Abdalla Alassuli

This study aimed to find out the influence of Accounting Information Systems on the performance of Jordanian commercial banks, and the degree to which internal audit moderates this relationship. This was a current quantitative study designed to be at a descending trend of the survey conducted primarily on 12 major Jordanian banks’ accounting departments using descriptive and cross-sectional designs. From a total distribution of 358 questionnaires, 249 were returned, and after screening only 243 were deemed valid. Partial Least Square Structural Equation Modeling (PLS-SEM) was used as a statistical tool for data analysis, which is appropriate when exploring convoluted relationships and testing hypotheses. The findings indicate that there is a clear positive relationship between the implementation of AIS systems and improvement in the performance metrics at Jordanian banks; thus, hypothesis 1 is corroborated at a significant level of p < 0.01. More significantly, the findings suggest that internal audit highly strengthens the positive effect of AIS on bank performance, thereby supporting hypothesis 2 at the same significance level. This dual realization reiterates the needed adoption of advanced AIS by Jordanian banks and a general improvement to the internal auditors of the mechanisms that ensure they maximize on the benefits accruing in performance. More fundamentally, the findings underscore the dire urgency to incorporate efficacious AIS alongside with robust internal audit mechanisms in banking strategies, thereby providing crucial implications for bank managers and sectoral policymakers.

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.