Critical Business Episodes: The criticality of damage adjustment processes in insurance relationships
University of Edinburgh MA Social Policy and Economics, United Kingdom.
Review Article
GSC Advanced Research and Reviews, 2024, 20(03), 327-339.
Article DOI: 10.30574/gscarr.2024.20.3.0320
Publication history:
Received on 16 August 2024; revised on 21 September 2024; accepted on 23 September 2024
Abstract:
This research study seeks to explore damage adjustment procedures in insurance contracts as far as their effects on customers and organizational performance are concerned, and the general stability of insurance businesses. Employing the industry reports- customer satisfaction surveys and technological integration in the analysis, this research identifies the degree of the study’s test hypothesis that shows the real impact of efficient damage assessment and creates solution aiming to improve policyholder’s trust, insurer’s financial stability and prevent fraud. Here the research studies the current state of the insurance sector, taking into account changes in legislation, the introduction of new technologies and possibilities such as artificial intelligence and machine learning, as well as new customer profiles and behaviors. Some of the objectives involve the ability of efficient and transparent claims processing on consumer preferences, possibility of using modern technologies for managing claims, and also studying experiences in identifying fraud phenomena. This dissertation seeks to provide a clearer perspective of how damage adjustment procedures determine the nature of insurance relationships and guarantee any rightful deserving claims for all relevant parties. Introducing theories that range from behavioral economics to game theories as well as agency norms, this study proffers ways of improving the nature and methods of damage adjustment for improved efficiency in the insurance business.
Keywords:
Damage Adjustment; Insurance Relationships; Customer Satisfaction; Fraud Mitigation; Technological Integration; Artificial Intelligence
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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
