Open Banking

Given the emergence of digital transformation from Industry 4 and the rapid dissemination of technological innovations as well as their impact as a strong driving force in new banking businesses, efforts should be made to identify the dimensions of this core factor as rapidly as possible. Providing a comprehensive overview of all aspects of the model. The purpose of this article is to provide insights into the state of the art of digital transformation in the banking industry and suggest ways for future research. Existing literature, especially research for 2019 and 2020, has enhanced our understanding of the specific aspects of digital transformation in future banking, and we are now grasping a clearer picture of nature, how, and the consequences of these in the years ahead. However, all its dimensions are not yet clear. In this article, by review of 218 articles in the WOS database, and the analysis has utilized the data-driven tools,165 questionnaire and 90 specialized interviews with experts, extracted factors of the research, and using SMART PLS statistical software, ANFIS and MATLAB software for analysis. The paper, therefore, tends to understand Open Banking Innovation based on the digital transformation area and its dimensions in its previously known domains.

FinTech is the solution that strengthens the way of financial communication and if we apply this technology, it will provide us with new methods of performing smarter, more agile and wider financial services. The purpose of this study is to investigate and analyze the factors affecting the implementation of FinTech in Iran's banking industry using structural equation modeling to provide comprehensive solutions of removing barriers and development of this industry in the Iranian banking industry by fully understanding the current situation. The present article is of descriptive-analytical type and data collection has been done through library studies and questionnaires. The statistical sample of the study was 12147 personnel working in Iran's banks in 1400. Due to the size of the population, Cochran’s method and random sampling method were used to determine the sample size. To analyze and classify the extracted data, a questionnaire and a test of the main hypothesis and sub-hypotheses and structural equation modeling were used using smart PLS statistical software. The obtained results confirm the main hypothesis and the sub-hypotheses of the research. The results indicated that in the banking sector, there is a need for legalization and harmonization with upstream laws, as well as the need for infrastructure and tools that are very important in adopting strategies to implement FinTech in Iran's banking industry, in order to make transparency, reduce costs, provide high-speed services, and move towards a smart economy.