Title | Expert Systems and Neural Networks and their Impact on the Relevance of Financial Information in the Jordanian Commercial Banks |
Publication Type | Conference Paper |
Year of Publication | 2022 |
Authors | Qasaimeh, Ghazi, Al-Gasaymeh, Anwar, Kaddumi, Thair, Kilani, Qais |
Conference Name | 2022 International Conference on Business Analytics for Technology and Security (ICBATS) |
Date Published | feb |
Keywords | Banks, Distributed databases, expert systems, financial information, Hardware, Human Behavior, Neural networks, pubcrawl, relevance, resilience, Resiliency, Scalability, security, Sociology, Task Analysis |
Abstract | The current study aims to discern the impact of expert systems and neural network on the Jordanian commercial banks. In achieving the objective, the study employed descriptive analytical approach and the population consisted of the 13 Jordanian commercial banks listed at Amman Stock Exchange-ASE. The primary data were obtained by using a questionnaire with 188 samples distributed to a group of accountants, internal auditors, and programmers, who constitute the study sample. The results unveiled that there is an impact of the application of expert systems and neural networks on the relevance of financial information in Jordanian commercial banks. It also revealed that there is a high level of relevance of financial information in Jordanian commercial banks. Accordingly, the study recommended the need for banks to keep pace with the progress and development taking place in connection to the process and environment of expertise systems by providing modern and developed devices to run various programs and expert systems. It also recommended that, Jordanian commercial banks need to rely more on advanced systems to operate neural network technology more efficiently. |
DOI | 10.1109/ICBATS54253.2022.9759047 |
Citation Key | qasaimeh_expert_2022 |