Designing a Model for Implementing Digital Banking Policy Based on Using Big Data in Iranian Banking Industry

Document Type : Research Paper

Authors

1 Prof., Department of Leadership and Human Capital, Faculty of Public Administration and Organizational Sciences, College of Management, University of Tehran, Tehran, Iran.

2 Ph.D. Candidate, Department of Public Administration, Kish International Campus, University of Tehran, Tehran, Iran.

10.22059/jipa.2024.376062.3500

Abstract

Objective
In the current digital era, the immense challenges posed by technological advancements have driven significant developments, including the emergence of digital banking policies. For banks to survive and maintain their competitive edge among both new entrants and established competitors, it is essential to correctly implement digital banking strategies. This requires not only appropriate structural changes but also careful planning, the adoption of new business methods, and the use of innovative and technological tools, such as big data, to achieve strategic goals. On a broader scale, these efforts contribute to the realization of a smart economy. This research addresses the gap in existing literature regarding the lack of a digital banking policy implementation model, particularly within Iranian banks. It seeks to develop an optimal model for implementing such policies, with a special focus on the dimensions of policy implementation specific to digital banking. The research emphasizes the pivotal role of big data technology, which has received limited attention but has a significant impact on achieving the goals and ensuring the optimal implementation of digital banking.
Methods
This research falls within the realm of qualitative and postmodern studies, adopting an inductive approach. The research strategy employed is "Grounded Theory," specifically the emerging or classical Glaserian approach. Given that developing a foundational theory necessitates the collection of in-depth interview and textual data, the study aimed to identify the concepts, categories, and components of a digital banking implementation model leveraging big data technology. To this end, semi-structured interviews were conducted with experts in the fields of banking and financial technology. The study involved 15 accessible experts from the banking industry, selected through purposive judgment sampling. Interviews continued until theoretical saturation was reached, ensuring that the data collected was comprehensive and insightful. The research data was analyzed through a process of open, axial, and selective coding, which allowed for the extraction and categorization of key concepts. Ultimately, these efforts led to the emergence of a robust research model.
Results
The resulting model identifies 15 main themes, including Big Data Management, Data Governance (encompassing Data Collection, Data Refinement, Data Design and Modeling, Data Security), Data Regulation, Various Sources of Data Acquisition, Trust in Big Data Analysis, the Banking System Ecosystem, Organizational Agility, Big Data Analysis Tools, Scenario Development (practical application of data), Executive Structure, Improvement of Banks' Business, Customer Orientation, Transparency, Technological Infrastructure, and Dominant Culture. These themes were organized into six dimensions based on Glaser's 6C model, with an overarching or central category dimension forming the core of the final research model. According to this model, Big Data Management serves as the main axis around which 13 other themes revolve, acting as the model's center of gravity. This relationship is explained within the category of linkages, highlighting how these components interconnect.
Conclusion
The findings underscore a significant gap in the attention and application of big data technology within banks. Despite the availability of rich information and data resources in state banks, this valuable capital remains underutilized. Proper utilization of big data could create a necessary competitive advantage, enabling banks to survive and thrive amidst competition from both new and old players in the banking sector. Moreover, leveraging big data can enhance and improve customer-oriented platforms, a primary goal of digital banking, thereby facilitating better implementation of digital banking policies. The model developed through this research illustrates the integration of technological, organizational, and innovative cultural factors within state banks, all aimed at effectively utilizing big data. To optimize digital banking implementation, these factors must be prioritized within the structures of the country's state banks. The results demonstrate that Big Data Management, along with associated governance, regulatory practices, and infrastructural considerations, are crucial categories that must be meticulously observed and integrated into the operational frameworks of state banks to fully harness the potential of big data.

Keywords

Main Subjects

References

 
Aliu, B. (2019). Big Data Phenomenon in Banking. Texila International Journal of Academic Research, 6(2). DOI: 10.21522/TIJAR.2014.06.02.Art008
Asgari Mehr, M., Tork Tabrizi, M., Dehghani Qahfarokhi, A. & Kazemi, N. (2017). Identifying strategic components for the successful implementation of the digital banking model. The 7th National Conference on Electronic Banking and Payment Systems. Tehran. Monetary and Banking Research Institute. https://www.civilica.com/Paper-CEBPS07-CEBPS07_014.html (in Persian)
Azadeh, Z. (2016). Big Data Analytics (BDA) as a Driver for Creating Competitive Advantage for Banks, Master's Thesis, Payame Noor University, Tehran Province, West Tehran Branch. (in Persian)
Boudlaie, H., Kenarroodi, M., Ebadi, H. & Bahmani, A. (2021). Digital Human Resource Management: An Approach to Creating Organizational Agility in the Public Sector in the Digital Economy Era (A Study on the Public Sector Banking Network in Iran). Journal of Public Administration, 13(4), 766-785. doi: 10.22059/jipa.2022.333338.3051 (in Persian)
Dastranj, R., Ghazinoory, S., Dastranj, N. & Shayan, A. (2019). Assessment of Big Data Ecosystem in Iran with Metaphor of Millennium Ecosystem Assessment Model. Iranian Journal of Information Processing and Management, 34(4), 1613-1642. doi: 10.35050/JIPM010.2019.016 (in Persian)
Ghadami, M., Mousakhani, M., Alwani, S. M. & Yazdani, H. (2022). Developing a Model for Policy Making in Digital Banking, Based on Network Approach. Iranian Journal of Public Policy, 8(1), 125-141. doi: 10.22059/jppolicy.2022.85915 (in Persian)
Gholipour, R., Danaii Fard, H., Zareii Matin, H., Jandaghi, G. & Fallah, M. (2011). A Model for Implementing Industrial Policies (Case Study in Qom Province). Organizational Culture Management, 9(24), 103-130. (in Persian)
Hasani Moghadam, S., Mohtadi, M., Bazargani, H. & Taheri, A. (2023). Agility in Business Processes Management Based on the Theory of Complex Adaptive Systems. Journal of Public Administration, 15(3), 553-583. doi: 10.22059/jipa.2023.359912.3335 (in Persian)
Hassani, H., Huang, X. & Silva, E. (2018). Digitalisation and Big Data Mining in Banking. Big Data and Cognitive Computing, 2(3), 18. https://doi.org/10.3390/bdcc2030018
Hosseini, S. S. & Soori, A. R. (2007). The Estimation of Efficiency and Its Effecting Factors in Iran's Banks. Economics Research, 7(25), 127-155. (in Persian)
Hosseinzadeh, M. (2016). The need to transition to digital banking. Future Banking Monthly. Number 28.
Hung, A., Leclerc, O. & Murdoch, T. (2017). How to succeed as a chief digital officer in pharma. McKinsey white paper, New York, NY.
Indriasari, E., Gaol, F. L. & Matsuo, T. (2019). Digital Banking Transformation: Application of Artificial Intelligence and Big Data Analytics for Leveraging Customer Experience in the Indonesia Banking Sector. In 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI) (pp. 863-868). IEEE.
Kamandi, A. & Farahi, Z. (2019). Data Management Knowledge Framework Based on the DMBOK Framework (First Edition), Tehran: Sharif University of Technology.
(in Persian)
Kenari Zadeh Dezful, M. & Tajfar, A.H. (2016). Knowledge Management: Its Importance and Implementation in Modern Education, Second National Conference on Management and Humanities, Arzuyieh. https://civilica.com/doc/573384 (in Persian)
Keshvarian Azad, R., Etebarian Khorasgani, A., Hadi Paykani, M. & Shahnoushi, M. (2022). Designing a Model for Implementing Judicial Policies in Iran's Judiciary. Journal of Public Administration, 14(1), 129-164. doi: 10.22059/jipa.2021.334472.3060 (in Persian)
Khalil Nejad, Sh. & Azami, S. (2018). Open banking: a new development in the banking and financial services industry. The 13th International Strategic Management Conference, Tehran, Strategic Management Association of Iran. (in Persian)
Kordi Ardestani, F. & Mobrahen, R. (2017). A study of the factors influencing the acceptance of big data analytics in the banking industry. The 7th National Conference on Electronic Banking and Payment Systems, Tehran. Monetary and Banking Research Institute. https://www.civilica.com/Paper-CEBPS07-CEBPS07_026.html (in Persian)
Ladley, J. )2012(. Data Governance How to Design, Deploy, and Sustain an Effective Data Governance Program. Academic Press.
Mahmoodzade, E., Sahraei, M. & Ghouchani Khorasani, M. M. (2017). Development of Big Data Strategy in Social Network Analysis toward Prediction of Crisis. Emergency Management, 6(1), 77-91. (in Persian)
Mbama, C. I., Ezepue, P., Alboul, L. & Beer, M. (2018). Digital banking, customer experience and financial performance: UK bank managers’ perceptions. Journal of Research in Interactive Marketing, 12(4), 432-451.
Oyarhossein, S., Toloie Eshlaghy, A., Radfar, R. & Pour Ebrahimi, A. (2022). Digital transformation in corporate banking: Theoretical approach and behavioral analysis. Journal of Investment Knowledge, 11(44), 603-630. (in Persian)
Pourebrahimi, N., Kordnaeij, A., Hosseini, H. K. & Azar, A. (2018). Developing a digital banking framework in the Iranian banks: Prerequisites and Facilitators. International Journal of E-Business Research (IJEBR), 14(4), 65-77. (in Persian)
Pressman, J. & Wildavsky, A. (1973). Implementation. University of California Press: Berkeley.
Rastgar, A. A., Ebrahimi, S. A., Shafiei Nikabadi, M. & Kolahi, B. (2022). Smart Human Resources Architecture: A Structural Approach to the Digital Transformation of Knowledge-based Companies. Journal of Public Administration, 14(2), 215-234. doi: 10.22059/jipa.2022.338173.3101 (in Persian)
Sadeghi, B., Gholipour, R., Amiri, M. & Saffari, M. (2024). Designing a Policy Making Model in Iran' Sport with the Approach of Sport for All Development. Journal of Public Administration, 16(1), 52-79. doi: 10.22059/jipa.2023.359698.3332 (in Persian)
Saheb, T. & Farzin, H. (2017). Report on the Analysis of the Business Ecosystem Based on Big Data. Project for Developing a Roadmap for Big Data. Tehran: Iranian Telecommunications Research Center. (in Persian)
Salamati Taba, S.S., Beigi, M. & Akbari, A. (2017). Digital Banking: A Revolution in the Banking Industry. The 7th National Conference on Electronic Banking and Payment Systems, Tehran, Monetary and Banking Research Institute. (in Persian)
Saunders, M., Lewis, P. & Thornhill, A. (2016). Research methods for business students (4th ed.). Pearson Education Limited, Essex.
Shami Zanjani, M. (2022). Proposed frameworks of strategy and data governance. Retrieved from the website https://shamizanjani.ir (in Persian)
Siddiqui, A. A. & Qureshi, R. (2017). Big Data in Banking: Opportunities and Challenges Post Demonetisation in India. IOSR Journal of Computer Engineering (IOSR-JCE), 2278-8727. www.iosrjournals.org
Sohrabi, B. & Iraj, H. (2015). Managing Big Data in the Private and Public Sectors. Tehran, Samt Publications. (in Persian)
Streubert, H. J. & Carpenter, D. R. (2003). Qualitative research in nursing: Advancing the humanistic imperative (3rd Ed). Philadelphia, Lippincott Co.
Sullivan, W., Wilson, D., Thakral, C., Verma, S., & Venkataraman, K. (2016). Top 10 Trends in Insurancein 2016. Capgemini.
Sultan, J. & Bechter, C. (2019). Big Data Analytics in Islamic Banking. International Academic Journal of Business Management, 6(01), 21-31.
Supreme Document on Banking and Digital Transformation of the Ministry of Economic Affairs and Finance (2019). The Future of Banking and Digital Transformation; Policy Approach and Implementation Framework Based on the Smart Economy Paradigm. http://mefa.ir/fa (in Persian)
Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., Sui, F. (2018). Digital twin-driven product design, manufacturing and service with big data. The International Journal of Advanced Manufacturing Technology, 94 (9-12), 3563–3576.
Van Meter, D. & Van Horn, C. (1975). The Policy Implementation Process. Administration and Society, 6, 4.
Vazifeh Dost, H. & Malek Ara, M. (2020). Big data applications in e-commerce: 5th International Conference on Modern Tricks in Management, Accounting, Economics, and Banking with a focus on business growth. (in Persian)
Wei, W. (2020). Looking at the Demand of Bank Big Data Talents from the Perspective of Big Data. In Journal of Physics: Conference Series, 1437(1), 012116. IOP Publishing.
Zareian, D. & Vahed, F. (2020). Legal Review of Data Regulatory Protection. Rasaneh, 31(1), 47-72. (in Persian)
Journal of Public Administration
Volume 16, Issue 4
2024
Pages 825-851

Files

Share

How to cite

Statistics