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Enhancing Customer Experience with Generative AI in Financial Services Contact Centers

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  • Santhosh Kumar Ganesan

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.

Suggested Citation

  • Santhosh Kumar Ganesan, 2024. "Enhancing Customer Experience with Generative AI in Financial Services Contact Centers," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 10(5), pages 943-949, October.
  • Handle: RePEc:jbh:ijsrcs:v10:y2024:i5:id:386
    DOI: 10.32628/CSEIT241051084
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT241051084
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