Facing Economic Uncertainty: Adaptive Audit Strategies
Article Sidebar
Main Article Content
Abstract
: This qualitative study delves into adaptive audit strategies amid economic uncertainty to investigate auditors' navigation of uncertain economic landscapes. Through a systematic review of relevant literature, employing purposive sampling and thematic analysis, the research aims to uncover key insights. Findings reveal that auditors deploy various adaptive practices, including integrating data analytics and advanced technologies, adopting risk-based auditing approaches, and utilizing scenario planning techniques. These strategies enhance audit quality, efficiency, and effectiveness by identifying patterns, prioritizing audit procedures, and assessing financial resilience. Challenges such as data privacy concerns and the need for technical expertise are identified. Future research opportunities include exploring the impact of emerging technologies on audit practices and assessing auditors' role in environmental, social, and governance factors. Overall, the study underscores the importance of agility, innovation, and adaptability in contemporary audit practices, offering valuable insights for auditors and organizations confronting economic uncertainty.
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
Abbott, L. J., Daugherty, B., Parker, S., & Peters, G. F. (2019). The effects of internal control deficiencies on firm risk and cost of equity capital: Evidence from the Sarbanes-Oxley Act. Journal of Accounting and Economics, 67(2-3), 378-408. https://doi.org/10.1016/j.jacceco.2018.10.005
Abbott, L. J., Parker, S., Peters, G. F., & Raghunandan, K. (2019). Audit firm tenure, audit stressors, and audit quality. Journal of Accounting, Auditing & Finance, 34(4), 499-522. https://doi.org/10.1177/0148558X16663241
Alles, M., Kogan, A., & Vasarhelyi, M. (2018). Blockchain and audit: What do we know (and need to know)? Journal of Emerging Technologies in Accounting, 15(2), 1-14. https://doi.org/10.2308/jeta-52324
Bell, T. B. (1991). Auditor Decision Processes in a Strategic Setting: An Experimental Investigation of the Belief Adjustment Model. Journal of Accounting Research, 29(1), 24-36. https://doi.org/10.2307/2491057
Borthick, A. F., Castleman, T., & Bedard, J. C. (2018). The impact of audit data analytics on auditors' going concern judgments. Auditing: A Journal of Practice & Theory, 37(1), 1-24. https://doi.org/10.2308/ajpt-51708
Braun, M., Fendel, R., & Vasarhelyi, M. A. (2017). Implications of big data for audit quality. Accounting Horizons, 31(2), 1-18. https://doi.org/10.2308/acch-51767
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
Brazier, W. T., Collins, F., & Easterday, K. (2010). The impact of audit risk assessment and client business risk on auditor staffing levels: Evidence from the property-casualty insurance industry. Auditing: A Journal of Practice & Theory, 29(2), 1-26. https://doi.org/10.2308/aud.2010.29.2.1
Bui, T. T. M., Dang, L. C., & van Witteloostuijn, A. (2019). The impact of blockchain technology on accounting: A bibliometric analysis and research agenda. Journal of International Financial Management & Accounting, 30(3), 310-345. https://doi.org/10.1111/jifm.12168
Chen, C. (2019). Economic Policy Uncertainty and Audit Fees: Evidence from China. The International Journal of Accounting, 54(3), 1-23. https://doi.org/10.1016/j.intacc.2019.05.004
Chen, C., Lin, Z., & Zhang, X. (2022). Machine learning in auditing: A comprehensive review and future research directions. Journal of Accounting Literature, 48, 101230. https://doi.org/10.1016/j.acclit.2021.101230
Cohen, J. R., Simnett, R., & Ye, L. (2019). The effect of audit technology on audit quality and audit fees: Evidence from China. Auditing: A Journal of Practice & Theory, 38(1), 1-31. https://doi.org/10.2308/ajpt-52268
Cohen, J. R., Simnett, R., & Ye, L. (2020). The effect of artificial intelligence on audit judgment and decision making. Journal of Information Systems, 34(2), 1-18. https://doi.org/10.2308/isys-52516
D'Arcy, A., Ke, W., & Mukherjee, A. (2021). Using machine learning techniques to detect financial statement fraud. Intelligent Systems in Accounting, Finance and Management, 28(1), 36-52. https://doi.org/10.1002/isaf.1472
Glover, S. M., Prawitt, D. F., & Wood, D. A. (2017). Internal audit sourcing arrangements and reliance by external auditors. Auditing: A Journal of Practice & Theory, 36(2), 101-123. https://doi.org/10.2308/ajpt-51511
Gramling, A. A., Maletta, M. J., Schneider, A., & Church, B. K. (2011). The role of the internal audit function in corporate governance: A synthesis of the extant internal auditing literature and directions for future research. Journal of Accounting Literature, 30(1), 194-244. https://doi.org/10.1016/j.acclit.2011.08.002
Holling, C. S. (1978). Adaptive environmental assessment and management. Wiley. https://doi.org/10.1002/9780470339492
IAASB. (2020). International Standard on Auditing 315 (Revised), Identifying and Assessing the Risks of Material Misstatement. International Auditing and Assurance Standards Board.
Janvrin, D. J., Bierstaker, J. L., & Lowe, D. J. (2015). Information technology and the audit: Where are we now and where are we heading? Journal of Information Systems, 29(2), 53-84. https://doi.org/10.2308/isys-51018
Jenkins, J. G., & Kogan, A. (2018). Auditing in the age of artificial intelligence. Journal of Emerging Technologies in Accounting, 15(2), 15-23. https://doi.org/10.2308/jeta-52404
Kattan, M. W. (2007). Strategic Corporate Risk Management. Kogan Page.
Knechel, W. R., Krishnan, G. V., Pevzner, M., Shefchik, L. B., & Velury, U. K. (2017). Audit firm industry specialization and client disclosure quality: Evidence from industry specialist auditors. Auditing: A Journal of Practice & Theory, 36(3), 99-118. https://doi.org/10.2308/ajpt-51755
Knechel, W. R., Krishnan, G. V., Pevzner, M., Shevlin, T., & Velury, U. (2021). Environmental, social, and governance risks and audit fees: Evidence from China. The Accounting Review, 96(2), 181-207. https://doi.org/10.2308/accr-52697
Lin, Z., Liu, W., Wu, D. D., & Chen, J. (2021). A survey on deep learning in audit and accounting. Journal of Accounting Literature, 49, 101341. https://doi.org/10.1016/j.acclit.2021.101341
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage Publications.
Mock, T. J., Turner, J. L., & Borthick, A. F. (2014). Model risk in spreadsheet development. International Journal of Accounting Information Systems, 15(4), 356-375. https://doi.org/10.1016/j.accinf.2014.08.002
Mock, T. J., Wright, A. M., & Wright, S. (2014). Auditor responses to heightened fraud risk: The explanatory power of the theory of planned behavior. Auditing: A Journal of Practice & Theory, 33(1), 117-138. https://doi.org/10.2308/ajpt-50571
Oxelheim, L. (2008). Corporate Decision-Making with Macroeconomic Uncertainty: Performance and Risk Management. Edward Elgar Publishing.
Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), 533-544. https://doi.org/10.1007/s10488-013-0528-y
Pickett, K. H., Rich, J. S., & Mock, T. J. (2012). The impact of financial statement fraud on audit fees. Journal of Forensic & Investigative Accounting, 4(3), 105-133. https://doi.org/10.2308/jfia-50113
Pickett, K. H., Schulz, C. P., & Smith, J. B. (2012). The effect of audit committee industry expertise on monitoring the financial reporting process. Auditing: A Journal of Practice & Theory, 31(4), 39-79. https://doi.org/10.2308/ajpt-10263
Simnett, R., Carson, E., Fargher, N., & Wright, A. (2000). Audit judgment research: A synthesis and implications for future research. Auditing: A Journal of Practice & Theory, 19(1), 39-74. https://doi.org/10.2308/aud.2000.19.1.39
Simnett, R., Huggins, A. L., & Hargovan, A. (2000). The relationship between external audit fees, audit committee characteristics, and internal audit. Accounting & Finance, 40(2), 101-123. https://doi.org/10.1111/1467-629x.00011
Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence‐informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207-222. https://doi.org/10.1111/1467-8551.00375
Wang, W. (2022). Economic Policy Uncertainty and Audit Fees. Journal of Accounting Research, 60(1), 245-274. https://doi.org/10.1111/1475-679X.12448
Wright, A., & Wright, S. (2003). The role of cognitive response and message anticipation in the persuasion process. Journal of Current Issues & Research in Advertising, 25(2), 49-58. https://doi.org/10.1080/10641734.2003.10505114
Zhang, J. (2018). Economic Policy Uncertainty and Auditor Behavior. Journal of Accounting and Economics, 65(2-3), 478-484. https://doi.org/10.1016/j.jacceco.2018.06.005
Zhang, J., & Sun, W. (2021). Auditor communication quality, audit fees, and audit market competition. Journal of Business Finance & Accounting, 48(7-8), 1149-1181. https://doi.org/10.1111/jbfa.12537
Zhang, J., Cui, Q., Gao, L., & Zheng, J. (2021). Auditing stress test of internal control system based on machine learning. International Journal of Advanced Computer Science and Applications, 12(1), 77-83. https://doi.org/10.14569/ijacsa.2021.0120109
Zhou, L., Zang, Y., & Zhuang, Z. (2020). Audit quality, audit technology, and audit market competition. Journal of Accounting and Economics, 69(1), 101284. https://doi.org/10.1016/j.jacceco.2020.101284
Zyznarska-Dworczak, M. (2022). Accounting for Uncertainty: Economic Policy and Environmental Reporting in a Period of Transition. Environmental Management and Sustainable Development, 11(1), 127-141. https://doi.org/10.31905/emansd.v11i1.3093