use of artificial intelligence in recruitment processes. Bussecon Review of Social Sciences (2687-2285), 2(4), 1–17. https://doi.org/10.36096/brss.v2i4.234
  • Khan, A. K. M. K. (2024). AI in Finance Disruptive Technologies and Emerging Opportunities. Journal of Artificial Intelligence General Science (JAIGS) ISSN:3006-4023, 3(1), 155–170. https://doi.org/10.60087/jaigs.v3i1.76
  • Kimani, B. (2024). Influence of Accounting Information Systems (AIS) on Financial Reporting Accuracy. American Journal of Accounting, 6(1), 37–47. https://doi.org/10.47672/ajacc.1787
  • Kline, R. B. (2016). Principles and practice of structural equation modeling (Fourth edition). The Guilford Press.
  • Lazăr Pleşa, T., Popescu, C., & Pleşa, I. T. (2023). From Digitization to Artificial Intelligence in External Public Audit. Valahian Journal of Economic Studies, 14(1), 47–59. https://doi.org/10.2478/vjes-2023-0006
  • Lidiana, L. (2024). AI and Auditing: Enhancing Audit Efficiency and Effectiveness with Artificial Intelligence. Accounting Studies and Tax Journal (COUNT), 1(3), 214–223. https://doi.org/10.62207/g0wpn394
  • Lu, H., Peng, Y., Ding, J., & Fu, Z. (2024). Integration and transformation: The impact and applications of artificial intelligence in the financial sector. Applied and Computational Engineering, 42(1), 140–146. https://doi.org/10.54254/2755-2721/42/20230769
  • Meira, M. F. P. (2019). O impacto da Inteligência Artificial na Auditoria. https://api.semanticscholar.org/CorpusID:226809589
  • Mirzaei, A., Hajizade, M., & Hajizade, H. (2022). Studying the effect of artificial intelligence on improvement of various quality criteria in relation to audit work in Iran. International Journal of Health Sciences, 12623–12635. https://doi.org/10.53730/ijhs.v6nS1.8181
  • Mpofu, F. Y. (2023). The application of Artificial Intelligence in external auditing and its implications on audit quality? A review of the ongoing debates. International Journal of Research in Business and Social Science (2147- 4478), 12(9), 496–512. https://doi.org/10.20525/ijrbs.v12i9.2737
  • Noordin, N. A., Hussainey, K., & 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. https://doi.org/10.3390/jrfm15080339
  • Nwachukwu, C. E., Usman, T. O., Akhor, S. O., & Oladipupo, A. O. (2021). Auditing in the New Age of Industry 4.0: The Need for More Research. International Journal of Business Strategy and Automation, 2(1), 17–28. https://doi.org/10.4018/IJBSA.20210101.oa2
  • Olabanji, S. O., Oladoyinbo, O. B., Asonze, C. U., Oladoyinbo, T. O., Ajayi, S. A., & Olaniyi, O. O. (2024). Effect of Adopting AI to Explore Big Data on Personally Identifiable Information (PII) for Financial and Economic Data Transformation. Asian Journal of Economics, Business and Accounting, 24(4), 106–125. https://doi.org/10.9734/ajeba/2024/v24i41268
  • Oladejo, M., Yinus, S. O., Kampala International University, Shittu, S., ,Ladoke Akintola University of Technology, Nigeria, Rutaro, A., & Kampala International University. (2021). INTERNAL AUDIT PRACTICE AND FINANCIAL REPORTING QUALITY: PERSPECTIVE FROM NIGERIAN QUOTED FOODS AND BEVERAGES FIRMS. Kampala International University Interdisciplinary Journal of Humanities and Social Sciences, 2(1), 410–428. https://doi.org/10.59568/KIJHUS-2021-2-1-24
  • Peretz-Andersson, E., Tabares, S., Mikalef, P., & Parida, V. (2024). Artificial intelligence implementation in manufacturing SMEs: A resource orchestration approach. International Journal of Information Management, 77, 102781. https://doi.org/10.1016/j.ijinfomgt.2024.102781
  • Pizzini, M., Lin, S., & Ziegenfuss, D. E. (2015). The Impact of Internal Audit Function Quality and Contribution on Audit Delay. AUDITING: A Journal of Practice & Theory, 34(1), 25–58. https://doi.org/10.2308/ajpt-50848
  • Ramzan, S. (2023). Perception of Artificial Intelligence in the Auditing Industry of British Columbia. International Journal of Scientific and Research Publications, 13(5), 252–260. https://doi.org/10.29322/IJSRP.13.05.2023.p13733
  • Rodrigues, L., Pereira, J., Da Silva, A. F., & Ribeiro, H. (2023). The impact of artificial intelligence on audit profession. Journal of Information Systems Engineering and Management, 8(1), 19002. https://doi.org/10.55267/iadt.07.12743
  • Sari, G. I., Suhaili, A., & Lesfandra, L. (2024). The Mediation Role of Audit Quality: Impact Internal Audit Strategy, Auditor Ethics, and Accounting Culture on Financial Report Quality. Atestasi : Jurnal Ilmiah Akuntansi, 7(1), 300–316. https://doi.org/10.57178/atestasi.v7i1.779
  • Seethamraju, R. C., & Hecimovic, A. (2020). Impact of Artificial Intelligence on Auditing—An Exploratory Study. Americas Conference on Information Systems. https://api.semanticscholar.org/CorpusID:220795188
  • Setyahuni, S. W., Purusa, N. A., Prayogi, J., & Mujib, M. (2022). Internal Audit Quality, Corporate Governance, and Corporate Social Responsibility: Determinants of Financial Reporting Quality. BALANCE: Economic, Business, Management and Accounting Journal, 19(2), 113. https://doi.org/10.30651/blc.v19i2.10683
  • Tüfekci, M., Tüfekci, E., & Dikicioğlu, A. (2020). Numerical Investigation of the Collapse of a Steel Truss Roof and a Probable Reason of Failure. Applied Sciences, 10(21), 7769. https://doi.org/10.3390/app10217769
  • Vojvodic, M., & Hitz, C. (2022). Relation of Data Governance, Customer-Centricity and Data Processing Compliance. Central European Business Review, 11(5), 109–148. https://doi.org/10.18267/j.cebr.310
  • Vuković, B., Tica, T., & Jakšić, D. (2024). Challenges of using digital technologies in audit. Anali Ekonomskog Fakulteta u Subotici, 51, 15–30. https://doi.org/10.5937/AnEkSub2300014V
  • Wassie, F. A., & Lakatos, L. P. (2024). Artificial intelligence and the future of the internal audit function. Humanities and Social Sciences Communications, 11(1), 386. https://doi.org/10.1057/s41599-024-02905-w
  • Wu, W., Widiatmo, G., & Riantama, D. (2023). What motivates customers to repurchase online under social distancing? Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1155302
  • Yusup, M., & Juhara, D. (2020). Influence of Internal Audit On the Quality of Financial Statements: (Survey on Private Sector Manufacturing Companies in Bandung). Jurnal Ekonomi, Bisnis & Entrepreneurship, 14(2), 56–61. https://doi.org/10.55208/jebe.v14i2.205
  • Zain Mohammad Ali Al- Dahabi, Rula Yousef Hajjaj, & Fatima Ali Algazo. (2024). Attitudes of auditors about employing artificial intelligence in the auditing process: Jordanian auditing companies are an example. International Journal of Science and Research Archive, 11(2), 1765–1776. https://doi.org/10.30574/ijsra.2024.11.2.0679

ARTIFICIAL INTELLIGENCE INVESTMENT, REALISTIC REPORTS, AND FINANCIAL LOSS

Yıl 2024, Sayı: 31, 117 - 128, 01.12.2024
https://doi.org/10.58348/denetisim.1519501

Öz

During audit planning, auditors examine the business of their firms. Still, the target is to minimize the discrepancy in the real planned financial statement of inspection and summary reports of internal audits. On the other hand, expenditures on artificial intelligence have been increasing in Turkish firms; according to the National Artificial Strategy document, AI will be part of every organizational process, including internal audits. Moreover, the literature supports a positive relationship between internal audits and firms’ decreasing capital loss. So, this research aims to analyze the relationship between AI expenditures, internal audit reports, and the firms’ historical loss. To reach this aim, suitable data was analyzed from 732 incorporated companies that are members of the Chamber of Trade and Industry/Tekirdag/Turkey. Structural equation modeling results show that AI investments decrease the discrepancy between financial statements and internal audit reports (β=-0.045). On the other hand, discrepancies found in the internal audit reports compared to real financial statements are increasing firms’ financial losses by almost 10% (β=.118). In other words, investing in AI contributes to more realistic financial reports, resulting in fewer financial losses. From this perspective, this study is one of the leading studies that connects AI investment to internal audits and the financial performance of Turkish firms.

Kaynakça

  • Al-Baity, H. H. (2023). The Artificial Intelligence Revolution in Digital Finance in Saudi Arabia: A Comprehensive Review and Proposed Framework. Sustainability, 15(18), 13725. https://doi.org/10.3390/su151813725
  • Alina, C. M., Cerasela, S. E., & Gabriela, G. (2018). Internal Audit Role in Artificial Intelligence. Ovidius University Annals: Economic Sciences Series, XVIII(1), 441–445.
  • Almufadda, G., & Almezeini, N. A. (2022). Artificial Intelligence Applications in the Auditing Profession: A Literature Review. Journal of Emerging Technologies in Accounting, 19(2), 29–42. https://doi.org/10.2308/JETA-2020-083
  • Alwadie, A. (2024). Impact of Technology on Auditing: Evidence in Developing Countries. International Journal for Scientific Research, 3(2), 29–48. https://doi.org/10.59992/IJSR.2024.v3n2p2
  • Amiq, B., Prawesthi, W., Taufik, M., Widodo, H., Seti, S., & Aranggraeni, R. (2024). Increasing Internal Auditor Accountability in Law of State Financial Management. Journal of Law and Sustainable Development, 12(1), e2877. https://doi.org/10.55908/sdgs.v12i1.2877
  • Askary, S., Abu-Ghazaleh, N., & Tahat, Y. A. (2018). Artificial Intelligence and Reliability of Accounting Information. In S. A. Al-Sharhan, A. C. Simintiras, Y. K. Dwivedi, M. Janssen, M. Mäntymäki, L. Tahat, I. Moughrabi, T. M. Ali, & N. P. Rana (Eds.), Challenges and Opportunities in the Digital Era (Vol. 11195, pp. 315–324). Springer International Publishing. https://doi.org/10.1007/978-3-030-02131-3_28
  • Azzam, M. J., Alrabba, H. M., AlQudah, A. M., & Mansur, H. M. A. (2020). A study on the relationship between internal and external audits on financial reporting quality ,. Management Science Letters, 937–942. https://doi.org/10.5267/j.msl.2019.10.001
  • Badem, M. (2024). Agricultural Structure of Tekirdağ Province and Evaluation of Agricultural Supports. International Journal of Innovative Approaches in Agricultural Research, 8(1), 45–61. https://doi.org/10.29329/ijiaar.2024.656.5
  • Brown, A., & Maydeu-Olivares, A. (2011). Item Response Modeling of Forced-Choice Questionnaires. Educational and Psychological Measurement, 71(3), 460–502. https://doi.org/10.1177/0013164410375112
  • Buaton, R., Muhammad, Z., Elviwani, & Dilham, A. (2022). Optimization of Higher Education Internal Quality Audits Based on Artificial Intelligence. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 1(2), 158–161. https://doi.org/10.59934/jaiea.v1i2.83
  • Byrne, B. M. (2010). Structural Equation Modeling with AMOS Basic Concepts, Applications, and Programming. Routledge.
  • Collins Kindzeka, K. (2023). Impact of Artificial Intelligence on Accounting, Auditing and Financial Reporting. American Journal of Computing and Engineering, 6(1), 29–34. https://doi.org/10.47672/ajce.1433
  • Commerford, B. P., Dennis, S. A., Joe, J. R., & Wang, J. (2020). Man Versus Machine: Complex Estimates and Auditor Reliance on Artificial Intelligence. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3422591
  • Dagunduro, M. E., Falana, G. A., Adewara, Y. M., & Busayo, T. O. (2023). Application of Artificial Intelligence and Audit Quality in Nigeria. Advances in Multidisciplinary and Scientific Research Journal Publication, 11(1), 39–56. https://doi.org/10.22624/AIMS/HUMANITIES/V11N1P4
  • Dazok Donald Jambol, Oludayo Olatoye Sofoluwe, Ayemere Ukato, & Obinna Joshua Ochulor. (2024). Transforming equipment management in oil and gas with AI-Driven predictive maintenance. Computer Science & IT Research Journal, 5(5), 1090–1112. https://doi.org/10.51594/csitrj.v5i5.1117
  • Deribe, W. J., & Regasa, D. G. (2014). Factors Determining Internal Audit Quality: Empirical Evidence from Ethiopian Commercial Banks. Research Journal of Finance and Accounting, 5, 86–94.
  • Felix, Jr., W. L., Gramling, A. A., & Maletta, M. J. (2001). The Contribution of Internal Audit as a Determinant of External Audit Fees and Factors Influencing This Contribution. Journal of Accounting Research, 39(3), 513–534. https://doi.org/10.1111/1475-679X.00026
  • Ganapathy, V. (2023). AI in Auditing: A Comprehensive Review of Applications, Benefits and Challenges. Shodh Sari-An International Multidisciplinary Journal, 02(04), 328–343. https://doi.org/10.59231/SARI7643
  • Gebrayel, E., Jarrar, H., Salloum, C., & Lefebvre, Q. (2018). Effective association between audit committees and the internal audit function and its impact on financial reporting quality: Empirical evidence from Omani listed firms. International Journal of Auditing, 22(2), 197–213. https://doi.org/10.1111/ijau.12113
  • Glory Ugochi Ebirim, Beryl Odonkor, Ese Eigbadon Oshioste, Kehinde Feranmi Awonuga, Nduniuisi Leonard Ndubuisi, & Odunayo Adewunmi Adelekan. (2024). Evolving trends in corporate auditing: A systematic review of practices and regulations in the United States. World Journal of Advanced Research and Reviews, 21(1), 2250–2262. https://doi.org/10.30574/wjarr.2024.21.1.0312
  • Hair, J. F. (Ed.). (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (Second edition). Sage.
  • Hergan, K. (2022). Challenges implementing and running an AI-Lab: Experience and Literature Review. Biomedical Journal of Scientific & Technical Research, 45(4). https://doi.org/10.26717/BJSTR.2022.45.007222
  • Hoffman, B. J., Blair, C. A., Meriac, J. P., & Woehr, D. J. (2007). Expanding the criterion domain? A quantitative review of the OCB literature. Journal of Applied Psychology, 92(2), 555–566. https://doi.org/10/cvdk6n
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10/dbt
  • Ibrahim, G., Mansor, N., & Ahmad, A. U. (2020). The Mediating Effect Of Internal Audit Committee On The Relationship Between Firms Financial Audits And Real Earnings Management. International Journal of Scientific & Technology Research, 9, 816–822.
  • Ikhsan, W. M., Ednoer, E. H., Kridantika, W. S., & Firmansyah, A. (2022). FRAUD DETECTION AUTOMATION THROUGH DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE. Riset, 4(2), 103–119. https://doi.org/10.37641/riset.v4i2.166
  • Iman Supriadi. (2024). The audit revolution: Integrating artificial intelligence in detecting accounting fraud. Akuntansi Dan Teknologi Informasi, 17(1), 48–61. https://doi.org/10.24123/jati.v17i1.6279
  • Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or Not, AI Comes—An Interview Study of Organizational AI Readiness Factors. Business & Information Systems Engineering, 63(1), 5–20. https://doi.org/10.1007/s12599-020-00676-7
  • K. Johl, S., Kaur Johl, S., Subramaniam, N., & Cooper, B. (2013). Internal audit function, board quality and financial reporting quality: Evidence from Malaysia. Managerial Auditing Journal, 28(9), 780–814. https://doi.org/10.1108/MAJ-06-2013-0886
  • Kabakci, G. E., & Ince, Y. (2023). Artificial Intelligence’s Impact on SMEs: AI in Practice Restructuring Small and Medium-Sized Businesses. Proceeding Book of 2nd International Conference on Frontiers in Academic Research ICFAR 2023, 153–160. https://doi.org/10.59287/as-proceedings.456
  • Kahyaoglu, S. B., & Aksoy, T. (2021). Artificial Intelligence in Internal Audit and Risk Assessment. In U. Hacioglu & T. Aksoy (Eds.), Financial Ecosystem and Strategy in the Digital Era (pp. 179–192). Springer International Publishing. https://doi.org/10.1007/978-3-030-72624-9_8
  • Karaboga, U., & Vardarlier, P. (2020). Examining the use of artificial intelligence in recruitment processes. Bussecon Review of Social Sciences (2687-2285), 2(4), 1–17. https://doi.org/10.36096/brss.v2i4.234
  • Khan, A. K. M. K. (2024). AI in Finance Disruptive Technologies and Emerging Opportunities. Journal of Artificial Intelligence General Science (JAIGS) ISSN:3006-4023, 3(1), 155–170. https://doi.org/10.60087/jaigs.v3i1.76
  • Kimani, B. (2024). Influence of Accounting Information Systems (AIS) on Financial Reporting Accuracy. American Journal of Accounting, 6(1), 37–47. https://doi.org/10.47672/ajacc.1787
  • Kline, R. B. (2016). Principles and practice of structural equation modeling (Fourth edition). The Guilford Press.
  • Lazăr Pleşa, T., Popescu, C., & Pleşa, I. T. (2023). From Digitization to Artificial Intelligence in External Public Audit. Valahian Journal of Economic Studies, 14(1), 47–59. https://doi.org/10.2478/vjes-2023-0006
  • Lidiana, L. (2024). AI and Auditing: Enhancing Audit Efficiency and Effectiveness with Artificial Intelligence. Accounting Studies and Tax Journal (COUNT), 1(3), 214–223. https://doi.org/10.62207/g0wpn394
  • Lu, H., Peng, Y., Ding, J., & Fu, Z. (2024). Integration and transformation: The impact and applications of artificial intelligence in the financial sector. Applied and Computational Engineering, 42(1), 140–146. https://doi.org/10.54254/2755-2721/42/20230769
  • Meira, M. F. P. (2019). O impacto da Inteligência Artificial na Auditoria. https://api.semanticscholar.org/CorpusID:226809589
  • Mirzaei, A., Hajizade, M., & Hajizade, H. (2022). Studying the effect of artificial intelligence on improvement of various quality criteria in relation to audit work in Iran. International Journal of Health Sciences, 12623–12635. https://doi.org/10.53730/ijhs.v6nS1.8181
  • Mpofu, F. Y. (2023). The application of Artificial Intelligence in external auditing and its implications on audit quality? A review of the ongoing debates. International Journal of Research in Business and Social Science (2147- 4478), 12(9), 496–512. https://doi.org/10.20525/ijrbs.v12i9.2737
  • Noordin, N. A., Hussainey, K., & 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. https://doi.org/10.3390/jrfm15080339
  • Nwachukwu, C. E., Usman, T. O., Akhor, S. O., & Oladipupo, A. O. (2021). Auditing in the New Age of Industry 4.0: The Need for More Research. International Journal of Business Strategy and Automation, 2(1), 17–28. https://doi.org/10.4018/IJBSA.20210101.oa2
  • Olabanji, S. O., Oladoyinbo, O. B., Asonze, C. U., Oladoyinbo, T. O., Ajayi, S. A., & Olaniyi, O. O. (2024). Effect of Adopting AI to Explore Big Data on Personally Identifiable Information (PII) for Financial and Economic Data Transformation. Asian Journal of Economics, Business and Accounting, 24(4), 106–125. https://doi.org/10.9734/ajeba/2024/v24i41268
  • Oladejo, M., Yinus, S. O., Kampala International University, Shittu, S., ,Ladoke Akintola University of Technology, Nigeria, Rutaro, A., & Kampala International University. (2021). INTERNAL AUDIT PRACTICE AND FINANCIAL REPORTING QUALITY: PERSPECTIVE FROM NIGERIAN QUOTED FOODS AND BEVERAGES FIRMS. Kampala International University Interdisciplinary Journal of Humanities and Social Sciences, 2(1), 410–428. https://doi.org/10.59568/KIJHUS-2021-2-1-24
  • Peretz-Andersson, E., Tabares, S., Mikalef, P., & Parida, V. (2024). Artificial intelligence implementation in manufacturing SMEs: A resource orchestration approach. International Journal of Information Management, 77, 102781. https://doi.org/10.1016/j.ijinfomgt.2024.102781
  • Pizzini, M., Lin, S., & Ziegenfuss, D. E. (2015). The Impact of Internal Audit Function Quality and Contribution on Audit Delay. AUDITING: A Journal of Practice & Theory, 34(1), 25–58. https://doi.org/10.2308/ajpt-50848
  • Ramzan, S. (2023). Perception of Artificial Intelligence in the Auditing Industry of British Columbia. International Journal of Scientific and Research Publications, 13(5), 252–260. https://doi.org/10.29322/IJSRP.13.05.2023.p13733
  • Rodrigues, L., Pereira, J., Da Silva, A. F., & Ribeiro, H. (2023). The impact of artificial intelligence on audit profession. Journal of Information Systems Engineering and Management, 8(1), 19002. https://doi.org/10.55267/iadt.07.12743
  • Sari, G. I., Suhaili, A., & Lesfandra, L. (2024). The Mediation Role of Audit Quality: Impact Internal Audit Strategy, Auditor Ethics, and Accounting Culture on Financial Report Quality. Atestasi : Jurnal Ilmiah Akuntansi, 7(1), 300–316. https://doi.org/10.57178/atestasi.v7i1.779
  • Seethamraju, R. C., & Hecimovic, A. (2020). Impact of Artificial Intelligence on Auditing—An Exploratory Study. Americas Conference on Information Systems. https://api.semanticscholar.org/CorpusID:220795188
  • Setyahuni, S. W., Purusa, N. A., Prayogi, J., & Mujib, M. (2022). Internal Audit Quality, Corporate Governance, and Corporate Social Responsibility: Determinants of Financial Reporting Quality. BALANCE: Economic, Business, Management and Accounting Journal, 19(2), 113. https://doi.org/10.30651/blc.v19i2.10683
  • Tüfekci, M., Tüfekci, E., & Dikicioğlu, A. (2020). Numerical Investigation of the Collapse of a Steel Truss Roof and a Probable Reason of Failure. Applied Sciences, 10(21), 7769. https://doi.org/10.3390/app10217769
  • Vojvodic, M., & Hitz, C. (2022). Relation of Data Governance, Customer-Centricity and Data Processing Compliance. Central European Business Review, 11(5), 109–148. https://doi.org/10.18267/j.cebr.310
  • Vuković, B., Tica, T., & Jakšić, D. (2024). Challenges of using digital technologies in audit. Anali Ekonomskog Fakulteta u Subotici, 51, 15–30. https://doi.org/10.5937/AnEkSub2300014V
  • Wassie, F. A., & Lakatos, L. P. (2024). Artificial intelligence and the future of the internal audit function. Humanities and Social Sciences Communications, 11(1), 386. https://doi.org/10.1057/s41599-024-02905-w
  • Wu, W., Widiatmo, G., & Riantama, D. (2023). What motivates customers to repurchase online under social distancing? Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1155302
  • Yusup, M., & Juhara, D. (2020). Influence of Internal Audit On the Quality of Financial Statements: (Survey on Private Sector Manufacturing Companies in Bandung). Jurnal Ekonomi, Bisnis & Entrepreneurship, 14(2), 56–61. https://doi.org/10.55208/jebe.v14i2.205
  • Zain Mohammad Ali Al- Dahabi, Rula Yousef Hajjaj, & Fatima Ali Algazo. (2024). Attitudes of auditors about employing artificial intelligence in the auditing process: Jordanian auditing companies are an example. International Journal of Science and Research Archive, 11(2), 1765–1776. https://doi.org/10.30574/ijsra.2024.11.2.0679
Toplam 59 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Denetim ve Mali Sorumluluk
Bölüm Makale
Yazarlar

Korhan Arun 0000-0001-7494-9591

Yayımlanma Tarihi 1 Aralık 2024
Gönderilme Tarihi 20 Temmuz 2024
Kabul Tarihi 24 Eylül 2024
Yayımlandığı Sayı Yıl 2024 Sayı: 31

Kaynak Göster

APA Arun, K. (2024). ARTIFICIAL INTELLIGENCE INVESTMENT, REALISTIC REPORTS, AND FINANCIAL LOSS. Denetişim(31), 117-128. https://doi.org/10.58348/denetisim.1519501

TR Dizin'de yer alan Denetişim dergisi yayımladığı çalışmalarla; alanındaki profesyoneller, akademisyenler ve düzenleyiciler arasında etkili bir iletişim ağı kurarak, etkin bir denetim ve yönetim sistemine ulaşma yolculuğunda önemli mesafelerin kat edilmesine katkı sağlamaktadır.