The application of artificial intelligence in the insurance industry is on the rise
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Recently, Zhongan Insurance and Zhongan Technology jointly released the "AIGC/ChatGPT Insurance Industry Application White Paper", which sorted out more than 30 specific application links and AIGC scenario application points of technology in the insurance field.Generative artificial intelligence technology (AIGC) refers to an algorithm that can learn complex data structures and patterns, and use these patterns to generate new content, data, or problem-solving
Recently, Zhongan Insurance and Zhongan Technology jointly released the "AIGC/ChatGPT Insurance Industry Application White Paper", which sorted out more than 30 specific application links and AIGC scenario application points of technology in the insurance field.
Generative artificial intelligence technology (AIGC) refers to an algorithm that can learn complex data structures and patterns, and use these patterns to generate new content, data, or problem-solving. Compared with traditional machine learning algorithms, the quality improvement of artificial intelligence content generation has exponential development characteristics.
The White Paper proposes that AIGC can not only provide deep technological empowerment in the entire chain of insurance product design, actuarial analysis, marketing, operation, and customer service, but also be applied in various aspects such as daily office work and R&D efficiency improvement for insurance companies.
Fang Rui, CEO of the Internet insurance brokerage platform Yuanbao Group, stated that the company has accumulated a large amount of dialogue data in the insurance and medical fields and is exploring the application of AIGC in customer service, marketing, quality inspection, automatic analysis of insurance terms, claims settlement, and other aspects. Shi Xingtian, the head of Zhongan Insurance Data Science Application Center, expressed the hope of bringing new content and experiences to the industry through data and technology, with the goal of efficient and rapid application implementation, and fully utilizing the capabilities of AIGC.
It is worth mentioning that the White Paper believes that future AIGC technology may be applied to the claims process. For example, based on the claim application materials and policy information provided by customers, automatic or auxiliary processes such as application, evaluation, review, and settlement can be completed to improve claim efficiency, reduce costs, and improve customer satisfaction. As a technology subsidiary of Zhongan Insurance, Zhongan Technology has currently planned to incorporate large model capabilities such as AIGC technology into its entire series of products, exploring a fast, controllable, and replicable AIGC model application path.
According to Fang Rui, based on the current generation capability of AIGC, Yuanbao Group has widely applied AIGC in the production of visual images and videos for insurance products and service consulting. The efficiency of the design team has increased by nearly 30%, and with subsequent optimization, there is still greater room for improvement in efficiency.
Several industry insiders have stated that the insurance industry still faces many challenges when using generative artificial intelligence technology applications. For example, in the marketing process, there may be copyright issues with design outputs, model training issues with professional adaptive insurance data, and security issues with customer personal information. In the operational process, there may be issues with the compliant use of insurance core data and the accuracy of output results. Experts suggest that in practical applications, enterprises should comprehensively consider issues such as data quality, semantic understanding, security risks, misunderstanding risks, and user needs to ensure the accuracy and usability of the model. At the same time, developers and users need to master corresponding skills and experience, combined with artificial intelligence and human judgment, to achieve the best collaborative effect.
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