大模型技术深度赋能保险行业白皮书（2024）

Industry Investment Rating - The report highlights the transformative potential of large model technology in the insurance industry, indicating a positive outlook for investment in this sector [1][2][3] Core Viewpoints - Large model technology is driving a significant transformation in the insurance industry, with applications ranging from customer service to risk management and product innovation [2][3][4] - The integration of large models is reshaping the competitive landscape and ecosystem of the insurance industry, enabling more precise risk prediction and management [4] - The report emphasizes the importance of collaboration between insurance companies and tech firms to build an open, shared, and collaborative innovation ecosystem [3] Summary by Sections Introduction - 2023 marked a breakthrough year for large model technology, with ChatGPT leading the way in revolutionizing human-computer interaction and signaling the dawn of a new intelligent era [1] - The insurance industry has seen profound changes due to this technological revolution, with companies like Sunshine Insurance leading the charge in applying large models to reshape business models [2] Strategic Vision and Industry Trends - The global insurance industry is undergoing a shift from traditional "assessment and service models" to "predictable, personalized, and ecosystem-based models" [75][76] - Digital transformation is essential for insurance companies to enhance customer experience, optimize risk management, and improve operational efficiency [84][85][86] Practical Applications in Insurance - Large model technology has been widely applied in various insurance business scenarios, including customer service, claims assessment, marketing, and underwriting [3][58] - Initial applications have focused on low-risk, high-efficiency scenarios such as intelligent office assistants and coding support tools, with gradual expansion into higher-value areas like marketing and sales [59][60][61] Technological Developments - Significant progress has been made in data synthesis, computing power, and model optimization, with synthetic data playing a crucial role in overcoming data shortages [12][13][14] - The rise of multimodal models and edge-side computing is expected to influence future terminal applications, offering advantages in cost, energy efficiency, and privacy [26][27][30] Challenges and Future Outlook - The insurance industry faces challenges such as reasoning speed bottlenecks, accuracy limitations, and regulatory compliance issues when applying large model technology [69][70][71] - Despite these challenges, the potential for large models to drive innovation and efficiency in the insurance industry remains substantial, with ongoing advancements expected to address current limitations [73]