The effect of corporate governance, audit quality and public sector accounting on the financial performance with the approach of neural networks (Case study: Iraq)

The purpose of this research is to investigate the impact of corporate governance, audit quality and public sector accounting on the financial performance of Iraqi manufacturing companies and government organizations using monthly data from 2015 to 2022 using machine learning pattern analysis including decision tree, reinforcing gradient, support vector machine (SVM) and artificial neural networks (ANNs). The results show the significant impact of corporate governance, audit quality and public sector accounting on financial performance. The present study shows that larger companies with stronger governance structure have better financial performance, and focusing on the separation of managerial roles and strengthening effective management structures helps to improve the financial performance of companies. The neural network analysis also shows that these factors have a significant impact on transparency and risk management. Therefore, this research re-emphasizes the importance of corporate governance and audit quality as key indicators in increasing operational efficiency and investor confidence. Therefore, it is suggested that managers and policy makers pay attention to these factors as key components to improve financial performance and economic strength. Finally, the current research is known as a solid foundation for ensuring the health and financial stability of companies in the Iraqi economy and can be useful to a wide range of financial stakeholders and investors.