Digital Transformation of Financial Auditing Through Automated Evidence Management and Regulatory Compliance
DOI:
https://doi.org/10.63282/3117-5481/AIJCST-V7I6P116Keywords:
Financial Auditing, Digital Transformation, Automated Evidence Management, Regulatory Compliance, Artificial Intelligence, Robotic Process Automation, Audit AnalyticsAbstract
The traditional auditing which was performed on the basis of computerized evidences, smart information processing and technology of compliance with regulations is undergoing transformation to computerization of financial auditing. The traditional approaches to auditing usually include manual records, disjointed records archives, confirmation of time wasted and issues with consistent record keeping of regulations. The present paper suggests the conceptual elaboration of creating the financial auditing, by incorporating it with the automated system of managing its evidence and compliance mechanisms applied. The system has artificial intelligence and robot process automation along with cloud-based document management, blockchain-traceable and regulatory analytics to reinforce the collection and classification, and authentication as well as storage and recovery of audit evidence. It also raises the issue of the involvement of the regulatory requirements in the automated audit work legislations, as a way to ensure compliance management is an ongoing process, risk identification, transparency and accountability. The proposed solution has laid out the interrelationships among the additions of the layers of functions, which involve the acquisition of financial information, evidence collection, analysis of audit and reporting compliance. Incorporate special consideration on information security, data integrity, and maintenance of audit trail, interoperability and human controls. The framework is conceptually learned based on the key aspects in the performance of audit, flexibility of the regulators, transparency of the activity of the framework, effectiveness of the governance in the framework. The article will provide insights on how intelligent automation can impact the quality of an audit, decrease disparate documentation and ensure timely reporting on the claims side by the regulation. It also presents obstacles to the implementation, future research directions to come up with a safe, scalable and explainable digital auditing ecosystem.
References
[1] Qader, K. S., & Cek, K. (2024). Influence of blockchain and artificial intelligence on audit quality: Evidence from Turkey. Heliyon, 10(9), Article e30166. https://doi.org/10.1016/j.heliyon.2024.e30166
[2] 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
[3] Abu Huson, Y., Sierra-García, L., & García-Benau, M. A. (2024). A bibliometric review of information technology, artificial intelligence, and blockchain on auditing. Total Quality Management & Business Excellence, 35(1–2), 91–113. https://doi.org/10.1080/14783363.2023.2256260
[4] 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
[5] Han, H., Shiwakoti, R. K., Jarvis, R., Mordi, C., & Botchie, D. (2023). Accounting and auditing with blockchain technology and artificial intelligence: A literature review. International Journal of Accounting Information Systems, 48, Article 100598. https://doi.org/10.1016/j.accinf.2022.100598
[6] Valavala, S. K. (2024). From application logs to audit evidence in financial microservices. International Journal of Research and Applied Innovations, 7(4), 11246–11256.
[7] 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
[8] Lee, H., Zhang, L., Liu, Q., & Vasarhelyi, M. (2022). Text visual analysis in auditing: Data analytics for journal entries testing. International Journal of Accounting Information Systems, 47, Article 100571. https://doi.org/10.1016/j.accinf.2022.100571
[9] Zhang, C. A., Thomas, C., & Vasarhelyi, M. (2022). Attended process automation in audit: A framework and a demonstration. Journal of Information Systems, 36(2), 101–124. https://doi.org/10.2308/ISYS-2020-073
[10] Sargent, C. S. (2022). Replacing financial audits with blockchain: The verification issue. Journal of Computer Information Systems, 62(6), 1145–1153. https://doi.org/10.1080/08874417.2021.1992805
[11] Werner, M., Wiese, M., & Maas, A. (2021). Embedding process mining into financial statement audits. International Journal of Accounting Information Systems, 41, Article 100514. https://doi.org/10.1016/j.accinf.2021.100514
[12] Dyball, M. C. (2021). The impact of client use of blockchain technology on audit risk and audit approach—An exploratory study. International Journal of Auditing, 25(2), 602–615. https://doi.org/10.1111/ijau.12238
[13] Yoon, K., Liu, Y., Chiu, T., & Vasarhelyi, M. A. (2021). Design and evaluation of an advanced continuous data level auditing system: A three-layer structure. International Journal of Accounting Information Systems, 42, Article 100524. https://doi.org/10.1016/j.accinf.2021.100524
[14] Rakipi, R., De Santis, F., & D’Onza, G. (2021). Correlates of the internal audit function’s use of data analytics in the big data era: Global evidence. Journal of International Accounting, Auditing and Taxation, 42, Article 100357. https://doi.org/10.1016/j.intaccaudtax.2020.100357
[15] Ashraf, M., Michas, P. N., & Russomanno, D. (2020). The impact of audit committee information technology expertise on the reliability and timeliness of financial reporting. The Accounting Review, 95(5), 23–56. https://doi.org/10.2308/accr-52622
