Generative AI Evolution: Co-Pilot Tools for Claims Processing and Underwriting Enhancement
DOI:
https://doi.org/10.63282/3117-5481/AIJCST-V7I2P103Keywords:
Generative AI, Co-Pilot Tools, Claims Processing, Underwriting, Insurance Technology, Large Language Models, Predictive Analytics, Automation, Explainable AIAbstract
This is because, with the introduction of artificial intelligence (AI) that is generative a lot of industries have been transformed among which is insurance that is a major beneficiary. In the current paper, the authors observe the progress of the generative AI tools that are designed to act as a co-pilot in the claims processing and underwriting, enhancing effectiveness, accuracy and decision-making. A wide range of architecture types such as transformer-based models, large language models (LLMs), and diffusion networks have enabled insurers to automate some of the most complex tasks, such as document analysis, fraud detection, risk assessment, etc. We discuss the integration of these AI systems into the actual work processes, which will result in performance increases, the reduction of manual operations, and cost-efficiency. Among the critical issues, such as data privacy, model bias, and compliance, among others, are discussed as well as possible mitigation measures are provided. Case study and industry survey, as well as experimental studies, are given to measure AI impact. Outcomes: economic Enhancements Economic results in improved relations between both companies have shown that AI tools, which generate content can significantly reduce the time it takes to justify claims, increase precision in the process of underwriting and provide predictive analytics to better control risks. Lastly, the paper covers the developments in the future of generative AI with emphasis on explainable AI (XAI), continuous AI, and human-AI interface architectures
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