Implementing Analytical Procedures in Predicting Return on Assets Through the Mediating Role of Regression Analysis: An Applied Study in Mosul Bank for Development and Investment
Keywords:
Analytical Procedures, Return on Assets, Bank Profitability, Linear Regression.Abstract
The present study highlights the influence of using analytical procedures through the application
of regression analysis as an analytical procedure in predicting the rate of return on banking
assets. This approach is applied to the financial statements of Mosul Bank for Development and
Investment to obtain reasonable assurance as to whether the rate of return on assets, based on the
data contained in the financial statements, will continue in the near future. The results of the
analysis demonstrate that the expected rate of return on assets for 2024 is (1.21%), compared to
the years of the study sample. This indicates that Mosul Bank for Development and Investment
does not possess a good rate of return on assets, enabling it to confront emergency and
unexpected situations resulting from future economic changes and events. Furthermore, the
phenomenon of financial failure is one of the most important phenomena requiring careful
consideration and investigation into its causes, as its consequences are now reflected on both
internal and external stakeholders. To obtain this objective, the regression model was applied to
Mosul Bank for Development and Investment, a sample of Iraqi banks listed on the Iraq Stock
Exchange, to determine the bank's ability to confront any
risks or difficulties that may arise as a result of fluctuations in the Iraqi economy.
The study recommends enhancing the use of quantitative analytical procedures in accounting and
auditing practices, with a focus on developing the skills of analysts and auditors in utilizing
analytical statistical tools, such as regression analysis, to provide more accurate and objective
assessments of financial performance. It also emphasizes the importance of integrating these methods into accounting and control systems to improve the effectiveness of financial
forecasting and strengthen the response to potential risks.
