فریده فرحناک

Data is considered the most crucial element in open banking processes and services. Therefore, it is necessary to pay attention to various aspects of the quality of this data in order to provide appropriate and expected services to customers. In this research, various dimensions representing different aspects of data quality were investigated in the field of open banking. This research has been conducted in two main steps: The Delphi method and the pairwise comparisons method. In the first step, various dimensions of data quality in open banking were extracted based on the Delphi method. In the next step, the importance of each of these dimensions was assessed relative to each other using the pairwise comparisons method, and the most crucial dimensions were determined. Based on the results obtained from these two methods, the significance of eleven dimensions of data quality in this field was determined. The best overall weighted averages were related to dimensions such as accuracy, accessibility, relevancy, timeliness, consistency, security, interpretability, reputation, believability, ease of understanding, and value-added, respectively. Banks and fintech companies offering open banking services can consider these dimensions when evaluating the quality of their data to enhance the provision of superior services