Repenser la qualité et la performance de l’audit à l’ère des approches analytiques : proposition d’un cadre conceptuel intégrateur
DOI:
https://doi.org/10.23882/ijdam.26348Palavras-chave:
Audit Data Analytics, Big Data Analytics, Intelligence artificielle, Qualité de l’audit, Efficience de l’audit, Efficacité de l’auditResumo
L’évolution des environnements organisationnels et la croissance des volumes de données transforment profondément les pratiques d’audit, remettant en question les approches traditionnelles fondées sur des traitements manuels et des logiques d’échantillonnage. Dans ce contexte, les approches analytiques orientées données apparaissent comme des leviers potentiels d’amélioration de la qualité et de la performance de l’audit. Cet article vise à examiner dans quelle mesure ces approches permettent de repenser la qualité et la performance de l’audit, et à proposer un cadre conceptuel intégrateur permettant d’en structurer l’analyse tout en tenant compte des conditions susceptibles d’en influencer les effets. Pour ce faire, la recherche adopte une démarche conceptuelle fondée sur une revue approfondie de la littérature, permettant de clarifier les notions de qualité et de performance de l’audit et d’articuler leurs relations avec les approches analytiques. Les résultats mettent en évidence que ces approches constituent des leviers significatifs d’amélioration du processus d’audit, tout en soulignant que leurs effets demeurent conditionnés par des facteurs individuels et organisationnels, notamment la compétence des auditeurs et le soutien de la direction générale.
Referências
Abdelrahim, A., & Al-Malkawi, H. A. N. (2022). The influential factors of internal audit effectiveness: A conceptual model. International Journal of Financial Studies, 10(3), Article 71. https://doi.org/10.3390/ijfs10030071
Abdelwahed, A. S., Abu-Musa, A. A. E. S., Badawy, H. A. E. S., & Moubarak, H. (2025a). Investigating the impact of adopting big data and data analytics on enhancing audit quality. Journal of Financial Reporting and Accounting, 23(2), 472–495. https://doi.org/10.1108/JFRA-12-2023-0724
Abdelwahed, A. S., Abu-Musa, A. A. E. S., Badawy, H. A. E. S., & Moubarak, H. (2025b). Unleashing the beast: The impact of big data and data analytics on the auditing profession: Evidence from a developing country. Future Business Journal, 11(1), Article 12. https://doi.org/10.1186/s43093-024-00420-7
Abdelwahed, A. S., Abu-Musa, A. A. E. S., Moubarak, H., & Badawy, H. A. E. S. (2024). The use of big data and analytics in external auditing: Does audit firm size matter? Evidence from a developing country. South African Journal of Accounting Research, 38(2), 113–145. https://doi.org/10.1080/10291954.2023.2279751
Akaaboune, O., & Laqrib, Y. Z. (2026). Les synergies entre les dispositifs d’audit et la qualité de l’information financière : Une revue systématique de la littérature. Alternatives Managériales & Économiques, 8(1), 158–173. https://doi.org/10.48374/IMIST.PRSM/ame-v8i1.61195
Al-Hajaya, K. (2019). The impact of audit committee effectiveness on audit quality: Evidence from the Middle East. International Review of Management and Marketing, 9(5), 1–8. https://doi.org/10.32479/irmm.8341
Alles, M. G., & Gray, G. L. (2015). The pros and cons of using big data in auditing: A synthesis of the literature and a research agenda [Working paper]. J. E. Boritz Consultants Limited. Consulté le 9 juillet 2026, sur https://jebcl.com/symposium/wp-content/uploads/2015/09/The-Pros-and-Cons-of-Using-Big-Data-in-Auditing-A-Synthesis-of-the-Literature-UWCISA-Revised.pdf
Alles, M. G., & Gray, G. L. (2016). Incorporating big data in audits: Identifying inhibitors and a research agenda to address those inhibitors. International Journal of Accounting Information Systems, 22, 44–59. https://doi.org/10.1016/j.accinf.2016.07.004
Allouli, N., & Boumeska, M. (2023). L’impact de la transformation digitale sur l’audit externe : Nouvelles perspectives et pratiques émergentes. Revue systématique de littérature. Alternatives Managériales & Économiques, 5(4), 135–153. https://doi.org/10.48374/IMIST.PRSM/ame-v5i4.44213
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
Alqaraleh, M. H., Almari, M. O. S., Ali, B. J. A., & Oudat, M. S. (2022). The mediating role of organizational culture on the relationship between information technology and internal audit effectiveness. Corporate Governance and Organizational Behavior Review, 6(1), 8–18. https://doi.org/10.22495/cgobrv6i1p1
Alzeban, A., & Gwilliam, D. (2014). Factors affecting the internal audit effectiveness: A survey of the Saudi public sector. Journal of International Accounting, Auditing and Taxation, 23(2), 74–86. https://doi.org/10.1016/j.intaccaudtax.2014.06.001
American Institute of Certified Public Accountants (2015). Audit analytics and continuous audit: Looking toward the future [Report]. Consulté le 9 juillet 2026, sur https://www.aicpa-cima.com/resources/download/audit-analytics-and-continuous-audit-looking-toward-the-future
American Institute of Certified Public Accountants (2017). Guide to audit data analytics [Report]. Consulté le 9 juillet 2026, sur https://egrove.olemiss.edu/aicpa_guides/1737
André, H. (2020). Facteurs affectant l’efficacité de la fonction d’audit interne dans les entreprises publiques béninoises : Forces et faiblesses ?. Revue Internationale des Sciences de Gestion, 3(4), 471–505.
Appelbaum, D., Kogan, A., & Vasarhelyi, M. A. (2017). Big data and analytics in the modern audit engagement: Research needs. Auditing: A Journal of Practice & Theory, 36(4), 1–27. https://doi.org/10.2308/ajpt-51684
Ayadi, O., & Bensghir, A. (2021). La transition de l’audit traditionnel vers l’audit continu. Revue Française d’Économie et de Gestion, 2(3), 1–12. Consulté le 9 juillet 2026, sur https://www.revuefreg.fr/index.php/home/article/view/217
Barr-Pulliam, D., Brown-Liburd, H. L., & Sanderson, K.-A. (2022). The effects of the internal control opinion and use of audit data analytics on perceptions of audit quality, assurance, and auditor negligence. Auditing: A Journal of Practice & Theory, 41(1), 25–48. https://doi.org/10.2308/AJPT-19-064
Bassrih, M. (2021). L’efficacité de l’audit interne dans les établissements publics marocains : Analyse des facteurs d’influence par la méthode des équations structurelles. Revue des Études Multidisciplinaires en Sciences Économiques et Sociales, 6(2). https://doi.org/10.48375/IMIST.PRSM/remses-v6i2.25509
Bierstaker, J. L., Burnaby, P., & Thibodeau, J. (2001). The impact of information technology on the audit process: An assessment of the state of the art and implications for the future. Managerial Auditing Journal, 16(3), 159–164. https://doi.org/10.1108/02686900110385489
Boyle, D., & Canning, M. (2005). The impact of audit education on perceptions of deficient auditor performance. Accounting, Finance & Governance Review, 12(1), 15–37. https://doi.org/10.52399/001c.34149
Brennan, B., Baccala, M., & Flynn, M. (2017, February 2). Artificial intelligence comes to financial statement audits. CFO.com. Consulté le 9 juillet 2026, sur https://www.cfo.com/news/artificial-intelligence-comes-to-financial-statement-audits/660745/
Cao, M., Chychyla, R., & Stewart, T. (2015). Big data analytics in financial statement audits. Accounting Horizons, 29(2), 423–429. https://doi.org/10.2308/acch-51068
Cavaliere, L. P. L., Rakesh, Keswani, S., Muda, I., Polisetty, A., Swadia, B. U., Rajest, S. S., & Regin, R. (2021). The determinants of audit quality and impact on overall audit performance. Natural Volatiles & Essential Oils, 8(5), 12963–12984. Consulté le 9 juillet 2026, sur https://www.nveo.org/index.php/journal/article/view/4139
Chambers, A. D., & Odar, M. (2015). A new vision for internal audit. Managerial Auditing Journal, 30(1), 34–55. https://doi.org/10.1108/MAJ-08-2014-1073
Chemingui, M., & Pigé, B. (2004, May). La qualité de l’audit : Analyse critique et proposition d’une approche d’évaluation axée sur la nature des travaux d’audit réalisés [Communication]. Normes et mondialisation, France. Consulté le 9 juillet 2026, sur https://shs.hal.science/halshs-00593012
Christ, M. H., Emett, S. A., Summers, S. L., & Wood, D. A. (2021). Prepare for takeoff: Improving asset measurement and audit quality with drone-enabled inventory audit procedures. Review of Accounting Studies, 26(4), 1323–1343. https://doi.org/10.1007/s11142-020-09574-5
Citron, D. B., & Taffler, R. J. (1992). The audit report under going concern uncertainties: An empirical analysis. Accounting and Business Research, 22(88), 337–345. https://doi.org/10.1080/00014788.1992.9729449
Cohen, A., & Sayag, G. (2010). The effectiveness of internal auditing: An empirical examination of its determinants in Israeli organisations. Australian Accounting Review, 20(3), 296–307. https://doi.org/10.1111/j.1835-2561.2010.00092.x
Dai, J., & Vasarhelyi, M. A. (2016). Imagineering Audit 4.0. Journal of Emerging Technologies in Accounting, 13(1), 1–15. https://doi.org/10.2308/jeta-10494
DeAngelo, L. E. (1981). Auditor size and audit quality. Journal of Accounting and Economics, 3(3), 183–199. https://doi.org/10.1016/0165-4101(81)90002-1
Ditkaew, K., & Suttipun, M. (2023). The impact of audit data analytics on audit quality and audit review continuity in Thailand. Asian Journal of Accounting Research, 8(3), 269–278. https://doi.org/10.1108/AJAR-04-2022-0114
Dittenhofer, M. (2001). Internal auditing effectiveness: An expansion of present methods. Managerial Auditing Journal, 16(8), 443–450. https://doi.org/10.1108/EUM0000000006064
Drogalas, G., Karagiorgos, T., & Arampatzis, K. (2015). Factors associated with internal audit effectiveness: Evidence from Greece. Journal of Accounting and Taxation, 7(7), 113–122. https://doi.org/10.5897/JAT2015.0182
Eulerich, M., Masli, A., Pickerd, J., & Wood, D. A. (2023). The impact of audit technology on audit task outcomes: Evidence for technology-based audit techniques. Contemporary Accounting Research, 40(2), 981–1012. https://doi.org/10.1111/1911-3846.12847
Fatikasari, C. D., & Amrulloh, A. (2024). Evaluating the impact of information technology on audit efficiency and effectiveness. Researcher Academy Innovation Data Analysis, 1(2), 102–112. https://doi.org/10.69725/raida.v1i2.159
Fedyk, A., Hodson, J., Khimich, N., & Fedyk, T. (2022). Is artificial intelligence improving the audit process?. Review of Accounting Studies, 27(3), 938–985. https://doi.org/10.1007/s11142-022-09697-x
Freiman, J. W., Kim, Y., & Vasarhelyi, M. A. (2022). Full population testing: Applying multidimensional audit data sampling (MADS) to general ledger data auditing. International Journal of Accounting Information Systems, 46, Article 100573. https://doi.org/10.1016/j.accinf.2022.100573
Gao, R., Huang, S., & Wang, R. (2020). Data analytics and audit quality [Working paper]. SSRN. https://doi.org/10.2139/ssrn.3928355
Gepp, A., Linnenluecke, M. K., O’Neill, T. J., & Smith, T. (2018). Big data techniques in auditing research and practice: Current trends and future opportunities. Journal of Accounting Literature, 40, 102–115. https://doi.org/10.1016/j.acclit.2017.05.003
Girma, M. (2023). Factors affecting internal audit efficiency: The case of Commercial Nominees [Master’s thesis, St. Mary’s University]. Consulté le 9 juillet 2026, sur https://repository.smuc.edu.et/bitstream/123456789/7775/1/Mintesinot%20thesis%20.pdf
Glover, S. M., Prawitt, D. F., & Drake, M. S. (2015). Between a rock and a hard place: A path forward for using substantive analytical procedures in auditing large P&L accounts: Commentary and analysis. Auditing: A Journal of Practice & Theory, 34(3), 161–179. https://doi.org/10.2308/ajpt-50978
Gu, H., Schreyer, M., Moffitt, K., & Vasarhelyi, M. (2024). Artificial intelligence co-piloted auditing. International Journal of Accounting Information Systems, 54, Article 100698. https://doi.org/10.1016/j.accinf.2024.100698
Gurama, Z., & Mansor, M. (2018). Internal audit effectiveness in tax administration: A model proposition. Journal of Advanced Research in Business and Management Studies, 12(1), 70–78.
Haenlein, M., & Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Review, 61(4), 5–14. https://doi.org/10.1177/0008125619864925
Hidayat, I., Antong, & Rahmawati (2024). The role of artificial intelligence (AI) in improving audit efficiency and effectiveness. Proceedings Series on Proceedings of Multidisciplinary Sciences, 1(1), 1195–1202. Consulté le 9 juillet 2026, sur https://journal.conference.umpalopo.ac.id/index.php/icbens/article/view/124
Holmes, A. F., & Douglass, A. (2022). Artificial intelligence: Reshaping the accounting profession and the disruption to accounting education. Journal of Emerging Technologies in Accounting, 19(1), 53–68. https://doi.org/10.2308/JETA-2020-054
Ibrahim, A. E. A., Elamer, A. A., & Ezat, A. N. (2021). The convergence of big data and accounting: Innovative research opportunities. Technological Forecasting and Social Change, 173, Article 121171. https://doi.org/10.1016/j.techfore.2021.121171
Issa, H., Sun, T., & 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. https://doi.org/10.2308/jeta-10511
Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3(4), 305–360. https://doi.org/10.1016/0304-405X(76)90026-X
Joshi, P. L. (2020). Determinants affecting internal audit effectiveness. EMAJ: Emerging Markets Journal, 10(2), 10–17. https://doi.org/10.5195/emaj.2020.208
Joshi, P. L. (2021). Which factors affect the internal audit effectiveness in India?. Indian Journal of Commerce & Management Studies, 12(2), 1–13. https://doi.org/10.18843/ijcms/v12i2/01
Joshi, P. L., & Marthandan, G. (2020). Continuous internal auditing: Can big data analytics help?. International Journal of Accounting, Auditing and Performance Evaluation, 16(1), 25–42. https://doi.org/10.1504/IJAAPE.2020.106766
Kamala, R. (2017, March–April). Using data analytics. Today’s CPA. Consulté le 9 juillet 2026, sur https://www.tx.cpa/docs/default-source/communications/2017-today%27s-cpa/data-analytics.pdf?sfvrsn=2
Kaya, C. T., Türkyılmaz, M., & Birol, B. (2019). RPA teknolojilerinin muhasebe sistemleri üzerindeki etkisi. Muhasebe ve Finansman Dergisi, (82), 235–250. https://doi.org/10.25095/mufad.536083
Kaya, İ., Akbulut, D. H., & Ozoner, K. (2018). Big data analytics in internal audit. PressAcademia Procedia, 7(1), 260–262. https://doi.org/10.17261/Pressacademia.2018.893
Kerfali, S. (2023). Contribution to the study of the effectiveness of internal audit functions in Moroccan public institutions and companies: A quantitative approach. Alternatives Managériales & Économiques, 5(4), 116–134. https://doi.org/10.48374/IMIST.PRSM/ame-v5i4.44210
Khalaf, M. H. (2024). The impact of using data analytics in the audit process on the audit report lag: Evidence from Egypt. Alexandria Journal of Managerial Research and Information Systems, 3(3), 1–15. https://doi.org/10.21608/ajmris.2024.376686
Khan, R., Adi, E., & Hussain, O. (2021). AI-based audit of fuzzy front end innovation using ISO 56002. Managerial Auditing Journal, 36(4), 564–590. https://doi.org/10.1108/MAJ-03-2020-2588
Kokina, J., Blanchette, S., Davenport, T. H., & Pachamanova, D. (2025). Challenges and opportunities for artificial intelligence in auditing: Evidence from the field. International Journal of Accounting Information Systems, 56, Article 100734. https://doi.org/10.1016/j.accinf.2025.100734
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. https://doi.org/10.2308/jeta-51730
Lawrence, P. R., & Lorsch, J. W. (1967). Organization and environment: Managing differentiation and integration. Division of Research, Graduate School of Business Administration, Harvard University.
Lehlous, I., Zeamari, M., & Berrada, K. (2024). Efficacité de l’audit interne entre indicateurs et difficultés de mesure : Cadre conceptuel. Revue Marocaine de Commerce et de Gestion, 1, 85–105. Consulté le 9 juillet 2026, sur https://revues.imist.ma/index.php/RMCGE/article/view/48305
Li, H., Dai, J., Gershberg, T., & Vasarhelyi, M. A. (2018). Understanding usage and value of audit analytics for internal auditors: An organizational approach. International Journal of Accounting Information Systems, 28, 59–76. https://doi.org/10.1016/j.accinf.2017.12.005
Li, X., Brazel, J. F., Gold, A., & Leiby, J. (2026). Inheriting versus developing data analytic tests and auditors’ professional skepticism. Journal of Accounting Research, 64(2), 885–922. https://doi.org/10.1111/1475-679X.70014
Lombardi, D. R., Kim, M., Sipior, J. C., & Vasarhelyi, M. A. (2025). The increased role of advanced technology and automation in audit: A Delphi study. International Journal of Accounting Information Systems, 56, Article 100733. https://doi.org/10.1016/j.accinf.2025.100733
Lugli, E., & Bertacchini, F. (2023). Audit quality and digitalization: Some insights from the Italian context. Meditari Accountancy Research, 31(4), 841–860. https://doi.org/10.1108/MEDAR-08-2021-1399
Mahouat, N., Azenzoul, A., Benlakouiri, A., & Mokhlis, K. (2025). Contribution de la transformation digitale à l’amélioration de la qualité de l’audit externe dans les établissements publics : Étude qualitative dans le contexte marocain. Alternatives Managériales & Économiques, 7(4), 107–130. https://doi.org/10.48374/IMIST.PRSM/ame-v7i4.58988
Messier, W. F., Eilifsen, A., & Austen, L. A. (2004). Auditor detected misstatements and the effect of information technology. International Journal of Auditing, 8(3), 223–235. https://doi.org/10.1111/j.1099-1123.2004.00092.x
Mihret, D. G., & Yismaw, A. W. (2007). Internal audit effectiveness: An Ethiopian public sector case study. Managerial Auditing Journal, 22(5), 470–484. https://doi.org/10.1108/02686900710750757
Miszczuk, P., & Bednarek, P. (2024). Artificial intelligence application in the auditing profession. In J. Dyczkowska (Ed.), Human versus machine: Accounting, auditing and education in the era of artificial intelligence (pp. 35–48). Publishing House of Wroclaw University of Economics and Business. https://doi.org/10.15611/2024.58.1.02
Moffitt, K. C., Rozario, A. M., & Vasarhelyi, M. A. (2018). Robotic process automation for auditing. Journal of Emerging Technologies in Accounting, 15(1), 1–10. https://doi.org/10.2308/jeta-10589
Mökander, J., Schuett, J., Kirk, H. R., & Floridi, L. (2024). Auditing large language models: A three-layered approach. AI and Ethics, 4(4), 1085–1115. https://doi.org/10.1007/s43681-023-00289-2
Munoko, I., Brown-Liburd, H. L., & Vasarhelyi, M. (2020). The ethical implications of using artificial intelligence in auditing. Journal of Business Ethics, 167(2), 209–234. https://doi.org/10.1007/s10551-019-04407-1
Murphy, M. L., & Tysiac, K. (2015, April 13). Data analytics helps auditors gain deep insight. Journal of Accountancy. Consulté le 9 juillet 2026, sur https://www.journalofaccountancy.com/issues/2015/apr/data-analytics-for-auditors/
Nasution, R., Dailibas, Chaerudin, Harahap, M. N., Mutaufiq, A., & Kumala, D. (2024). Influence of audit technology implementation on efficiency and accuracy of audits in public companies: A case study of manufacturing companies in Indonesia. International Journal of Artificial Intelligence Research, 8(1.1). Consulté le 9 juillet 2026, sur https://www.ijair.id/index.php/ijair/article/view/1196
Nugroho, Y., Uzliawati, L., & Taqi, M. (2021). The effect of audit quality, internal audit size, auditor competency and management support on the effectiveness of internal audit. Asian Journal of Social Science and Management Technology, 3(4), 48–60. Consulté le 9 juillet 2026, sur https://www.ajssmt.com/Papers/344860.pdf
Rahman, M. J., Zhu, H., & Yue, L. (2024). Does the adoption of artificial intelligence by audit firms and their clients affect audit quality and efficiency? Evidence from China. Managerial Auditing Journal, 39(6), 668–699. https://doi.org/10.1108/MAJ-03-2023-3846
Rahman, M. J., & Ziru, A. (2023). Clients’ digitalization, audit firms’ digital expertise, and audit quality: Evidence from China. International Journal of Accounting & Information Management, 31(2), 221–246. https://doi.org/10.1108/IJAIM-08-2022-0170
Rajgopal, S., Srinivasan, S., & Zheng, X. (2021). Measuring audit quality. Review of Accounting Studies, 26(2), 559–619. https://doi.org/10.1007/s11142-020-09570-9
Rose, A. M., Rose, J. M., Rotaru, K., Sanderson, K.-A., & Thibodeau, J. C. (2022). Effects of uncertainty visualization on attention, arousal, and judgment. Behavioral Research in Accounting, 34(1), 113–139. https://doi.org/10.2308/BRIA-2021-011
Saleh, I., Marei, Y., Ayoush, M., & Abu Afifa, M. M. (2023). Big data analytics and financial reporting quality: Qualitative evidence from Canada. Journal of Financial Reporting and Accounting, 21(1), 83–104. https://doi.org/10.1108/JFRA-12-2021-0489
Salijeni, G., Samsonova-Taddei, A., & Turley, S. (2019). Big data and changes in audit technology: Contemplating a research agenda. Accounting and Business Research, 49(1), 95–119. https://doi.org/10.1080/00014788.2018.1459458
Schultz, T. W. (1961). Investment in human capital. The American Economic Review, 51(1), 1–17.
Sewpersadh, N. S. (2025). Adaptive structural audit processes as shaped by emerging technologies. International Journal of Accounting Information Systems, 56, Article 100735. https://doi.org/10.1016/j.accinf.2025.100735
Singh, K. S. D., Ravindran, S., Ganesan, Y., Abbasi, G. A., & Haron, H. (2021). Antecedents and internal audit quality implications of internal audit effectiveness. International Journal of Business Science and Applied Management, 16(2), 1–21. https://doi.org/10.69864/ijbsam.16-2.145
Spence, M. (1973). Job market signaling. The Quarterly Journal of Economics, 87(3), 355–374. https://doi.org/10.2307/1882010
Suchman, M. C. (1995). Managing legitimacy: Strategic and institutional approaches. Academy of Management Review, 20(3), 571–610. https://doi.org/10.2307/258788
Thottoli, M. M. (2021). Impact of information communication technology competency among auditing professionals. Accounting. Analysis. Auditing, 8(2), 38–47. https://doi.org/10.26794/2408-9303-2021-8-2-38-47
Torroba, M., Sánchez, J. R., López, L., & Callejón, Á. (2025). Investigating the impacting factors for the audit professionals to adopt data analysis and artificial intelligence: Empirical evidence for Spain. International Journal of Accounting Information Systems, 56, Article 100738. https://doi.org/10.1016/j.accinf.2025.100738
Vitali, S., & Giuliani, M. (2024). Emerging digital technologies and auditing firms: Opportunities and challenges. International Journal of Accounting Information Systems, 53, Article 100676. https://doi.org/10.1016/j.accinf.2024.100676
Williamson, O. E. (1981). The economics of organization: The transaction cost approach. American Journal of Sociology, 87(3), 548–577. https://doi.org/10.1086/227496
Yoon, K., Hoogduin, L., & Zhang, L. (2015). Big data as complementary audit evidence. Accounting Horizons, 29(2), 431–438. https://doi.org/10.2308/acch-51076
Zaleha, P. A., & Novita, N. (2021). Dampak teknologi informasi, etika profesi terhadap kinerja auditor. Jurnal Akuntansi dan Auditing, 17(1), 90–114. https://doi.org/10.14710/jaa.17.1.90-114
Zhang, C., Cho, S., & Vasarhelyi, M. (2022). Explainable artificial intelligence (XAI) in auditing. International Journal of Accounting Information Systems, 46, Article 100572. https://doi.org/10.1016/j.accinf.2022.100572
Zhang, G., Atasoy, H., & Vasarhelyi, M. A. (2022). Continuous monitoring with machine learning and interactive data visualization: An application to a healthcare payroll process. International Journal of Accounting Information Systems, 46, Article 100570. https://doi.org/10.1016/j.accinf.2022.100570
Downloads
Publicado
Como Citar
Edição
Secção
Licença
Direitos de Autor (c) 2026 Hanae BENALLAL, Abdelkamel ALJ, Adnane BOUJIBAR
Este trabalho encontra-se publicado com a Creative Commons Atribuição-NãoComercial 4.0.
Portugal
