Farras, Ashab and Ali, Amjad and Audi, Marc (2025): Advancing Audit Practices through Technology: A Comprehensive Review of Continuous Auditing.
Preview |
PDF
MPRA_paper_127319.pdf Download (291kB) | Preview |
Abstract
Continuous auditing has emerged as a transformative practice within the accounting and auditing professions, driven by rapid technological advancements and the growing demand for real-time financial assurance. Traditional audit practices rely on manual work, increasing the risk of human error and repetitive tasks. But Continuous auditing is powered by transformative tools like robotic process automation which eliminates these barriers by automating routine processes, reducing errors, and freeing employees from repetitive work. This paper examines the evolution of continuous auditing, its integration with advanced technologies such as artificial intelligence, robotic process automation, blockchain, and data analytics, and the broader implications for auditors, organizations, and academic institutions. Such advanced technology works together in continuous auditing to enhance accuracy, automate processes, and ensure data accuracy. Synergy in these advanced technologies enhanced audit efficiency. Through a comprehensive review of scholarly literature, the study underscores how continuous auditing facilitates real-time monitoring, improves audit quality, and reduces risks associated with traditional audit methods. Nevertheless, its adoption presents several challenges, including the management of information overload, the preservation of auditor independence, and the resolution of skill deficiencies among professionals. The 2024 BDO Audit Innovation Survey found that more than two-thirds (69%) of finance leaders said establishing data governance and internal data management is a barrier to a smooth audit experience. According to a 2019 ISACA survey, nearly two-thirds of organizations say the tech skills gap is impacting IT audits. The paper concludes by stressing the critical need to align auditing practices, professional training, and technological innovation to get the maximum benefits of continuous auditing in a digitally driven business environment.
| Item Type: | MPRA Paper |
|---|---|
| Original Title: | Advancing Audit Practices through Technology: A Comprehensive Review of Continuous Auditing |
| English Title: | Advancing Audit Practices through Technology: A Comprehensive Review of Continuous Auditing |
| Language: | English |
| Keywords: | AI, RPA, Accuracy, Sample, Audit Frequency, Automation and Training |
| Subjects: | G - Financial Economics > G3 - Corporate Finance and Governance |
| Item ID: | 127319 |
| Depositing User: | Dr. Amjad Ali |
| Date Deposited: | 08 Feb 2026 07:34 |
| Last Modified: | 08 Feb 2026 07:34 |
| References: | Akim, M. (2020). Analyzing the role of information and communication technology in economic development among OIC nations. Journal of Policy Options, 3(3). Alles, M. (2020). Continuous auditing: Theory and application. Journal of Information Systems, 34(2), 5–24. Alles, M. G., Kogan, A., & Vasarhelyi, M. A. (2008). Putting continuous auditing theory into practice: Lessons from two pilot implementations. Journal of Information Systems, 22(2), 195–214. Alles, M., Brennan, G., Kogan, A., & Vasarhelyi, M. A. (2018). Continuous monitoring of business process controls: A pilot implementation of a continuous auditing system at Siemens. In Continuous auditing: Theory and application (pp. 219–246). Emerald Publishing Limited. Alles, M., Kogan, A., & Vasarhelyi, M. A. (2006). Continuous auditing: A new view of auditing. Managerial Auditing Journal, 21(1), 123–134. American Institute of Certified Public Accountants. (1980). Evidential matter: Statement on Auditing Standards (SAS) No. 31. August. American Institute of Certified Public Accountants. (1988). Analytical procedures: Statement on Auditing Standards (SAS) No. 56. April. American Institute of Certified Public Accountants. (1995). Consideration of internal control in a financial statement audit: An amendment to SAS No. 55: Statement on Auditing Standards (SAS) No. 78. December. American Institute of Certified Public Accountants. (1996). Amendment to Statement on Auditing Standards No. 31, Evidential Matter: SAS No. 80. December. American Institute of Certified Public Accountants. (1997). The information technology age: Evidential matter in the electronic environment, auditing procedure study. January. 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. Appelbaum, D., Kogan, A., & Vasarhelyi, M. A. (2024). Artificial intelligence in auditing: The state of the art and future directions. Journal of Information Systems, 38(1), 1–20. Argento, D., Dobija, D., Grossi, G., Marrone, M., & Mora, L. (2025). The unaccounted effects of digital transformation: Implications for accounting, auditing, and accountability research. Accounting, Auditing & Accountability Journal, 38(2), 123–145. Audi, M., Ali, A., & Al-Masri, R. (2022). Determinants of Advancement in Information Communication Technologies and its Prospect under the Role of Aggregate and Disaggregate Globalization. Scientific Annals of Economics and Business, 69(2), 191-215. Ayogu, M. (2023). Fostering transparency and accountability: Enhancing statutory audits in Nigeria. Journal of Business and Economic Options, 6(1). Baltagi, B. H. (2005). Econometric analysis of panel data (3rd ed.). John Wiley & Sons. Bell, T. B., Marrs, F. O., Solomon, I., & Thomas, H. (1997). Auditing organizations through a strategic-systems lens. KPMG. Bierstaker, J., Burnaby, P., & Thibodeau, J. (2012). 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, 17(3), 159–164. Brazel, J. F., Agoglia, C. P., & Hatfield, R. C. (2014). A review of experimental and archival auditing research. Journal of Accounting Literature, 33, 1–25. Brougham, D., & Haar, J. (2018). Smart technology, artificial intelligence, robotics, and algorithms (STARA): Employees’ perceptions of future workplace automation. Journal of Management & Organization, 24(2), 239–257. Brown-Liburd, H., Issa, H., & Lombardi, D. (2015). Behavioral implications of big data's impact on audit judgment and decision making and future research directions. Accounting Horizons, 29(2), 451–468. Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company. Can, K. (2021). The evolution of communication technologies in Turkey's modern economy. Journal of Policy Options, 4(3). Canadian Institute of Chartered Accountants. (1999). Research report: Continuous auditing. Cao, M., Chychyla, R., & Stewart, T. (2015). Big data analytics in financial statement audits. Accounting Horizons, 29(2), 423–429. Chan, D. Y., & Vasarhelyi, M. A. (2011). Innovation and practice of continuous auditing. International Journal of Accounting Information Systems, 12(3), 152–160. Chan, D. Y., & Vasarhelyi, M. A. (2018). Innovation and practice of continuous auditing. In Continuous auditing (pp. 271–283). Emerald Publishing Limited. Clark, R., Dillion, R., & Farrell, T. (1989). Continuous auditing. Internal Auditor, Spring, 3–10. Committee of Sponsoring Organizations of the Treadway Commission. (1992). Internal control-integrated framework. American Institute of Certified Public Accountants. Dai, J., & Vasarhelyi, M. A. (2017). Toward blockchain-based accounting and assurance. Journal of Information Systems, 31(3), 5–21. Davenport, T. H., & Kirby, J. (2016). Only humans need apply: Winners and losers in the age of smart machines. Harper Business. Debreceny, R., Gray, G. L., & Rahman, A. (2005). The determinants of Internet financial reporting. Journal of Accounting and Public Policy, 24(2), 123–163. Dowling, C., & Leech, S. A. (2014). A Big 4 firm's use of information technology to control the audit process: How an audit support system is changing auditor behavior. Contemporary Accounting Research, 31(1), 230–252. Earley, C. E. (2001). Knowledge acquisition in auditing: Training novice auditors to recognize cue relationships in real estate valuation. The Accounting Review, 76(1), 81–97. Earley, C. E. (2015). Data analytics in auditing: Opportunities and challenges. Business Horizons, 58(5), 493–500. Eilifsen, A., Messier, W. F., Glover, S. M., & Prawitt, D. F. (2001). Auditing and assurance services. McGraw-Hill. Ge, W., & McVay, S. (2005). The disclosure of material weaknesses in internal control after the Sarbanes-Oxley Act. The Accounting Review, 80(3), 803–823. Geda, A. (2023). Advancing rural welfare: The role of irrigation technology in Ethiopia's agricultural sector. Journal of Business and Economic Options, 6(2). Groomer, S. M., & Murthy, U. S. (1989). Continuous auditing of database applications: An embedded audit module approach. Journal of Information Systems, 3(2), 53–69. Hamdy, A., Diab, A., & Eissa, A. M. (2025). Digital transformation and the quality of accounting information systems in the public sector: Evidence from developing countries. International Journal of Financial Studies, 13(1), 30–45. Hasan, A. R. (2021). Artificial intelligence (AI) in accounting and auditing: A literature review. Open Journal of Business and Management, 10(1), 440–465. Hossain, M. A., Karim, S., & Akhter, N. (2023). Impact of regulatory policies on the financial performance of Bangladeshi banks: A panel data analysis. South Asian Journal of Banking and Finance, 10(1), 45–62. IIA (Institute of Internal Auditors). (2016). Global Internal Audit Common Body of Knowledge (CBOK) survey results. Altamonte Springs, FL: IIA Research Foundation. Intacct Corp. (2000). Web-based audit program is developed with Deloitte. Wall Street Journal, June 26, p. A13. 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. Jamel, M., & Zhang, C. (2024). Green finance, financial technology, and environmental innovation impact on CO₂ emissions in developed countries. Journal of Energy and Environmental Policy Options, 7(3). Jędrzejka, D. (2019). Robotic process automation and its impact on accounting. Zeszyty Teoretyczne Rachunkowości, 105, 137–166. Karhan, G. (2019). Investing in research and development for technological innovation: A strategy for Turkey's economic growth. Journal of Business and Economic Options, 2(4). Knechel, W. R., & Salterio, S. E. (2016). Auditing: Assurance and risk. Routledge. Koch, H. S. (1981). On-line computer auditing through continuous and intermittent simulation. MIS Quarterly, March, 29–41. 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. Kuenkaikaew, S., & Vasarhelyi, M. A. (2013). The utility of continuous auditing in fraud detection. Journal of Emerging Technologies in Accounting, 10(1), 1–15. Kuhn, J. R., & Sutton, S. G. (2010). Continuous auditing in ERP system environments: The current state and future directions. Journal of Information Systems, 24(1), 91–112. Liu, Q., Chen, C., & Wang, Y. (2023). Artificial intelligence in financial auditing: Enhancing accuracy and audit cycle efficiency. Journal of Emerging Technologies in Accounting, 20(2), 127–146. Liu, Q., Wang, H., & Wu, L. (2020). Artificial intelligence applications in the accounting industry: Opportunities and challenges. Accounting Research, 10(4), 36–45. Ma, J., Lin, W., & Zhao, K. (2025). Robotic process automation and continuous auditing: Enhancing real-time accuracy in financial control systems. Journal of Information Systems and Technology Management, 41(1), 55–70. Mate, A. (2022). The impact of internal audits on corporate fraud detection and mitigation. Journal of Policy Options, 5(3). Mock, T. J., & Turner, J. L. (2005). Auditor identification of and responses to audit process deficiencies. Behavioral Research in Accounting, 17(1), 51–70. Mock, T. J., & Wright, A. M. (1999). Are audit program plans risk adjusted? Auditing: A Journal of Practice & Theory, 18(1), 55–74. 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. Moretti, M., & Wamba, S. F. (2024). Blockchain technology in financial reporting: Evidence from European companies. International Journal of Accounting Information Systems, 53, 100609. Murphy, D., & Tysiac, K. (2015). The next evolution in auditing. Journal of Accountancy, 219(5), 42–47. Murthy, U. S., & Groomer, S. M. (2004). A continuous auditing web services model for XML-based accounting systems. International Journal of Accounting Information Systems, 5(2), 139–163. O’Leary, D. E. (2023). Digitization, digitalization, and digital transformation in accounting, electronic commerce, and supply chains. Intelligent Systems in Accounting, Finance and Management, 30(2), 101–110. O’Leary, D. E., & O’Keefe, R. M. (1997). The impact of artificial intelligence in accounting work: Expert systems use in auditing and tax. AI & Society, 11, 36–47. Owusu, F., & Novignon, J. (2021). Exploring the benefits and challenges of mobile technology in Ghanaian small-scale enterprises. Journal of Policy Options, 4(1). PwC (PricewaterhouseCoopers). (2017). State of the Internal Audit Profession Study: Elevating Internal Audit’s Role. New York, NY: PwC. Qasim, A., & Kharbat, F. F. (2020). Blockchain technology, business data analytics, and artificial intelligence: Use in the accounting profession and ideas for inclusion into the accounting curriculum. Journal of Emerging Technologies in Accounting, 17(1), 107–117. Qasim, M., & Su, W. (2022). Technology transfer and economic growth through foreign direct investment in transition economies. Journal of Policy Options, 5(2). Rezaee, Z., Elam, R., & Sharbatoghlie, A. (2001). Continuous auditing: The audit of the future. Managerial Auditing Journal, 16(3), 150–158. Rezaee, Z., Ford, W. F., & Elam, R. (2000). The role of internal auditors in a real-time accounting system. Internal Auditor, April, 62–67. Richins, G., Stapleton, R., Stratopoulos, T., & Wong, C. (2017). Big data analytics: Opportunity or threat for the accounting profession? Journal of Information Systems, 31(3), 63–79. Rozario, A. M., & Vasarhelyi, M. A. (2018). How artificial intelligence is changing auditing. Journal of Emerging Technologies in Accounting, 15(1), 1–20. Salleh, I., & Sapengin, F. (2023). Exploring the impact of technological capability on inter-firm relationships in Malaysian manufacturing supply chains. Journal of Policy Options, 6(4). Sangster, A., Leoni, G., & Vollstedt, J. (2020). Training accounting students in analytics: Evidence from a longitudinal study. Accounting Education, 29(3), 289–306. Sanoran, K., & Ruangprapun, J. (2023). Initial implementation of data analytics and audit process management. Sustainability, 15(3), 1766. Schmidt, G. B., Spector, P. E., & Brodie, J. (2016). Workforce automation: A strategic HR challenge. Organizational Dynamics, 45(3), 185–190. Searle, R. (2018). Cognitive bias and AI systems. AI & Society, 33(4), 565–573. Sutton, S. G., Holt, M., & Arnold, V. (2016). The reports of my death are greatly exaggerated—Artificial intelligence research in accounting. International Journal of Accounting Information Systems, 22, 60–73. Tila, G., & Cera, D. (2021). Information and communication technologies integration and usage patterns among university students. Journal of Policy Options, 4(1). Tiron-Tudor, A., Deliu, D., Farcane, N., & Şuşnea, C. (2018). Managing change with and through stakeholder engagement: Evidence from the implementation of audit analytics. Journal of Accounting and Management Information Systems, 17(2), 248–276. van Zanden, J. L. (2023). Examining the relationship of information and communication technology and financial access in Africa. Journal of Business and Economic Options, 6(3). Vasarhelyi, M. A., & Halper, F. B. (1991). The continuous audit of online systems. Auditing: A Journal of Practice & Theory, 10(1), 110–125. Vasarhelyi, M. A., & Kuenkaikaew, S. (2020). Continuous auditing: Theory and application in a world of big data. Journal of Emerging Technologies in Accounting, 17(2), 55–67. Vasarhelyi, M. A., Kogan, A., & Tuttle, B. M. (2015). Big data in accounting: An overview. Accounting Horizons, 29(2), 381–396. Warren, J. D., Moffitt, K. C., & Byrnes, P. (2015). How big data will change accounting. Accounting Horizons, 29(2), 397–407. Wessels, P. L. (2005). Critical information and communication technology (ICT) skills for professional accountants. Meditari Accountancy Research, 13(1), 87–103. Yermack, D. (2017). Corporate governance and blockchains. Review of Finance, 21(1), 7–31. Yoon, H. G., Zo, H., & Ciganek, A. P. (2011). Does XBRL adoption reduce information asymmetry? Journal of Business Research, 64(2), 157–163. Yoon, K., Hoogduin, L., & Zhang, L. (2015). Big data as complementary audit evidence. Accounting Horizons, 29(2), 431–438. Yuen, D. C., Law, P., Lu, C., & Guan, J. (2018). The redefined role of accountants in the era of artificial intelligence. Asian Review of Accounting, 26(3), 413–430. Zarowin, S., & Harding, W. E. (2000). Finally, business talks the same language. Journal of Accountancy, August, 24–30. Zemánková, A. (2019). Artificial intelligence and blockchain in audit and accounting: Literature review. WSEAS Transactions on Business and Economics, 16, 568–581. Zhang, J., Yang, J., & Appelbaum, D. (2015). Toward effective big data analysis in continuous auditing. Accounting Horizons, 33(3), 121–140. Zhang, P., Yang, S., & Appelbaum, D. (2017). Toward effective use of big data in auditing. Journal of Information Systems, 31(3), 153–165. Zhang, Y., Xiong, F., Xie, Y., Fan, X., & Gu, H. (2020). The impact of artificial intelligence and blockchain on the accounting profession. IEEE Access, 8, 110461–110477. |
| URI: | https://mpra.ub.uni-muenchen.de/id/eprint/127319 |

