Big Data-Driven Banking Operations: Opportunities, Challenges, and Data Security Perspectives

Abstract

At present, with the rise of information technology revolution, such as mobile internet, cloud computing, big data, machine learning, artificial intelligence, and the Internet of Things, the banking industry is ushering in new opportunities and encountering severe challenges. This inspired us to develop the following research concepts to study how data innovation impacts banking. We used qualitative research methods (systematic and bibliometric reviews) to examine research articles obtained from the Web of Science and SCOPUS databases to achieve our research goals. The findings show that data innovation creates opportunities for a well-developed banking supply chain, effective risk management and financial fraud detection, banking customer analytics, and bank decision-making. Also, data-driven banking faces some challenges, such as the availability of more data increasing the complexity of service management and creating fierce competition, the lack of professional data analysts, and data costs. This study also finds that banking security is one of the most important issues; thus, banks need to respond to external and internal cyberattacks and manage vulnerabilities.

Big data analytics usage in the banking industry in Tanzania: does perceived risk play a moderating role on the technological factors

“…Banks benefit the most from big data since they can now rapidly and easily extract useful information from their data and transform it into advantageous outcomes for both them and their clients. Internationally, banks are starting to use data to their advantage in various ways, including sentiment analysis, product cross-selling, regulatory compliance management, reputational risk management, financial crime management and many other things (Hasan, Hoque, & Le, 2023). Four observable trends exist in the use of BDA by banks in the Big Data era.…”