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

Author:

Hasan Morshadul1ORCID,Hoque Ariful1ORCID,Le Thi1ORCID

Affiliation:

1. Murdoch Business School, Murdoch University, Perth 6150, Australia

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.

Publisher

MDPI AG

Reference165 articles.

1. Big Data and Service Operations;Cohen;Prod. Oper. Manag.,2018

2. Developing banking intelligence in emerging markets: Systematic review and agenda;Arjun;Int. J. Inf. Manag. Data Insights,2021

3. Transforming business using digital innovations: The application of AI, blockchain, cloud and data analytics;Akter;Ann. Oper. Res.,2020

4. Fintech investments in European banks: A hybrid IT2 fuzzy multidimensional decision-making approach;Kou;Financial Innov.,2021

5. Opinion dynamics in finance and business: A literature review and research opportunities;Zha;Financial Innov.,2020

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Big data analytics usage in the banking industry in Tanzania: does perceived risk play a moderating role on the technological factors;Journal of Electronic Business & Digital Economics;2024-05-06

2. Financial Fraudulent Detection using Vortex Search Algorithm based Efficient 1DCNN Classification;2024 International Conference on Distributed Computing and Optimization Techniques (ICDCOT);2024-03-15

3. Examining Customers' Intentions to Use Financial Technology in Islamic Banking;Fintech Applications in Islamic Finance;2023-12-07

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3