Leveraging Artificial Intelligence and Agentic AI Models for Personalized Risk Assessment and Policy Customization in the Modern Insurance Industry: A Case Study on Customer-Centric Service Innovations
Keywords:
AI, insurance, unfair discrimination, unfair differentiation, transparency, explanation, predictive processing, car insurance, health insurance, life insurance, agentic modeling, personalization, risk, customer, algorithmic impact assessment, real-time surveillance, freedom of privacy, algorithmic ethics.Abstract
An insurer, premiums, and discrimination provide a background for AI insurance research. A policyholder insured, for example,
a home against the risk of fire. In return, the policyholder timely pays a premium. If a fire causes damage to the insured object,
the insurer promptly pays out an indemnity.
References
Lakshminarayana Reddy Kothapalli Sondinti, Ravi Kumar Vankayalapati, Shakir Syed, Ramanakar Reddy Danda, Rama Chandra Rao Nampalli, Kiran Kumar Maguluri, & Yasmeen. (2024). Financial Optimization in the Automotive Industry: Leveraging Cloud-Driven Big Data and AI for Cost Reduction and Revenue Growth. The Bioscan, 19(Special Issue-1), 639–645. https://doi.org/10.63001/tbs.2024.v19.i02.S.I(1).pp 639-645
Downloads
Published
2024-12-02
How to Cite
Sneha Singireddy. (2024). Leveraging Artificial Intelligence and Agentic AI Models for Personalized Risk Assessment and Policy Customization in the Modern Insurance Industry: A Case Study on Customer-Centric Service Innovations . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 2532–2545. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2163
Issue
Section
Articles
