Exploring Factors Affecting Ethiopian Private Banks Data Analytics Tool Implementation
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Date
2020-09-03
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Addis Ababa University
Abstract
Data and Financial sectors are two much correlated concepts where by Financial sector by its
nature has been an intensively data-driven industry. Data is characterized as the lifeblood of
decision-making and the raw material for the sectors. Due to the high and variable demands of
their end-users, these sectors are undergoing huge reforms and digitalization. As a result, these
financial institutions are beginning to understand the importance of collating and utilizing their
internal data such as debit and credit transactions, internet banking data and their digital channel
application service using latest or moderate data analytics tools.
Generally, this analytics tools driven insights are used to the realization of competitive advantage
and to achieve wider market share. Hence this study is aimed at identifying the Definition and
characteristic, the role, current challenges, motivational and facilitator factor on the
implementation of the data analytics tools in sampled Ethiopian private banks.
Thus, to meet the above objectives, qualitative methodology is adopted. Standardized open
ended interview with 5 respondent whose work is directly related with these tools is conducted.
For analyzing the data collected through interview a thematic analysis is conducted to identify
patterns of themes. These themes are organized based on categories: i.e., facilitator factor,
inhibitor factors and motivational factors of data analytics tool implementation. Under each
category sub-themes are constructed namely: External factors, relative advantage, top level
management, IT infrastructure, Human resource, Data management, Ease of use and
customization. The result of the research is believed to provide an insight into the current status
of the banks in implementing the tools. Additionally, the result can be used as a baseline for
future studies related to the data analytics area for academic researches.
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Keywords
Data Analytics, Analytics Tools, Technology Acceptance Models, Data Analytics Tools in Banks