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ISSN Approved Journal || eISSN: 2582-8185 || CODEN: IJSRO2 || Impact Factor 8.2 || Google Scholar and CrossRef Indexed

Peer Reviewed and Referred Journal || Free Certificate of Publication

Research and review articles are invited for publication in March 2026 (Volume 18, Issue 3) Submit manuscript

Cloud-based CRM systems: Revolutionizing customer engagement in the financial sector with artificial intelligence

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Nnaemeka Stanley Egbuhuzor 1, *, Ajibola Joshua Ajayi 1, Experience Efeosa Akhigbe 1, Oluwole Oluwadamilola Agbede 1, Chikezie Paul-Mikki Ewim 2 and David Iyanuoluwa Ajiga 3

1 Price water house Coopers Limited, Lagos Nigeria.
2 Independent Researcher, Lagos, Nigeria.
3 Independent Researcher, Chicago, Illinois, USA.

Research Article
 
International Journal of Science and Research Archive, 2021, 03(01), 215-234.
Article DOI: 10.30574/ijsra.2021.3.1.0111
DOI url: https://doi.org/10.30574/ijsra.2021.3.1.0111

Received on 24 June 2021; revised on 27 July 2021; accepted on 29 July 2021

Cloud-based Customer Relationship Management (CRM) systems have emerged as transformative tools for enhancing customer engagement in the financial sector. By integrating Artificial Intelligence (AI) technologies, these systems enable financial institutions to optimize customer interactions, improve operational efficiency, and deliver personalized services at scale. The shift to cloud-based CRM platforms offers unparalleled advantages, including cost-effectiveness, scalability, real-time analytics, and seamless integration with existing financial technologies. AI capabilities, such as natural language processing (NLP), predictive analytics, and machine learning algorithms, empower financial firms to gain deep insights into customer behavior, anticipate needs, and provide proactive solutions. Key applications of AI-driven cloud CRM systems in the financial sector include fraud detection, credit risk assessment, customer segmentation, and personalized marketing. These technologies streamline workflows, enhance customer satisfaction, and enable banks, credit unions, and financial service providers to remain competitive in an increasingly digitalized economy. Additionally, cloud-based CRM systems facilitate omnichannel customer engagement by integrating data from multiple touchpoints, such as mobile applications, social media, and in-person interactions, providing a unified and consistent customer experience. Despite these advancements, challenges persist in implementing cloud-based CRM systems in the financial sector. Concerns over data privacy, cybersecurity, regulatory compliance, and the high cost of initial setup require careful consideration. Furthermore, financial institutions must invest in employee training and robust IT infrastructure to fully leverage the potential of these technologies. This paper explores the transformative impact of AI-powered cloud CRM systems on the financial sector, analyzing key trends, benefits, and challenges. It also examines case studies of successful implementations, offering insights into best practices and strategies for optimizing customer engagement through technology. By harnessing the synergy between cloud computing and AI, financial institutions can revolutionize customer relationships, build trust, and drive sustainable growth in a competitive marketplace.

Cloud-Based CRM; Artificial Intelligence; Customer Engagement; Financial Sector; Predictive Analytics; Natural Language Processing; Machine Learning; Fraud Detection; Personalized Marketing; Omnichannel Experience

https://ijsra.net/sites/default/files/fulltext_pdf/IJSRA-2021-0111.pdf

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Nnaemeka Stanley Egbuhuzor, Ajibola Joshua Ajayi, Experience Efeosa Akhigbe, Oluwole Oluwadamilola Agbede, Chikezie Paul-Mikki Ewim and David Iyanuoluwa Ajiga. Cloud-based CRM systems: Revolutionizing customer engagement in the financial sector with artificial intelligence. International Journal of Science and Research Archive, 2021, 03(01), 215-234. Article DOI: https://doi.org/10.30574/ijsra.2021.3.1.0111

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

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