The present study aims to design a comprehensive model for the evaluation and ranking of factors affecting the quality of internal control in the Iranian capital market. To do so, four steps are taken. The first step is to identify the evaluation criteria that is carried out after reviewing the literature and research background. The second step is taken by a decision-making team of 20 experts in the area of capital market using the Fuzzy Delphi method. In this section, the internal factors identified are the characteristics of the board of directors, board committees, ownership structure, internal audit, and corporate structure and external factors are external audit, financial analysts, national culture, regulatory and market factors, and managerschr('39') decisions that affect the quality of internal control system in Iran. The third step is modeling the factors affecting the quality of internal control that is adaptable using the neural-fuzzy network model. The mean error of training of all main and subset models is below the threshold. The fourth step is to apply adaptive fuzzy neural network modeling in ranking the factors affecting the quality of internal control. In this step, internal audit, managers’ decisions, external audit, board committees, characteristics of the board of directors, ownership structure, corporate structure, regulatory and market factors, national culture, and financial analysts are ranked as factors that affect the quality of internal control, respectively.
v V, v V, v V. Designing a model for ranking factors affecting the internal control system with a hybrid intelligent approach. audit knowledge 2020; 20 (80) :383-400 URL: http://danesh.dmk.ir/article-1-2226-en.html