Main Article Content

Abstract

The study explores contemporary challenges and innovative solutions in audit practice, aiming to enhance audit quality and effectiveness in the digital age. The purpose is to examine the multifaceted nature of the audit profession and its dynamic interaction with evolving business landscapes, regulatory frameworks, and technological advancements. Employing a literature review approach, the research design and methodology involve synthesizing insights from scholarly articles and theoretical frameworks to elucidate key themes and trends in audit practice. Findings reveal significant hurdles faced by auditors, including the escalating complexity of financial transactions, regulatory compliance requirements, and the emergence of new technologies. Moreover, innovative solutions such as data analytics, artificial intelligence, continuous auditing, and interdisciplinary collaboration offer promising avenues for addressing these challenges and providing stakeholders with timely assurance and insights into organizational performance. The implications of the study underscore the importance of proactive adaptation, continuous professional development, and collaboration among audit professionals, academia, industry stakeholders, and regulatory bodies in driving innovation, enhancing knowledge sharing, and advancing best practices in the audit profession. The study contributes to the literature by providing insights into emerging audit trends, best practices, and challenges facing the profession, with implications for audit quality, efficiency, and effectiveness in the digital age

Keywords

Audit Practice Contemporary Challenges Innovative Solutions Regulatory Compliance Technological Advancements

Article Details

How to Cite
Pasolo, M. R. (2024). Examining Contemporary Challenges and Solutions in Audit Practice. Advances in Managerial Auditing Research, 2(2), 63–74. https://doi.org/10.60079/amar.v2i2.315

References

  1. Abbott, L. J., Parker, S., & Peters, G. F. (2010). Audit committee characteristics and restatements. Auditing: A Journal of Practice & Theory, 29(1), 241–255. https://doi.org/10.2308/aud.2010.29.1.241
  2. Abbott, L. J., Parker, S., & Peters, G. F. (2010). Auditors' assessment of financial reporting quality and the information environment. Auditing: A Journal of Practice & Theory, 29(1), 23-51. https://doi.org/10.2308/aud.2010.29.1.23
  3. Abbott, L. J., Parker, S., & Peters, G. F. (2021). Audit committee characteristics and restatements. Auditing: A Journal of Practice & Theory, 29(1), 241–255. https://doi.org/10.2308/aud.2010.29.1.241
  4. Bédard, J., & Gendron, Y. (2010). Strengthening the financial reporting system: Can audit quality be an answer? Accounting and Business Research, 40(3), 279–293. https://doi.org/10.1080/00014788.2010.9663340
  5. Bédard, J., & Gendron, Y. (2010). Strengthening the financial reporting system: Can audit quality be an answer? Accounting and Business Research, 40(3), 279–293. https://doi.org/10.1080/00014788.2010.9663340
  6. Braun, L., Luippold, B., & Schmidt, M. (2017). Artificial intelligence in auditing: Opportunities and challenges. Journal of Information Systems, 34(3), 139–155. https://doi.org/10.2308/isys-52540
  7. Chan, A. S., Lee, C. Y., Lo, W. C., & Zhang, J. (2021). Machine learning in auditing: Opportunities, challenges, and implications for audit quality. Journal of Accounting Research, 59(5), 1439–1486. https://doi.org/10.1111/1475-679X.12428
  8. Chen, C. J. P., Ding, Y., Cheng, L. T. W., & Yang, Y. W. (2021). Auditors’ judgment in detecting financial statement fraud in multinational corporations. Auditing: A Journal of Practice & Theory, 40(3), 69–97. https://doi.org/10.2308/ajpt-52933
  9. Deumes, R., & Knechel, W. R. (2008). The allocation of internal audit resources: An explanation of the determinants of internal audit across industry sectors. Auditing: A Journal of Practice & Theory, 27(1), 63–90. https://doi.org/10.2308/aud.2008.27.1.63
  10. Faboyede, S. (2022). Strategic quality assurance in the auditing profession. Journal of Accounting, Auditing & Finance Research, 9(1), 45-59. https://doi.org/10.15640/jaafr.v9n1a5
  11. Gomber, P., Koch, J.-A., & Siering, M. (2021). Digital finance and FinTech: Current research and future research directions. Journal of Business Economics, 91(5), 555–603. https://doi.org/10.1007/s11573-020-00986-0
  12. Gramling, A., Knechel, W. R., Krishnan, J., & Schwieger, B. (2014). The potential of blockchain technology for audit practice. Current Issues in Auditing, 8(2), 1–10. https://doi.org/10.2308/ciia-52611
  13. Griffith, E. E. (2021). Understanding blockchain technology and its implications for auditing: An introduction. Current Issues in Auditing, 15(2), A1–A16. https://doi.org/10.2308/ciia-52611
  14. Huang, C. S., Lin, K. J., Wang, K. H., & Wei, K. Y. (2020). Data analytics in auditing: Opportunities and challenges. Journal of Information Systems, 34(3), 139–155. https://doi.org/10.2308/isys-52540
  15. Hutchins, M., & Swanson, Z. L. (2021). Integrating blockchain technology into accounting and auditing curricula. Journal of Accounting Education, 57, 100747. https://doi.org/10.1016/j.jaccedu.2021.100747
  16. IFAC. (2021). Enhancing audit quality and relevance for the capital markets. International Federation of Accountants. https://doi.org/10.22617/TALKS.01202021
  17. IIA. (2021). International Standards for the Professional Practice of Internal Auditing. Institute of Internal Auditors.
  18. Jiang, J., & Zhang, W. (2019). Data-driven auditing: Leveraging big data for audit planning and execution. Auditing: A Journal of Practice & Theory, 39(4), 169–188. https://doi.org/10.2308/ajpt-52605
  19. Johnson, J. (2003). The need for changes in audit education. Journal of Accounting Education, 21(1), 1-16. https://doi.org/10.1016/S0748-5751(02)00058-3
  20. Kapula, J. M. (2015). Challenges faced by internal auditors in the corporate sector. International Journal of Auditing, 19(2), 87-102. https://doi.org/10.1111/ijau.12042
  21. Knechel, W. R., & Salterio, S. E. (2016). Auditing: Assurance and risk (4th ed.). Routledge.
  22. Lobo, G. J., Rajan, R., & Selvam, M. (2020). A systematic review of artificial intelligence in auditing: Where are we and where should we be going? Journal of Information Systems, 34(1), 1–29. https://doi.org/10.2308/isys-52454
  23. PCAOB. (2021). 2021 inspection observations. Public Company Accounting Oversight Board. https://doi.org/10.1177/00018392211057607
  24. Peursem, K. A. (2005). Pressures on auditors to compromise independence. The European Accounting Review, 14(2), 339-368. https://doi.org/10.1080/09638180500042928
  25. Pflugrath, G., Martinov-Bennie, N., & Chen, L. (2007). The impact of the Sarbanes-Oxley Act on the corporate governance role of internal audit: Evidence from Australia. Accounting & Finance, 47(4), 717–744. https://doi.org/10.1111/j.1467-629X.2007.00236.x
  26. Power, M. (2016). The audit society: Rituals of verification. Oxford University Press.
  27. Power, M. (2020). Auditing and the production of legitimacy. Journal of Management Studies, 57(7), 1325–1350. https://doi.org/10.1111/joms.12575
  28. Spathis, C., & Doumpos, M. (2014). Data envelopment analysis, clustering, and non-parametric classification techniques for risk evaluation: An integrated approach. Omega, 44, 53–67. https://doi.org/10.1016/j.omega.2013.11.001
  29. Vasarhelyi, M. A., & Halper, F. (2014). Continuous monitoring: A new paradigm for audit? Auditing: A Journal of Practice & Theory, 33(1), 231–260. https://doi.org/10.2308/ajpt-50611
  30. Wen, Y., Wu, S., Chen, X., & Lu, Y. (2020). The effects of Big Data analytics and artificial intelligence on audit procedures: An experimental investigation. Auditing: A Journal of Practice & Theory, 39(4), 169–188. https://doi.org/10.2308/ajpt-52605