监管政策让保障类保险重回主流，在此趋势之下健康类保险重新得到快速发展。第三方数字化中台TPA为保险公司中台各项业务提供了数字化的解决的方案。案例公司栈略数据在多方面在行业内处于领先位置，是行业内公司的典型代表。本文以栈略数据公司为例，主要围绕数字化中台提供的数字化理赔服务展开，从其处理保险理赔的业务模式和效率的角度对数字化理赔中台进行分析。在对数字化理赔对传统模式优化的分析中，本文对保险价值链、理赔流程、理赔流程存在的问题以及商业模式核心要素进行了分析。研究表明，理赔环节是保险价值链中重要的基础活动。通过优化信息系统来优化理赔对于保险公司而言较为困难，这是第三方数字化理赔能够存在的重要原因。数字化理赔流程与传统理赔有巨大的不同，其解决了传统理赔在实际业务和价值观层面的众多问题。医疗、理赔等层面的核心数据在实际开展业务中获取困难，是保险数字化中台行业的重要核心资源。医疗服务提供方与商保公司的互通，以及大型保险公司对数字化理赔系统的自建会对行业发展以及行业内壁垒造成一定影响。在进一步对数字化理赔效率进行分析的过程中，本文分别对智能理赔模型效率自我迭代优化和理赔效率的影响因素进行了分析。研究表明，智能化理算风控的效率在原理和效果上，具有自我不断迭代优化的特点。在控制各保险产品使用模型基本一致的情况下，非自动化因素也会随处理案件增多而自我优化。第三方数字化理赔可以一定程度消除保险核保、承保阶段的风险控制对理赔效率的影响。
Regulatory policies make protection-oriented insurance became mainstream. In this trend, health insurance develops rapidly again. TPA provides digital solutions for many businesses done by insurance company’s middle office. The case company is in the leading position of the industry in many aspects, and is a typical representative company in the industry. This paper takes Leapstack as an example. This paper mainly focuses on the digital claim settlement service provided by the third-party insurance digital middle office, and analyzes the digital claim settlement from the perspective of its business model and efficiency in settling insurance claims.In the analysis of the optimization of digital insurance claims settlement, this paper focus on the insurance value chain, claims settling process, existing problems of claims settling process and core elements of the company’s business model. Research shows that claims settlement is an important basic activity in the insurance value chain. It is difficult for insurance companies to optimize claims settlement by optimizing their information system, which is an important reason for the existence of third-party digital claims settlement service. The digital claims settling process is vastly different from the traditional process, through which it solves many problems in the aspect of practical business and moral values of the traditional claims settling process. Core data of medical treatment and claims settlement in practice is difficult to be obtained, which make it become an important core resource of the business model. The communication between medical service providers and commercial insurance companies as well as the self-construction of digital claim settlement system by large insurance companies, may have a certain impact on the development of the industry and its key barriers. In the analysis of digital claims settlement efficiency, this paper focus on the self-iterative optimization of intelligent claims settlement model and the influencing factors of claims settlement efficiency. The research shows that the efficiency of intelligent risk control system is characterized by self-iterative in mechanism and effect. Under the condition that the intelligent models used by all insurance products are basically the same at the same time, the non-automatic factors will optimize with the increase of cases they settled. The third-party digital claims settlement service can eliminate the impact of risk control in underwriting process on the claims settlement efficiency to a certain extent.
