Positioning big data analytics capabilities towards financial service agility
| DOI | https://doi.org/10.1108/AJIM-08-2021-0240 |
| Published date | 06 January 2022 |
| Date | 06 January 2022 |
| Pages | 569-588 |
| Subject Matter | Library & information science,Information behaviour & retrieval,Information & knowledge management,Information management & governance,Information management |
| Author | Abeeku Sam Edu |
Positioning big data analytics
capabilities towards financial
service agility
Abeeku Sam Edu
Operations and Management Information Systems,
University of Ghana Business School, Accra, Ghana
Abstract
Purpose–Enterprises are increasingly taking actionable steps to transform existing business models through
digital technologies for service transformation such as big data analytics (BDA). BDA capabilities offer
financial institutions to source financial data, analyse data, insight and store such data and information on
collaborative platforms for a quick decision-making process. Accordingly, this study identifies how BDA
capabilities can be deployed to provide significant improvement for financial services agility.
Design/methodology/approach –The study relied on survey data from 485 banking professionals’
perspectives with BDA usage,IT capability developmentand financial service agility. The PLS-SEM technique
was used to evaluate the underlying relationship and the applicability of the research framework proposed.
Findings –Based on the empirical test from this study, distinctive BDA usage grounded on the concept of IT
capability viewpoint proof that financial service agility could be enhanced provided enterprises develop
technical capabilities alongside other relevant resources.
Practical implications –The study further highlights the need for financial service managers to identify
BDA technologies such as data mining, query and reporting, data visualisation, predictive modelling,
streaming analytics, video analytics and voice analytics to focus on financial knowledge gathering and market
observation. Financial managers can also deploy BDA tools to develop a strategic road map for data
management, data transferability and knowledge discovery for customised financial products.
Originality/value –This study is a useful contribution to the burgeoning discussion with emerging
technologies such as BDA implication to improving enterprises operations.
Keywords Big data capability, Financial service agility, IT capability view, PLS-SEM
Paper type Research paper
1. Introduction
Digital technology innovations have gradually changed the phase of doing business globally
and subsequently influenced organisations performance. In their view, Cai et al. (2019)
observed that the business ecosystems are evolving mainly because of advanced innovations
in digital technologies. Therefore, many enterprises such as financial institutions have taken
actionable steps to transform existing business models through digital technologies for
service transformation. Consequently, financial institutions are steadily heading towards
digital banking for a number of reasons (Chanias et al., 2019;Pramanik et al., 2019). However,
the most imperative reason is informed by deploying innovative information technologies to
improve financial service agility (FSA) driven by data and information (Werth et al., 2020).
There is, therefore, a demand for an orientation towards enterprise agility as a new paradigm
within the financial service ecosystems. Diverse studies have stressed the antecedents or
consequences of enterprise agility (Meli
an-Alzola et al., 2020). Keenly, antecedents for most
enterprise agility has been ascribed to digital technology innovations, which stimulates
strategic decision-making, operational efficiency and stability (Harraf et al., 2015;Tallon et al.,
2019). Although Financial institutions have been deploying unique information technology
BDA
capabilities
towards FSA
569
Funding: This research was funded by the University of Ghana Business School (Award number:
03221821).
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/2050-3806.htm
Received 20 August 2021
Revised 18 November 2021
13 December 2021
Accepted 18 December 2021
Aslib Journal of Information
Management
Vol. 74 No. 4, 2022
pp. 569-588
Emerald Publishing Limited
2050-3806
DOI 10.1108/AJIM-08-2021-0240
(IT) strategies to shift from traditional banking into the era of digital banking, digital
disruptions are on the ascendency (Manser et al., 2021;Morkunas et al., 2019).
This has presented an opportunity for financial institutions to deploy emerging digital
technologies with their accompanying capabilities to build FSA to differentiate products or
services valuable to customers and ultimately improve revenues. Seemingly, continuous
advances and rapid availability of huge financial data calls for banks to deploy digital
technologies and applications to improve data acquisition, data processing, data and
information storage, knowledge creation and decision-making process in real-time (Labun,
2016;Mavlutova et al., 2020).
In recent times, billions of intelligent devices connect to create intelligent systems to
interact through data sharing on the cloud. Therefore, financial institutions have opined that
knowledge derived from financial data through the use of technologies and financial
resources is the new greatest asset for banks (Skyrius et al., 2018). This has immensely offered
emerging digital technologies such as big data analytics (BDA) capabilities to
comprehensively analyse customers’financial data and other related financial data to
enhance banking operations. BDA capabilities offer financial institutions to source financial
data, analysis of data, insight and store such data and information on collaborative platforms
for a quick decision-making process in real-time. Financial data acquisition, processing and
storage, have become pivotal for financial institutions (Roumeliotis, 2019). While current
studies on BDA deployment generally suggest an enhancement in enterprise operation, there
is still missing discourse on its implications on financial service operations, hence, linkage to
BDA capabilities is an important gap to explore. Based on this concept, the objective of this
study is to reveal the connection between BDA capabilities implications on financial services
agility.
As such, the role of BDA capability usage relies on the overall IT capability development
by a firm to promote enterprise agility. Additionally, based on Tallon et al. (2019)
recommendation for future study to investigate the impact of IT on enterprise agility, this
study proposes BDA capability (IT) topology usage as a factor to improve FSA. Moreover,
this insight is useful for shaping the discourse in IS literature towards BDA evolution for
financial services. The usage of BDA tools has been ascribed to be a catalyst to promotefirms ’
preparedness to collect and analyse large sizes of data for intelligence decisions. Thus, the
study proposes a holistic view of BDA capabilities usage in the financial service context.
Hence the study analysed the extent to which BDA capability uses can stimulate FSA
through the mediating role of the IT capability framework.
The remaining section of the study presents the literature review and the theoretical
framework. The next section presents the research methodology followed by data and, and
the final section presents the discussions of findings, implications and conclusions.
2. Literature review
2.1 An overview of technology applications in financial services
A cursory review of technology applications and platforms deployed by financial institutions
for retail banking and other services over the period ranges from stationed to virtual
technology platforms. Again, organisations that develop technology and some start-ups
whose activities do not guarantee obtaining financial services licences are gradually
expanding to collaborate with banks in various aspects of financial trading. These trends
contribute to driving financial institutions to refocus attention to financial technology
(FinTech) for operations. FinTech is therefore defined as “technologically enabled
innovations that could result in new business models, applications, process, or products
with an associated effect on financial markets and institutions and the provision of financial
services”(Gun, 2020). Therefore, financial technologies are driving the extent to which
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