عرفان شفیعی

This study aims to investigate the role of Big Data in improving the performance of banks. The emergence of new technologies and the expansion of digital tools have provided organizations with vast amounts of diverse and dynamic data. Banks, as one of the most important financial institutions, are confronted with massive and complex datasets more than other sectors. The ability to effectively utilize Big Data can enhance operational efficiency, increase customer satisfaction, strengthen corporate social responsibility, and ultimately improve profitability. Accordingly, this research seeks to explain the various dimensions of Big Data and its impact on banking performance indicators.

The research method is descriptive survey and applied in nature. The statistical population of the study consisted of managers and experts from selected banks. Data were collected using a standard questionnaire whose validity and reliability were confirmed. Data analysis was conducted through structural equation modeling (SEM) using SmartPLS software. To evaluate the model quality, tests such as convergent validity, composite reliability, average variance extracted (AVE), and path coefficients were applied. Additionally, model fit was assessed through indices such as R², Q², and GOF.

The findings revealed that the dimensions of Big Data including volume, velocity, variety, and digitalization have significant impacts on improving banks’ performance indicators. In particular, Big Data had the greatest influence on enhancing operational efficiency and customer satisfaction, providing advanced analytical infrastructures for more accurate and faster managerial decision-making. Moreover, Big Data plays a crucial role in improving employee job satisfaction and enhancing corporate social responsibility by increasing information tra  arency and service quality, thereby strengthening public trust in banks. The results indicate that strategic utilization of Big Data can lead to increased profitability and the creation of sustainable competitive advantage in the banking sector.

From a practical perspective, the results can guide bank managers and financial policymakers to invest in Big Data analytical infrastructures in order to enhance organizational productivity. It is also recommended that banks develop employees’ analytical skills and expand the use of artificial intelligence and machine learning in decision-making and risk management processes.

In conclusion, this study demonstrates that Big Data is not only a vast informational source but also a strategic tool for transforming organizational performance. The future of banking depends on the ability to smartly leverage data and convert it into valuable managerial insights. Thus, investing in technological infrastructure, fostering a data-driven culture, and training human resources are essential prerequisites for achieving data-driven intelligent banking.