Corporate governance research is primarily focused on the inputs for effective governance; however, we have limited information about how corporate governance systems are continuously monitored and evaluated. The purpose of this article is to analyze the evaluation of corporate governance system effectiveness in Iran using a grounded data approach. The research population included 11 experts from academia familiar with corporate governance topics, selected using a snowball sampling method. Interviews were used to collect the necessary data. The research interviews were designed using the CAR framework and analyzed qualitatively using a grounded data approach. Data analysis was performed through open, axial, and selective coding, eventually leading to the presentation of a final model consisting of six main dimensions and thirty-two sub-dimensions. The results indicate that the model for evaluating the effectiveness of corporate governance in Iran revolves around the central category of fintech and monitoring, which are influenced by causal conditions. This process begins with causal conditions, leading to the formation of the central category, which, through strategic actions, contributes to increased transparency, accountability, improved internal controls, creativity, and resource optimization.