Thesis:

Factors affecting the quality of financial statements from an audit point of view: A machine learning approach

The purpose of this research is to investigate the factors affecting the quality of financial statements from the perspective of auditing with a machine approach. To achieve this goal, a study of the theoretical foundations and background of the research was carried out, and a set of components, indicators, and hypotheses affecting the quality of financial statements were identified. Then, twelve hypotheses were examined by interpreting them. There is a significant relationship between the first hypothesis, the sixth stage hypothesis, the seventh hypothesis, the ninth stage hypothesis, the tenth hypothesis, the eleventh hypothesis, and the twelfth hypothesis, which indicates the validity of the methods presented for measuring the quality of financial statements Data from 1224 companies listed on the stock exchange, which were analyzed from 1396 to 1401, were analyzed. After calculating and measuring the data, 204 companies were selected as the statistical population. Using the systematic exclusion sampling method, 130 companies were selected as the research sample during the 10-year period between 1391 and 1400. The results of the study show that there is a direct relationship between company size and the quality of financial information. Also, factors that may affect the quality of financial statements include the quality of government agencies, human resource competencies, internal control systems, and information technology. Evidence about the quality of financial statements can be effective and improve the quality of financial statements with a machine approach by using new application software and advanced and up-to-date technology

Keywords: Financial Statement Quality Size Financial Statement Quality Number of Sample Companies