The Future of Insurance Technology: Leveraging AI for Transformation in Property and Casualty

Naveen Kondeti

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025, vol. 11, issue 1, 2919-2926

Abstract: This article explores the transformative impact of Artificial Intelligence (AI) on the property and casualty (P&C) insurance sector, focusing on key technological advancements reshaping core insurance operations. This article examines how AI-driven solutions are revolutionizing traditional underwriting processes, enhancing claims management efficiency, and strengthening fraud detection capabilities. Through an analysis of cloud-based platforms like Guidewire, it investigates the integration challenges and opportunities in implementing AI solutions within existing insurance infrastructure. It highlights how machine learning models, computer vision, and predictive analytics are enabling insurers to achieve more accurate risk assessment, automated claims processing, and sophisticated fraud prevention. It also suggests that the successful adoption of AI technologies in P&C insurance not only improves operational efficiency but also enables insurers to deliver more personalized products and enhanced customer experiences. The article concludes by examining emerging trends and providing strategic recommendations for insurers navigating this technological transformation, emphasizing the critical balance between innovation and regulatory compliance in the evolving insurance landscape.

Keywords: Artificial Intelligence in Insurance; roperty and Casualty Digital Transformation; Automated Underwriting Systems; Claims Process Automation; Insurance Fraud Detection Analytics (search for similar items in EconPapers)
Date: 2025
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112295
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijsrcseit.com/home/article/view/CSEIT251112295 Article URL (text/html)
https://ijsrcseit.com/home/article/download/CSEIT251112295/CSEIT251112295 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v11:y2025:i1:id:963

DOI: 10.32628/CSEIT251112295

Access Statistics for this article

More articles in International Journal of Scientific Research in Computer Science, Engineering and Information Technology from International Journal of Scientific Research in Computer Science, Engineering and Information Technology
Bibliographic data for series maintained by Pankaj Sharma (USA) ().