1. The Meeting of AI and Insurance Underwriting: From “Slow Flow” to “Instant Response” In the health insurance application process, consumers often hesitate due to the complexity of terms and cumbersome processes. Research shows that nearly half of respondents view insurance products as “too specialized,” while the information asymmetry and inefficiency in the underwriting process pose significant challenges to user experience. Traditional underwriting mainly relies on manual review of health information and medical records. Faced with vast amounts of unstructured data, human interpretation is not only time-consuming and subjective but also prone to misjudgment. With the rise of artificial intelligence, particularly large model technology, underwriting has become a critical area where AI is making significant strides in the insurance sector. Nowadays, AI underwriting systems can understand and analyze medical texts, health questionnaires, and insurance terms, achieving a leap from “process assistance” to “intelligent decision-making.”

2. Industry Trend: AI Underwriting is Accelerating Its Shift to Intelligent Decision-Making The logic behind AI underwriting lies in replacing manual judgment in “unstructured segments” with algorithms. AI can automate tasks such as health risk identification, terms matching, and underwriting suggestion generation based on semantic understanding, knowledge graphs, and reasoning capabilities derived from large models. Public company data indicates that several insurtech firms have made remarkable efficiency gains in intelligent underwriting. For instance, Waterdrop Inc. launched its AI underwriting expert “KEYI.AI,” which can reduce average processing time by about 80% and enhance underwriting response speed by hundreds of times, achieving an accuracy rate of nearly 99.8%. These explorations suggest that AI is gradually transforming the underwriting process from manual judgment to intelligent decision-making.

3. Case Study: The Practical Example of Waterdrop Inc.'s AI Underwriting Expert “KEYI” In the domestic market, some insurtech companies have taken the lead in exploring AI underwriting. Waterdrop Inc., for example, has introduced the AI underwriting expert “KEYI.AI,” based on its self-developed large model and insurance knowledge base, covering thousands of current and historical insurance product terms while integrating millions of underwriting knowledge and medical data. According to public information, “KEYI” can cut health insurance underwriting average processing time by 80%, boost underwriting response speed by 260 times, and achieve an underwriting accuracy rate of 99.8%, while increasing the matching rate of declined clients to other suitable products by six times. Importantly, the system offers 24/7 “instant response” capabilities, supporting automated underwriting recommendations, terms interpretation, and claims consultation. It's notable that Waterdrop has also opened the "KEYI" SaaS service to industry partners, enabling system integration in as little as three days. A large brokerage firm reported a 300% increase in onboarding speed for newly hired insurance personnel, with average client consultation time dropping below 50 seconds. From an industry perspective, Waterdrop's efforts validate the feasibility of AI in complex health insurance underwriting scenarios and provide a sample for “AI underwriting platformization.” In addition to exploring the domestic market, multiple insurtech companies are simultaneously initiating international expansion plans. Cheche Technology has outlined its international timeline, planning to kick off its internationalization process in Q4 2025, initially targeting the Asia-Pacific and European markets, followed by expansions into the Middle East and Latin America. Several insurtech firms, including Zhibao Technology, Waterdrop Inc., Shouhui Technology, and Huize Holding, have also announced their overseas plans. Notably, Waterdrop Inc. (WDH) established a licensed insurance brokerage in Hong Kong in 2023 and has developed a relatively mature insurance brokerage service system and partnership network locally. Founder and CEO Shen Peng stated that the company will leverage the successful experiences of its domestic operations to continuously innovate in products and operations, further exploring the application of technology in the international insurance market.

4. From Partial Efficiency to Ecological Synergy: AI Reshaping the Insurance Service Chain The significance of AI underwriting extends beyond the underwriting process itself. Its deeper impact lies in promoting the intelligent upgrade of the entire insurance value chain. - For insurance companies, AI underwriting enhances the precision of risk assessment and the efficiency of underwriting decisions; - For sales and service channels, AI tools reduce the growth cycle of new hires and improve customer communication quality; - For consumers, AI makes terms more understandable, protections more selectable, and services more empathetic. From “AI underwriting experts” to “smart customer service,” “quality inspection systems,” and “smart agent assistants,” AI is facilitating the insurance industry’s transition from a digital operation phase to a new stage of “smart insurance” centered around intelligent decision-making.

5. Think Tank Perspective: Governance Issues in AI Underwriting The rise of AI underwriting also brings new regulatory and governance challenges. The industry must strike a balance in the following three areas: - Algorithm interpretability and transparency — How can we ensure that the judgment logic of AI in the underwriting process is reasonably interpretable, allowing insurance institutions, regulators, and consumers to understand its decision-making basis? - Data security and privacy protection — The high sensitivity of health data necessitates a stricter data compliance system; - Fairness and inclusivity — Could AI exacerbate inequalities in risk selection? While AI significantly enhances the science and efficiency of insurance underwriting, it must also be matched with corresponding institutional innovations and regulatory frameworks to ensure compatibility between technological advancement and public interest.

6. Conclusion: From Algorithm Precision to Data Empathy The essence of AI underwriting is not “replacing humans” but “augmenting humans.” It achieves scientific identification of risks through algorithms and understands the real needs of clients through data. In the future, competition in the insurance industry will no longer be just between capital and channels but rather a contest of algorithm precision, data empathy, and service philosophy. The emergence of intelligent underwriting signifies that the insurance industry is accelerating its transition to the “era of intelligent decision-making.” This is not only a technological revolution but also an industry reshaping centered around trust, responsibility, and empathy.