REAL-TIME AUGMENTED ANALYTICS FOR ENHANCING CUSTOMER EXPERIENCE IN BFSI

Authors

  • Prof Dr R K Vaithiyanathan

Keywords:

Real Time Analytics, Federated learning, Generative AI, Augmented Analytics, Customer Experience, BFSI, REACT Framework

Abstract

Due to the swift digitization across India’s dynamic financial ecosystem, there is a soaring need for innovative solutions that uphold quality in the delivery of customer experience while also upholding stringent operations and compliance. In this paper, a new end-to-end model, REACT Framework (REaltime Enhanced Analytics for Customer Trust), is introduced to preserve customer privacy and generate actionable insights from the augmented analytics, artificial intelligence, machine learning, and federated learning, all with a new comprehensive study. Using a strong dataset of 1.2 million customer interactions over a number of BFSI channels, the research exploits a thoroughly blended technique, alongside state-of-the-art empirical statistics and intensive qualitative interviews of BFSI market players. Real analytics implementation enables boosting customer satisfaction scores by 27% and response time by 42%. REACT Framework allows proactive engagement, instant query resolution, quicker decision-making, and better fraud and compliance monitoring. Further, it is intended to facilitate integration with newer technologies such as generative AI and blockchain and allow for the growth of the platform for cross-border BFSI operations. Self-service analytics tools empower business users to be self-reliant on analytics and create a data-driven culture by reducing dependency on technical experts. The research also deals with critical challenges such as privacy of data, security, and organizational change management. Overall, real-time augmented analytics operationalized via the REACT Framework becomes a force multiplier for BFSI companies in their efforts to create seamless, personalized & trustworthy customer experiences. Further research can be conducted to explore the growth of the framework for large-scale BFSI markets and to integrate it in the future with the next generation of AI models to improve the customer experience. Actionable recommendations have been offered in the study to Indian BFSI leaders who want to leverage augmented analytics for strategic advantage and sustainable growth in the current competitive scenario.

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Published

2025-05-29

How to Cite

Prof Dr R K Vaithiyanathan. (2025). REAL-TIME AUGMENTED ANALYTICS FOR ENHANCING CUSTOMER EXPERIENCE IN BFSI. Utilitas Mathematica, 122(Special Issue-1), 418–433. Retrieved from https://utilitasmathematica.com/index.php/Index/article/view/2250

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