The Relationship between Foreign Exchange rate prediction using Artificial Intelligence and Audit Effort | ||
| المجلة العلمية للدراسات والبحوث المالية والإدارية | ||
| Article 5, Volume 16, Issue 3, September 2024, Pages 39-48 PDF (1.1 M) | ||
| Document Type: المقالة الأصلية | ||
| DOI: 10.21608/masf.2024.373952 | ||
| Authors | ||
| Safaa Mohammed El Halawany1; Shehata Elsayed Shehata2 | ||
| 1Assistant Lecturer, Information Systems department High Institute for Computer & Information Systems- Abi Qir Alexandria, Egypt | ||
| 2Professor, Department of Accounting and Auditing, Faculty of Commerce, Alexandria University Dean of High Institute for Computer & Information Systems- Abi Qir Alexandria, Egypt | ||
| Abstract | ||
| this working paper explores how Artificial Intelligence (AI) usage to predict foreign exchange rates has an effect on audit effort in financial firms. The challenge to forecast accurately in the ever-volatile foreign exchange markets necessitates the infusion of AI algorithms, for example, machine learning and neural networks. By using AI technology in forecasting future foreign exchange rates, accurate predictions are made leading to efficiency. Nevertheless, there are questions about the model’s complex nature and transparency which can make audits more complicated thereby increasing compliance costs, regulatory burden as well as risk management requirements. Furthermore, auditors need to consider new factors after integrating AI since they need to learn the underlying algorithms used in its design; assess data integrity during appraisal; and estimate model reliability selection when making decisions. This working paper emphasizes the necessity of further researching into the subtle effects of AI-driven exchange rate prediction on audit practices such as their influence on planning audits or sampling techniques for a particular year or even generally the approach taken by auditors. | ||
| Keywords | ||
| Artificial Intelligence; Machine Learning- foreign exchange rate prediction- Audit effort | ||
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