摘要
保险行业在中国是一个快速发展的朝阳行业,业务的急剧增长带来了更多的客户信息。随着保险公司的网络速度和服务器处理能力不断提高,基于数据的商业智能业务分析也逐渐成为趋势。近几年保险业在中国快速发展,客户量不断上升,保险公司的各项运营成本也在大幅度增加。保险公司的业务收入一方面是来自新客户的保费,更重要的是续期客户的保费收入。续期保费收入具有比较高的稳定性和连续性的特点,是保险公司利润的主要来源,是保险公司持续发展的坚实基础。目前保险公司续期收费的方式比较单一,对客户采取同样的催交和通知方式,管理方式粗放,不利于保险风险和成本控制。
本文基于数据挖掘分类方法,分析现有客户的缴费情况,发掘交费概率和交费次数以及交费准时程度的关系,将客户细分为优质客户、准优质客户、忠诚客户、非稳定客户等几类。利用决策树和多元线性回归方法,建立续期客户交率的预测模型,指导续期部门对不同客户采取差异化的催交策略。使保险公司客户管理更有针对性,降低客户保费迟缴、忘缴等风险,并降低管理成本。同时,利用聚类方法,从大量的客户中分析具有较高退保风险的客户,采取相应措施,尽量降低退保事件发生的概率,从而提高续期收费的成功率,提高公司的保单品质,确保公司长期经营发展。
在充分考虑保险公司实际经营需求基础上,将本文所研究的客户续期保单分析模型进行实现,并设计与实现人寿保险品质管理系统。该系统在太平人寿四川分公司顺利应用,系统运行效果好。为该公司保单续期工作的高效开展、控制退保风险和运营成本、提升客户服务和业务品质提供了有力的工具和准确的数据参考。
The insurance industry in China is a rapidly developing industry, business grows quickly to bring more customer information. Along with the insurance company's network speed and server processing capacity continue to improve, based on the data of business intelligence and analysis has gradually become a trend. In recent years, insurance industry in China develops rapidly, the rising volume of customers, the insurance company of the operating costs have increased by a large margin. Insurance company business income is from first-year premium, more important is the renewal premium. Renewal premium has higher stability and continuity characteristics, is the main source of profit, and is a solid foundation for insurance company. At present the way of getting renew premium in insurance company’s very simple,for every customer,they give notice in the same way,it cost a lot and waste a lot. does not favor the insurance risk and cost control.
This thesis try to use data mining technique and classification method to analyze the activities of customer in payment,to discover the relationship between the possibility of payment and how many times they have paid and when they have paid the premium. According to the information of customer,we partition the customer in several group,such as high quality customer,quasi high quality customer,faithful customer and risk customer.Using decision tree and multi-variable regression, we make a prediction model to estimate the possibility of a certain customer’s activity in payment . guide the renewal sectors for different clients to take the difference of expediting strategy. The insurance company customer management more targeted, reduce customer premium late payments, forgot to pay, and reduce the cost of management. At the same time, use clustering method, from a large number of customers with high risk analysis portion of customers, we try to identify the high-risk surrender customer from the large amount of customers.so as to promote the renewal work, improve the company's quality policy, to ensure that the company's long-term business development.
Considering the actual demand of insurance company operation, according to the insurance company’s hardware and software environment, and the insurance’s situation of data, using data mining method, establishes the customer and renewal policy analysis method and model, design the insurance of quality management system, and in the Taiping Life Sichuan Branch successfully applied,through the test and on the line, the system reliable, the effect is very good, to achieve the function, for the control risk and operating costs, improve customer service and service quality to provide a strong and accurate tool and data reference.
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