Abstract
Objectives : The study aimed to measure the impact of machine learning and deep learning techniques on the quality of accounting information in Yemeni banks, through the effectiveness of internal audit as an intermediate variable, and explored the interactive impact of organizational culture of these variables. Prior Work: The subject of the study is characterized by its novelty, especially after its emergence in peer-reviewed scientific journals, where it contributes to enriching the applied scientific literature related to the impact of AI on the accounting information quality and internal auditing through the interactive effect of organizational culture. Approach : The descriptive method of analysis, and the questionnaire, a tool for data collection, represented the study population in of all (18) Yemeni banks in the capital, Sana'a, and it is considered a survey study as it took the whole society Results: There is a high explanatory power of the proposed models, as it explained (63%) of the changes in the quality of accounting information, which supports its validity, and there is a positive effect of machine learning and deep learning on the quality of accounting information and the effectiveness of internal audit in Yemeni banks, in addition to a positive mediating effect of internal audit on the relationship between machine learning, deep learning, and the quality of accounting information. There is an interactive effect of organizational culture on the effectiveness of internal audit, and on the relationship between machine and deep learning and the quality of accounting information, with the intermediary role of internal audit stabilizing as organizational culture levels change. Implications: The study benefits executives, financial managers, auditors, regulatory institutions, and researchers.
Keywords
Machine Learning, Deep Learning, Accounting Information Quality, Internal Audit, Yemeni Banks
Full Text
Objectives : The study aimed to measure the impact of machine learning and deep learning techniques on the quality of accounting information in Yemeni banks, through the effectiveness of internal audit as an intermediate variable, and explored the interactive impact of organizational culture of these variables. Prior Work: The subject of the study is characterized by its novelty, especially after its emergence in peer-reviewed scientific journals, where it contributes to enriching the applied scientific literature related to the impact of AI on the accounting information quality and internal auditing through the interactive effect of organizational culture. Approach : The descriptive method of analysis, and the questionnaire, a tool for data collection, represented the study population in of all (18) Yemeni banks in the capital, Sana'a, and it is considered a survey study as it took the whole society Results: There is a high explanatory power of the proposed models, as it explained (63%) of the changes in the quality of accounting information, which supports its validity, and there is a positive effect of machine learning and deep learning on the quality of accounting information and the effectiveness of internal audit in Yemeni banks, in addition to a positive mediating effect of internal audit on the relationship between machine learning, deep learning, and the quality of accounting information. There is an interactive effect of organizational culture on the effectiveness of internal audit, and on the relationship between machine and deep learning and the quality of accounting information, with the intermediary role of internal audit stabilizing as organizational culture levels change. Implications: The study benefits executives, financial managers, auditors, regulatory institutions, and researchers.