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AI-driven CRM systems in insurance: Personalization at scale

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Julker Nain *

Insurance Product Management Researcher.

Research Article
 

World Journal of Advanced Research and Reviews, 2024, 23(02), 2850-2865
Article DOI: 10.30574/wjarr.2024.23.2.2523
DOI url: https://doi.org/10.30574/wjarr.2024.23.2.2523

Received on 20 July 2024; revised on 27 August 2024; accepted on 31 August 2024

The purpose of this research paper investigates artificial intelligence and data analytics phenomena which impact the financial services industry specifically in Customer Relationship Management systems implementation. This document examines contemporary CRM system development together with artificial intelligences in customer analytics and their practical and complex implementation challenges. This research explores how artificial intelligence enhances both personalization operations and customer information and decision-making through natural language processing and machine learning and predictive analysis study. The proof of AI-CRM system performance needs additional clarification based on current evidence from retail banking, wealth management businesses and insurance industries showing positive results. Data privacy aspects along with ethical AI utilization in finance and compliance requirements form essential points studied in the research. The research provides financial service providers with both present-time trends analysis and literature-validated guidelines about implementing AI into the CRM system to generate possibilities for future applications.

AI-Powered CRM; Insurance Personalization; Customer Experience Automation; Predictive Analytics In Insurance; Scalable AI Solutions

https://wjarr.co.in/sites/default/files/fulltext_pdf/WJARR-2024-2523.pdf

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Julker Nain. Ai-driven CRM systems in insurance: Personalization at scale. World Journal of Advanced Research and Reviews, 2024, 23(02), 2850-2865. Article DOI: https://doi.org/10.30574/wjarr.2024.23.2.2523

Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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