According to data from the State Administration of Financial Supervision and Administration, from January to June this year, the insurance industry has accumulated compensation expenditures of 1.3458 trillion yuan, a year-on-year increase of 9.4%, higher than the original premium income growth rate of 5.3% during the same period. Overall, it continues the development trend of recent years - while the business scale steadily grows, the growth rate of compensation amount is significantly higher than that of premium scale. Upon closer examination, the "scissors gap" between claims and premium growth rates reflects that the insurance industry has entered a new stage of development. On the one hand, the industry is actively returning to the source of protection, exploring effective ways of "insurance industry surname protection", focusing on the personalized, diversified, and constantly upgrading insurance protection needs of different age groups and types of people as the starting point, designing and launching an inclusive insurance product system that covers all age groups of specific groups such as new citizens, new business groups, elderly population, students and children. In particular, urban customized insurance and other inclusive insurance "phenomenal" products developed based on Internet platform and digital technology have developed rapidly, the coverage of insurance services has been significantly expanded, the proportion of security products has been significantly improved, and the risk assurance ability and quality and efficiency of serving people's livelihood have been continuously strengthened. On the other hand, the risk structure faced by the insurance industry is undergoing changes. During the period of rapid industry growth, long-term policies such as annuity insurance and critical illness insurance sold are gradually entering the payment period with the passage of time and the increasing age of the insured, resulting in corresponding increases in compensation expenses; The combination of sustained economic and social development, rapid advances in medical technology, and increasingly complex disease spectrum has led to increased risks of longevity and disease, as well as higher medical expenses and corresponding compensation costs. This situation reminds us that with the increasing penetration depth of the insurance industry in the social economy, the industry's quality and efficiency are constantly improving, and the development problems it faces are also undergoing changes. The business structure and business model are bound to face the challenge of upgrading and reshaping. As the scale continues to grow, many consumers have gained an understanding of the basic functions of life insurance products. If the development theme of personal insurance in the past was to broaden its reach and tap into new customers, then the current focus of development will be to deeply tap into existing customers, fill their protection gaps, meet their financial planning and wealth management needs, and further extend the insurance value chain. The industry increasingly needs to provide consumers with more refined lifecycle risk management services, effectively analyze and predict customer needs, proactively provide more targeted risk reminders, product recommendations, risk prevention and control suggestions, and other personalized services to meet the diverse, personalized, and dynamically changing needs of consumers. The continuous operation of the industry, coupled with the digital transformation promoted in recent years, has enabled insurance institutions to accumulate massive amounts of data in various aspects such as product design, underwriting and claims, and customer service. Therefore, they can rely on advanced technologies such as big data analysis and artificial intelligence to deeply explore the value of data, including insight into customer needs, analysis of claims data, timely discovery of potential risk points, optimization of risk control models, and improvement of risk management capabilities. This has also gradually transformed the data-driven development model of the insurance industry into a reality. For example, the insurance industry can achieve data exchange with medical institutions, medical insurance systems, third-party data platforms, etc., to obtain real-time information on customer visits, treatments, cost settlements, etc., and rely on artificial intelligence and big data analysis technology to conduct real-time intelligent review of claims cases. With the conditions, it can achieve direct or even no compensation for medical insurance, significantly improving the sense of gain for insurance consumers. The demand of life insurance consumers ultimately falls on aspects such as health, longevity, and safety. The improvement of quality and efficiency in various business processes is not the end point. The industry's continuous enrichment of its own connotation and evolution towards a new paradigm of "service embedding ecological synergy" are the logical direction for long-term sustainable development. For example, the insurance industry can break through traditional business boundaries and deeply integrate health monitoring, disease prevention, medical services, etc. with insurance products, seamlessly embedding insurance services into various scenarios such as medical health and transportation, providing customers with one-stop protection solutions, achieving a virtuous cycle of "less illness, less accident, less claims, and low premiums", and enhancing customer experience and service value; We can also explore more innovative profit models to promote the transformation and upgrading of the industry from a single risk protection provider to a comprehensive ecological service platform, and help personal insurance achieve a leap from efficiency improvement to value creation. Of course, there are differences in the resource endowments and development strategies of different insurance institutions, and their upgrading paths and methods are also different. It is not necessary to pursue the so-called best business model, avoid blind expansion, or "follow the trend" or "pile up". Instead, it is necessary to leverage their respective comparative advantages, plan development paths reasonably, establish sound management systems, cultivate stable talent teams, and provide a continuous source of power for innovative development to promote high-quality transformation and upgrading. Regulatory authorities should also continue to improve data sharing, data security, and privacy protection rules, build a compliance defense line for data-driven development, and establish a regulatory framework that adapts to the ecological synergy model, balancing the relationship between development and regulation, innovation and risk. (New Society)