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1. Introduction
Big data analytics has received increasing attention in organizations especially financial institutions in the last few years. As the set of techniques that is being used to discover hidden knowledge and customer value, big data analytics has the potential to enable financial institutions to reap many benefits including increased earnings and reduced fraud losses (Naveira et al., 2018). However, there are challenges to successful use of big data analytics in the banking industry, including cost consideration and lack of required human resources and skills (Raguseo, 2018). In addition, traditional banks face competitions from highly digitalized companies, such as online mutual fund and online insurance platforms. These companies have adopted big data analytics heavily for marketing. Many banks have yet to realize the full potential of leveraging big data analytics to improve returns from their decision processes and business operations (Naveira et al., 2018). Mikalef et al. (2019) reported that managerial skills are critical for gaining values from big data analytics as data resources and technical skills are. Currently, many banks are not familiar with successful practices in terms of how to successfully apply big data analytics deeply into their culture, decision processes and business operations.
This paper aims to help enterprises better leverage big data analytics for improving information management, operation and decision making. After all, the value of big data analytics depends on whether the insight generated by big data analytics can help improve firm operation or performance. As some personal or organizational factors may obstruct effective implementation of big data analytics in organizations, it is better to follow well-defined methodology or practices for implementation (Mikalef et al., 2019). Similar to other published case studies in organizations or governments such as Dolci et al. (2014) and Jones (2012), this paper discusses a real-world case study in an Asian bank – from planning to implementation – and observes related impacts over a longer period. The overarching research question for our study is as follows:
How can big data analytics be effectively adopted to help banks improve performance?
The remainder of the paper proceeds as follows. The second section provides a brief literature review about the technological frames of reference (TFR), transaction cost theory (TCT), adoption of big data analytics...