Leveraging RPA for enhancing audit efficiency: Insights and challenges in the audit landscape
1 Southern Illinois University Carbondale, IL, United States.
2 KPMG, Bangladesh.
3 Daraz Bangladesh Limited, Bangladesh.
4 Jahangirnagar University, Bangladesh.
5 Certified Information Systems Auditor (CISA), USA.
6 Oklahoma State University, Stillwater, OK, United States.
7 University of Dhaka, Bangladesh.
8 Dentsu X.
Review
World Journal of Advanced Engineering Technology and Sciences, 2024, 13(02), 671-677.
Article DOI: 10.30574/wjaets.2024.13.2.0653
Publication history:
Received on 18 November 2024; revised on 28 December 2024; accepted on 30 December 2024
Abstract:
The adoption of Robotic Process Automation (RPA) in auditing has emerged as a transformative trend, offering significant potential to enhance efficiency, accuracy, and overall audit effectiveness. This study explores the integration of RPA in auditing processes, identifying key areas where automation can streamline workflows and reduce human errors. Drawing from a qualitative research approach, semi-structured interviews were conducted with 15 professionals across diverse audit sectors, uncovering insights into the benefits, challenges, and strategic implications of RPA adoption. The findings reveal that RPA reduces routine task completion times by up to 50%, improves data accuracy by 40%, and delivers a 120% return on investment within two years. However, challenges such as resistance to change, skill gaps, and compatibility with legacy systems persist. This research highlights the necessity of effective change management, continuous skill development, and ethical governance to maximize RPA's potential. By addressing these challenges, this study provides actionable recommendations for leveraging RPA to revolutionize audit practices, enabling organizations to adapt to an evolving technological landscape.
Keywords:
Robotic Process Automation (RPA); Audit Efficiency; Automation in Auditing; RPA Challenges; Digital Transformation in Auditing; RPA Cost-Benefit Analysis
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0