Proceedings of the Global Innovation and Technology Summit “AAROHAN 3.0”_HSS track (GITS-HSS 2025)

<Previous Article In Volume
Next Article In Volume>

Leveraging AI-Driven Business Intelligence for Smarter and Secure Banking Systems

Authors
Shilpa Verma2, Suman Madan1, *, Zuleika Homavazir2, Vinima Gambhir2
1uGDX School of Technology, ATLAS SkillTech University, Mumbai, India
2ISME, ATLAS SkillTech University, Mumbai, India
*Corresponding author. Email: madan.suman@gmail.com
Corresponding Author
Suman Madan
Available Online 19 April 2026.
DOI
10.2991/978-2-38476-559-1_36How to use a DOI?
Keywords
Business Intelligence; Technology Adoption; Banking Sector; BI Adoption Framework; Data-Driven Decision
Abstract

The increasing competition in the banking sector has made customer acquisition and customer retention difficult for the banks. Banks need to integrate their processes to make their systems robust so as to offer exemplary customer experience, better risk management and reduced frauds which will help them stay ahead of the curve. Business Intelligence solutions today offer banks an opportunity to convert the customer data into meaningful information which can improve their decision making and also help in understanding customer behaviour. BI systems in banks cover various areas, including Customer Relationship Management, Performance Management, and Risk Management, utilizing data warehouses and online analytical processes as their foundation. This study examines how Business Intelligence (BI) is shaping the banking sector, focusing on its influence on decision-making, risk assessment, and customer engagement. It delves into the challenges banks face, such as navigating regulatory requirements, ensuring data security, and managing the costs of implementation. Additionally, the study explores emerging trends, including AI-powered analytics and real-time decision-making, which are set to redefine the future of banking.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the Global Innovation and Technology Summit “AAROHAN 3.0”_HSS track (GITS-HSS 2025)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
19 April 2026
ISBN
978-2-38476-559-1
ISSN
2352-5398
DOI
10.2991/978-2-38476-559-1_36How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Shilpa Verma
AU  - Suman Madan
AU  - Zuleika Homavazir
AU  - Vinima Gambhir
PY  - 2026
DA  - 2026/04/19
TI  - Leveraging AI-Driven Business Intelligence for Smarter and Secure Banking Systems
BT  - Proceedings of the Global Innovation and Technology Summit “AAROHAN 3.0”_HSS track (GITS-HSS 2025)
PB  - Atlantis Press
SP  - 553
EP  - 565
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-559-1_36
DO  - 10.2991/978-2-38476-559-1_36
ID  - Verma2026
ER  -