Joshi, Sameer (2025) Technical innovations transforming the property and casualty insurance landscape. World Journal of Advanced Engineering Technology and Sciences, 15 (2). pp. 757-764. ISSN 2582-8266
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Abstract
The property and casualty insurance sector is experiencing profound technological transformation driven by digital innovations that fundamentally restructure traditional insurance models. This technical review explores how cloud-native architectures, artificial intelligence, telematics, and regulatory technologies are reshaping core insurance functions. Cloud platforms with microservices architectures enable superior scalability while significantly reducing operational costs across the insurance value chain. AI-driven algorithmic underwriting systems transcend traditional actuarial models through ensemble learning techniques and deep neural networks, delivering enhanced risk assessment accuracy and processing efficiency. Telematics infrastructure with multiple data acquisition mechanisms has revolutionized auto insurance risk assessment, while RegTech solutions have transformed regulatory compliance through automated monitoring systems and blockchain frameworks. Autonomous vehicle insurance requires fundamentally different technical approaches including Bayesian networks and digital twin simulations, while advanced analytics architectures incorporate sophisticated security implementations such as homomorphic encryption and federated learning. Despite implementation challenges related to legacy system integration, data standardization, and model explainability, emerging directions including quantum computing, edge AI deployment, and decentralized insurance platforms promise to further evolve the technological landscape of property and casualty insurance.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjaets.2025.15.2.0530 |
Uncontrolled Keywords: | Automation; Blockchain; Digitalization; Innovation; Telematics |
Depositing User: | Editor Engineering Section |
Date Deposited: | 04 Aug 2025 16:25 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/3579 |