How Commercial Banks in Emerging Economies Can Leverage Big Data Analytics

A perspective of Asian countries

Authors

  • Buana Lintang Singarimbum Universitas Teknologi Indonesia, Indonesia
  • Azanaush Ah-Mei Dhial University of Malaya, Malaysia
  • Adeel Fidvin Farooqi Quaid-i-Azam University, Pakistan

DOI:

https://doi.org/10.69511/ijdsaa.v4i4.98

Keywords:

Big data, Risk, commercial banks, segmentaion, business value

Abstract

Background/ Objectives: Big Data is an incredibly big data set that needs to be examined, managed, handled and validated by way of an ordinary information management tool. Banks are among the financial services industries, which handles overwhelming amounts of transaction information managed, scrutinized, as well as used for the gain of banks and also the buyers. Hence, this particular study paper examined how BDA are managed in Malay/Indian/Indonesian industrial banks. The elements which have a bigger impact on banks in handling big data were analyzed, as well as how analytics generates value for the company.

Method/Statistical Analysis: Secondary data was collected from numerous sources like articles, websites and journals. The aspects like big data management, fraud detection, risk management, consumer segmentation, as well as business value of banking industries are studied. A conceptual framework was created to spotlight the elements which have a better influence on big data management in the banking industry.

Findings: From the research, it's examined those big data analytics has driven a visible change in the company worth of banks, and the elements having an impact on the company are highlighted.

Application/Improvements: Banks have to revamp their software architecture for dealing with the important data and follow the new technologies which boost the online business worth of the business

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Published

2022-11-30

How to Cite

Singarimbum, B. L., Dhial, A. A.-M., & Farooqi, A. F. (2022). How Commercial Banks in Emerging Economies Can Leverage Big Data Analytics: A perspective of Asian countries. International Journal of Data Science and Advanced Analytics, 4(1), 94–97. https://doi.org/10.69511/ijdsaa.v4i4.98

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Section

Articles