Dynamics of Big Data Analytics in the Banking Sector

• Published in: 2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) Vol. 2; pp. 1 - 6
• Main Author: Kour, Manjit
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14-03-2024
• Subjects: Banking; Big Data; big data analytics; Data analysis; Data integrity; Decision making; fintech; Industries; machine learning; Technological innovation
• DOI: 10.1109/IATMSI60426.2024.10502648

This study looks at the importance, uses, difficulties, and potential applications of big data analytics in the banking industry. The banking sector produces enormous amounts of data, making it a prime candidate for using big data analytics to derive insightful conclusions and guide strategic decision-making. The significance of big data is first discussed, along with its ramifications for the banking industry, emphasizing the difficulties that banks currently face as a result of this data. The research report also discusses the difficulties and factors to be taken into account when deploying big data analytics in the banking industry, including issues with data privacy and security, data quality and governance, skill gaps, infrastructure needs, and moral and legal ramifications. In order for banks to remain competitive in the quickly changing digital landscape, this paper emphasizes the necessity for them to adopt a data-driven culture, make investments in technology and talent, and create strategies for efficiently utilizing big data analytics. For banking professionals, academics, and policymakers who want to comprehend and take use of big data analytics' potential in the banking sector, this report offers insightful information.