Assessing the Importance of Various Dimensions of Data Quality in Open Banking Processes

Data is considered as the most important 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. Accordingly, in this research, various dimensions that represent different aspects of data quality were investigated in the field of open banking. This research has been done in two main steps, Delphi method and pairwise comparisons method. In the first step, based on the Delphi method, various dimensions of data quality in open banking were extracted, and in the next step using the pairwise comparisons method, the importance of each of these dimensions was assessed relative to each other, and the most important dimensions were determined. Based on the results obtained from these two methods, the importance of eleven dimensions of data quality in this field was determined. The best overall weighted averages were related to dimensions accuracy, accessibility, relevancy, timeliness, consistency, security, interpretability, reputation, believability, ease of understanding, and value-added, respectively. Banks and fintechs providing open banking services can consider these dimensions in assessing the quality of their data in order to provide better services.