Impact of artificial intelligence using the robotic process automation system on the efficiency of internal audit operations at Jordanian commercial banks
-
Author(s)Abdalla AlassuliLink to ORCID Index: https://orcid.org/0000-0001-9685-8324
-
DOIhttp://dx.doi.org/10.21511/bbs.20(1).2025.11
-
Article InfoVolume 20 2025, Issue #1, pp. 122-135
- 7 Views
-
0 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
This study aims to examine the impact of artificial intelligence through robotic process automation systems on internal audit operation efficiency in Jordanian commercial banks. The study uses a descriptive methodology to evaluate how robotic process automation systems enhance the different dimensions of internal audit efficiency: planning, management, execution, and communication. The study designed a structured questionnaire for data collection. The sample consisted of 12 commercial bank employees whose working processes are directly affected by robotic process automation system procedures which puts them in a unique position to comment on the practical applicability of this technology and its implications for internal audit. In this study, 480 electronic questionnaires were distributed via Google Forms, and 390 completed forms were collected for further analysis. The study employs descriptive statistics and advanced statistical techniques, such as linear regression analysis, for data analysis. The findings indicate that robotic process automation systems enhance the internal audit process by reducing the cost of operations, eliminating human errors, and smoothing work processes. The robotic process automation system will allow continuous auditing, real-time risk management, and proper reporting; hence, it will change the role of internal auditors and, in the end, improve organizational compliance and performance. This study asserts that the banking industry must integrate AI-driven automation to maintain its competitiveness in the constantly changing financial landscape.
- Keywords
-
JEL Classification (Paper profile tab)G21, M42, M15, O31
-
References51
-
Tables10
-
Figures0
-
- Table 1. Sample distribution
- Table 2. Reliability test
- Table 3. Means and standard deviations of artificial intelligence using the RPAS items, descending ranked order
- Table 4. Means and standard deviations for the efficiency of internal audit operations, in descending ranked order
- Table 5. Means and standard deviations for the efficiency of internal audit operations
- Table 6. Simple regression analysis for the impact of artificial intelligence using the RPAS in the efficiency of internal audit operations
- Table 7. Simple regression analysis for the impact of artificial intelligence using the RPAS on the quality of internal audit activity management
- Table 8. Simple regression analysis for the impact of artificial intelligence using the RPAS on the quality of planning dimension
- Table 9. Simple regression analysis results for the impact of artificial intelligence using the RPAS on the quality of audit engagement execution
- Table 10. Simple regression analysis for the impact of artificial intelligence using the RPAS on the quality of results communication
-
- Abousweilem, F., Alzghoul, A., Khaddam, A. A., & Khaddam, L. A. (2023). Revealing the effects of business intelligence tools on technostress and withdrawal behavior: The context of a developing country. Information Development, 02666669231207592.
- Ahmad, A. Y. A. B., Abusaimeh, H., Rababah, A., Alqsass, M., Al-Olima, N., & Hamdan, M. (2024). Assessment of effects in advances of accounting technologies on quality financial reports in Jordanian public sector. Uncertain Supply Chain Management, 12(1), 133-142.
- Alawaqleh, Q. A. (2021). Impact of Accounting Information System on Internal Audit Quality: Mediating Role of Organizational Culture. International Journal of Financial Research, 12(1), 205-213.
- Alkasasbeh, O. M., Alassuli, A., & Alzghoul, A. (2022). Energy consumption, economic growth and CO2 emissions in Middle East. International Journal of Energy Economics and Policy, 13(1), 322-327.
- Al-Kasasbeh, O., Khasawneh, O., & Alzghoul, A. (2023). The real effects of FinTech on the global financial system. International Journal of Professional Business Review, 8(3), e01725.
- Almaliki, O. J. (2021). The Effect of Accounting Information System On Internal Audit Effectiveness with Moderating Effect of Experience: A Measurement Model. The Middle East International Journal for Social Sciences, 3(3), 216-226.
- Alqudah, H., Lutfi, A., Abualoush, S. H., Al Qudah, M. Z., Alshira’h, A. F., Almaiah, M. A., Alrawad, M., & Tork, M. E. A. (2023). The impact of empowering internal auditors on the quality of electronic internal audits: A case of Jordanian listed services companies. International Journal of Information Management Data Insights, 3(2), 100183.
- Alrabei, A. M. (2021). The Influence of Accounting Information Systems in Enhancing the Efficiency of Internal Control at Jordanian Commercial Banks. Journal of Management Information and Decision Sciences, 24(1), 1-9.
- Alsabti, H. A., & Khalid, A. A. (2021). The Impact of Accounting Information System on Internal Audit Effectiveness in Companies Listed in Muscat Securities Market. Philosophical Readings, 13(4), 1478-1495.
- Alsabti, H. A., & Khalid, A. A. (2022). Factors Influencing Internal Accounting and Financial Audit Effectiveness: Evidence from Oman. Academy of Accounting and Financial Studies Journal, 26, 1-11.
- Alzghoul, A., Khaddam, A. A., Abousweilem, F., Irtaimeh, H. J., & Alshaar, Q. (2024). How business intelligence capability impacts decision-making speed, comprehensiveness, and firm performance. Information Development, 40(2), 220-233.
- Ayinla, B. S., Atadoga, A., Ike, C. U., Ndubuisi, N. L., Asuzu, O. F., & Adeleye, R. A. (2024). The Role of Robotic Process Automation (RPA) in Modern Accounting: A Review-Investigating How Automation Tools are Transforming Traditional Accounting Practices. Engineering Science & Technology Journal, 5(2), 427-447.
- Bellinga, J., Bosman, T., Höcük, S., Janssen, W. H., & Khzam, A. (2022). Robotic process automation for the extraction of audit information: A use case. Current Issues in Auditing, 16(1), A1-A8.
- Betti, N., & Sarens, G. (2021). Understanding the internal audit function in a digitalised business environment. Journal of Accounting & Organizational Change, 17(2), 197-216.
- Broek, S. J. (2024). Robotic Process Automation in the External Audit Function: Defining and Validating an Evaluation Framework (Master’s Thesis). University of Twente.
- Bruton, A., Conway, J., & Holgate, S. (2000), Reliability: What is it, and how is it measured? Physiotherapy, 86(2), 94-99.
- Candratio, E., Harita, M. P., Hartanto, A. D., & Hermawan, M. S. (2023). Adoption of Robotic Process Automation in External Auditing Process in Metropolitan Indonesia: A Qualitative Approach. JATISI (Jurnal Teknik Informatika dan Sistem Informasi), 10(2).
- Cooper, L. A., Holderness Jr, D. K., Sorensen, T. L., & Wood, D. A. (2019). Robotic process automation in public accounting. Accounting Horizons, 33(4), 15-35.
- Doguc, O. (2021). Applications of robotic process automation in finance and accounting. Beykent Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 14(1), 51-59.
- Eulerich, M., Waddoups, N., Wagener, M., & Wood, D. A. (2024). The dark side of robotic process automation (RPA): Understanding risks and challenges with RPA. Accounting Horizons, 38(2), 143-152.
- Farinha, D., Pereira, R., & Almeida, R. (2024). A framework to support Robotic process automation. Journal of Information Technology, 39(1), 149-166.
- Fotoh, L. E., & Lorentzon, J. I. (2023). Audit digitalization and its consequences on the audit expectation gap: A critical perspective. Accounting Horizons, 37(1), 43-69.
- Griffiths, L., & Pretorius, H. W. (2021). Implementing robotic process automation for auditing and fraud control. In Gerber, A., & Hinkelmann, K. (Eds.), Society 5.0: First International Conference (pp. 26-36). Springer International Publishing.
- Hair, J., Black, W., Babin, J., & Anderson, R. (2010). Multivariate Data Analysis: A Global Perspective (7th ed.). Publisher: Pearson.
- Harrast, S. A. (2020). Robotic process automation in accounting systems. Journal of Corporate Accounting & Finance, 31(4), 209-213.
- Hazaea, S. A., Zhu, J., Al-Matari, E. M., Senan, N. A. M., Khatib, S. F., & Ullah, S. (2021). Mapping of internal audit research in China: A systematic literature review and future research agenda. Cogent Business & Management, 8(1), 1938351.
- Hofmann, P., Samp, C., & Urbach, N. (2020). Robotic process automation. Electronic Markets, 30(1), 99-106.
- Hong, B., Ly, M., & Lin, H. (2023). Robotic process automation risk management: Points to consider. Journal of Emerging Technologies in Accounting, 20(1), 125-145.
- Hsiung, H. H., & Wang, J. L. (2022). Research on the introduction of a robotic process automation (RPA) system in small accounting firms in Taiwan. Economies, 10(8), 200.
- Karaki, B. A., Al_Kasasbeh, O., Alassuli, A., & Alzghoul, A. (2023). The impact of the digital economy on carbon emissions using the STIRPAT model. International Journal of Energy Economics and Policy, 13(5), 139-143.
- Kotb, A., Elbardan, H., & Halabi, H. (2020). Mapping of internal audit research: a post-Enron structured literature review. Accounting, Auditing & Accountability Journal, 33(8), 1969-1996.
- Krichene, A., & Baklouti, E. (2020). Internal Audit Quality: Perceptions of Tunisian Internal Auditors an Explanatory Research. Journal of Financial Reporting and Accounting, 19(1), 28-54.
- Kutbidinovich, K. S. (2022). Improvement of internal audit in budgetary organizations. International Journal of Research in Commerce, IT, Engineering and Social Sciences, 16(06), 135-139.
- Lacurezeanu, R., Tiron-Tudor, A., & Bresfelean, V. P. (2020). Robotic process automation in audit and accounting. Audit Financiar, 18(4), 752-770.
- Lin, C. H., Chiu, D. K., & Lam, K. T. (2024). Hong Kong academic librarians’ attitudes toward robotic process automation. Library Hi Tech, 42(3), 991-1014.
- Liu, S. (2022). Robotic Process Automation (RPA) in Auditing: A Commentary. International Journal of Computer Auditing, 4(1), 23-28.
- Napitupulu, I. H. (2023). Internal control, manager’s competency, management accounting information systems and good corporate governance: Evidence from rural banks in Indonesia. Global Business Review, 24(3), 563-585.
- Ng, C. (2023). Teaching advanced data analytics, robotic process automation, and artificial intelligence in a graduate accounting program. Journal of Emerging Technologies in Accounting, 20(1), 223-243.
- Perdana, A., Lee, W. E., & Kim, C. M. (2023). Prototyping and implementing Robotic Process Automation in accounting firms: Benefits, challenges and opportunities to audit automation. International Journal of Accounting Information Systems, 51, 100641.
- Plattfaut, R., & Borghoff, V. (2022). Robotic Process Automation: A Literature-Based Research Agenda. Journal of Information Systems, 36(2), 173-191.
- Ribeiro, J., Lima, R., Eckhardt, T., & Paiva, S. (2021). Robotic process automation and artificial intelligence in industry 4.0–a literature review. Procedia Computer Science, 181, 51-58.
- Romney, M., Steinbart, P., Summers, S., & Wood, D., (2021). Accounting Information Systems (15th ed.). Pearson Publisher.
- Saatchi, S. G., Sharairi, J. A., Sarram, M., Rahahle, M. Y., Anagreh, S., Haija, A. A. A., Maabreh, H. M. A., Alrfai, M. M., Al-Hawary, S. I. S., & Mohammad, A. A. S. (2024). Industry 4.0 Era: The Role of Robotic Process Automation in Internal Auditing Quality of Banking Sector in Jordan. In Musleh Al-Sartawi, A. M. A., Aydiner, A. S., & Kanan, M. (Eds.), Business Analytical Capabilities and Artificial Intelligence-Enabled Analytics: Applications and Challenges in the Digital Era (Vol. 1) (pp. 73-91). Cham: Springer Nature Switzerland.
- Salah, A. H., & Alzghoul, A. (2024). Assessing the moderating role of customer orientation on the impact of business intelligence tools on digital marketing strategy optimization. International Review of Management and Marketing, 14(3), 18-25.
- Syed, R., & Wynn, M. T. (2024). Robotic process automation: a review of the state-of-the-art. In Grefen, P. & Vanderfeesten, I. (Eds.), Handbook on Business Process Management and Digital Transformation (pp. 333-362). Cheltenham: Edward Elgar Publishing.
- Taber, K. (2018). The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Research in Science Education, 48(1), 1273-1296.
- Tiron-Tudor, A., Lacurezeanu, R., Bresfelean, V. P., & Dontu, A. N. (2024). Perspectives on How Robotic Process Automation Is Transforming Accounting and Auditing Services. Accounting Perspectives, 23(1), 7-38.
- Turetken, O., Jethefer, S., & Ozkan, B. (2020). Internal audit effectiveness: operationalization and influencing factors. Managerial Auditing Journal, 35(2), 238-271.
- Verma, P., & Sehgal, S. (2023). Leveraging Artificial Intelligence for Enhancing Customer Experience and Efficiency in the Banking Industry. In Bhardwaj, B., Sharma, D., & Dhiman, M. C. (Eds.), AI and Emotional Intelligence for Modern Business Management (pp. 282-310). IGI Global.
- Zareen, M., Hamdan, A., & Binsaddig, R. (2024). The Impact of Robotic Process Automation (RPA) on Accounting Profession. In Hamdan, A., and Harraf, A. (Eds.), Business Development via AI and Digitalization (Vol. 1) (pp. 191-199). Cham: Springer Nature Switzerland.
- Zhang, C., Issa, H., Rozario, A., & Soegaard, J. S. (2023). Robotic process automation (RPA) implementation case studies in accounting: A beginning to end perspective. Accounting Horizons, 37(1), 193-217.
-
Fintech in the eyes of Millennials and Generation Z (the financial behavior and Fintech perception)
Mohannad A. M. Abu Daqar ,
Samer Arqawi ,
Sharif Abu Karsh
doi: http://dx.doi.org/10.21511/bbs.15(3).2020.03
Banks and Bank Systems Volume 15, 2020 Issue #3 pp. 20-28 Views: 7122 Downloads: 2302 TO CITE АНОТАЦІЯThis study investigates the Millennials and Gen Z perception toward Fintech services, their usage intention, and their financial behavior. The study took place in the Palestinian context with a global comparison among these generations. The authors used the questionnaire-based technique to meet the study objective. West Bank respondents were selected for this purpose; the study instrument was distributed through different social media channels. The findings show that reliability/trust and ease of use are the main issues in using a financial service. Millennials are more aware (48%) of Fintech services than Gen Z (38%), which is different from the global view where Gen Z is the highest. The smartphone penetration rate is 100% among both generations, while the financial inclusion ratio in Palestine is around 36.4%; these clear indicators are the main Fintech drivers to promote Fintech services in Palestine, and these are global indicators for Fintech adoption intention. Both generations (84%) intend to use e-wallet services, Millennials (87%) and Gen Z is (70%) prefer using real-time services. Half of the respondents see that Fintech plays a complementary role with banks. The majority see that Fintech services are cheaper than bank services. Wealth management, and robot advisor services, and both generations are looking to acquire them in the long run. The authors revealed that 85% of respondents from both generations trust banks, so it is recommended that banks digitize their financial services to meet the customers’ needs, considering that 90% of respondents see that promotions are a key issue in adopting Fintech services. Promoting e-wallet services by banks is highly recommended due to the massive rivalry with Fintech parties.
-
Evaluating the nationalization & privatization effect: a case of Indian banking industry
Manju Rajan Babu ,
Ashok Kumar M.
doi: http://dx.doi.org/10.21511/bbs.13(1).2018.02
Banks and Bank Systems Volume 13, 2018 Issue #1 pp. 11-21 Views: 2995 Downloads: 418 TO CITE АНОТАЦІЯThe facilitation of economic transactions and friendly investor environment is undertaken through effective performance of financial systems. Mobilization of savings and funding the profitable business opportunities are essential in improving the efficiency of intermediation. The study aims to evaluate the effects of nationalization and privatization on Indian banks. Various factors have been considered to examine the effects of privatization and nationalization, including sources of public sector inefficiency, measures of firm performance, econometric issues, and the mode of privatization. The data was collected for the period of 1998 to 2016 from Indian banks. Data Envelopment Analysis (DEA) was used to evaluate the financial reports of the banks selected to evaluate the efficiency of input and output variables. Positive results were observed, concerning the efficiency and profitability of banking industry after banks’ privatization. Performance of private banks has been observed effective and efficient as compared to the public sector banks. Privatization of banks must be increased and maintained to sustain the efficiency of the banks and implement strategies to maintain the assets. Future studies may recruit more appropriate sample size to evaluate the privatization and nationalization effects of Indian banking industry. Greater number of banks will provide more precise results, using data envelopment analysis.
-
ERP implementation in banks: success factors & impact on financial performance
Banks and Bank Systems Volume 12, 2017 Issue #4 pp. 17-30 Views: 2833 Downloads: 1184 TO CITE АНОТАЦІЯThe study aims to measure the extent of implementing ERP systems in the banking sector in Jordan, and identify the main factors that influence the implementation decision, in addition to measure the impact of the post-implementation of the ERP system on the financial performance. The study utilized a content analysis as a research instrument. The study of population consisted of all the banks in Jordan, where the study applied ‘Purposive Sample’ type. Therefore, the study included 11 banks from 2011 to 2016.
The study indicated that the implementation year of the ERP system started in most of the Jordanian banks in 2013, and the rates vary from bank to bank according to their importance and the level of awareness. Training courses are considered the main variable that these banks face in the process of implementation. In addition, awareness of the advantages, the cost, and supporting the infrastructure are the core factors needed to influence the implementation decision.
There is no impact when implementing an ERP system on the financial performance of the Jordanian banks in regard to the ROI and the DPS; on the other hand, there is an impact of the ERP system on the overall performance of the banks.
The study recommends to disseminate knowledge on the advantages of implementing of ERP system in Jordanian banks and to develop the IT department efficiency. Moreover, it will be worthwhile to examine the effect of ERP systems by utilizing financial and non-financial measurements.
