EconPapers    
Economics at your fingertips  
 

Enhancing Customer Experience with Generative AI in Financial Services Contact Centers

Santhosh Kumar Ganesan

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 5, 943-949

Abstract: This article explores the transformative impact of Generative Artificial Intelligence (Gen AI) on customer service operations in financial services contact centers. Through a comprehensive case study approach, we examine the implementation of a Gen AI system designed to handle complex financial queries, provide personalized guidance, and ensure regulatory compliance. The article investigates the system's architecture, key features, and integration with existing infrastructure, while analyzing its performance across critical metrics such as First-Call Resolution rates, call handling times, customer satisfaction scores, and operational costs. Our article reveals significant improvements in these areas, with FCR rates increasing by 50%, call handling times decreasing by 40%, and customer satisfaction scores improving by 45%. The article also addresses the challenges and ethical considerations associated with AI-driven customer service in the financial sector, including data privacy, algorithmic bias, and the need for transparency. By providing a detailed analysis of both quantitative improvements and qualitative benefits, this article offers valuable insights for financial institutions considering the adoption of Gen AI technologies to enhance their customer service capabilities and maintain competitiveness in an increasingly digital financial landscape.

Keywords: Generative AI; Financial Services Contact Centers; Customer Experience Enhancement; Regulatory Compliance in AI; AI-Driven Personalized Financial Guidance (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT241051084
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijsrcseit.com/home/article/view/CSEIT241051084 Article URL (text/html)
https://ijsrcseit.com/home/article/download/CSEIT241051084/CSEIT241051084 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v10:y2024:i5:id:386

DOI: 10.32628/CSEIT241051084

Access Statistics for this article

More articles in International Journal of Scientific Research in Computer Science, Engineering and Information Technology from International Journal of Scientific Research in Computer Science, Engineering and Information Technology
Bibliographic data for series maintained by Pankaj Sharma ().

 
Page updated 2026-09-29
Handle: RePEc:jbh:ijsrcs:v10:y2024:i5:id:386