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论文编号：	15817
作者编号：	2320233819
上传时间：	2025/12/10 14:46:12
中文题目：	数据驱动的T公司人身险理赔查勘流程再造研究
英文题目：	Research on data-driven reengineering of personal insurance claims investigation process for T Company
指导老师：	姚欣林
中文关键字：	人身保险；保险公估；理赔查勘；流程优化
英文关键字：	life insurance;insurance assessment ;claims investigation;process optimization
中文摘要：	在当前人身保险行业产业格局变化下，低保费多保障产品逐渐占据主导地位，保险公司利润下行，赔付率上升。随着新的监管政策“报行合一”的深入推进、中介渠道承压、保险公司降本增效需求迫切的背景下，传统保险公估行业的生存与发展面临严峻挑战。行业数据显示，超半数公估公司处于亏损状态，其核心困境在于高度依赖人工、效率低下且成本高昂的“盲排式”理赔查勘模式。本研究以作者所在的T公估公司为案例，旨在探索如何利用数据要素驱动理赔查勘流程的再造与优化，以应对行业性难题。 本研究遵循“问题提出-方案设计-实施落地-效果评估”的逻辑主线。首先，深入剖析了行业宏观压力与公估公司自身微观经营困境的根源，指出传统查勘模式是导致查得率低、运营成本高的关键。继而，论文提出了一个双轮驱动的解决方案：其一，整合应用外部公共卫生数据，通过数据比对与互补，精准定位就诊医院调阅就诊病历，从根本上改变了调查的盲目性；其二，基于数据洞察进行彻底的内部流程再造，将传统的“一案到底”串行流程，变革为“调阅分离、专业分工”的工业化流水线模式，实现了调查员、公估师、重案专员和内勤人员的专业化协作。 方案在福建省率先试点落地，在国家对于加快公共数据资源开发利用战略指引下，通过与省大数据中心合作，梳理授权链路完整性，完成数据开发利用场景有效衔接。实施结果表明，数据驱动的流程再造取得了显著成效：公司查勘人员需求降低了60%，整体运营效率提升了三倍，同等人力下案件处理量提升至原来的3-4倍。此外，研究还实现了对跨公司理赔案件的查勘结论复用，进一步提升了行业整体效率。 本研究结论认为，以数据为生产要素，对传统业务流程进行根本性的再思考与再设计，是保险公估这类传统中介服务行业突破发展瓶颈、重塑核心竞争力的有效路径。它为同行企业提供了可借鉴的数字化转型范式，并对保险业如何深化应用公共数据要素以实现降本增效具有重要的实践启示与参考价值。
英文摘要：	Under the current changes in the industrial landscape of the personal insurance industry, low premium multi protection products are gradually taking the dominant position, causing insurance companies to experience a decline in profits and an increase in payout ratios. With the deepening of the new regulatory policy of "integrating reporting and operation", the pressure on intermediary channels, and the urgent need for insurance companies to reduce costs and increase efficiency, the survival and development of the traditional insurance appraisal industry are facing severe challenges. Industry data shows that over half of the appraisal companies are in a loss making state, and their core dilemma lies in the highly dependent, inefficient, and costly "blind sorting" claims investigation model. This study takes the T appraisal company where the author works as a case study, aiming to explore how to use data elements to drive the reengineering and optimization of claims investigation processes to address industry challenges. This study follows the logical mainline of "problem posing - scheme design - implementation and implementation - effectiveness evaluation". Firstly, an in-depth analysis was conducted on the macro pressures in the industry and the micro operational difficulties faced by appraisal companies, pointing out that the traditional survey model is the key factor leading to low survey success rates and high operating costs. Subsequently, the paper proposes a dual wheel drive solution: firstly, integrating and applying external public health data, through data comparison and complementarity, accurately locating hospitals to access medical records, fundamentally changing the blindness of investigations; Secondly, based on data insights, a thorough internal process reengineering is carried out, transforming the traditional "one case to the end" serial process into an industrialized assembly line model of "retrieval separation and professional division of labor", achieving specialized collaboration among investigators, appraisers, case specialists, and internal staff. The plan was first piloted and implemented in Fujian Province. Under the guidance of the national strategy to accelerate the development and utilization of public data resources, through cooperation with the provincial big data center, the integrity of the authorization link was sorted out, and the data development and utilization scenarios were effectively connected. The implementation results show that data-driven process reengineering has achieved significant results: the demand for survey personnel in the company has been reduced by 60%, the overall operational efficiency has been tripled, and the case processing volume under the same manpower has been increased by 3-4 times. In addition, the study also achieved the reuse of survey conclusions for cross company claims cases, further improving the overall efficiency of the industry. The conclusion of this study is that using data as a production factor and fundamentally rethinking and redesigning traditional business processes is an effective path for traditional intermediary service industries such as insurance appraisal to break through development bottlenecks and reshape core competitiveness. It provides a digital transformation paradigm for peer enterprises to learn from, and has important practical implications and reference value for the insurance industry on how to deepen the application of public data elements to achieve cost reduction and efficiency improvement.
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