Assisted Decision Support System For Insurance Company Based On The Analysis Of Business Data

The amount of insurance company's business data is very large, and it is indeed a huge challenge for the company to quickly process and manage vast amounts of information on businesses. We have developed an insurance data management system in the demand of a Japanese insurance company, while using the SQL Server 2005 in BIDS (Business Intelligence Development Studio) to analysis business data in classification and meanwhile helps the enterprises to find the intrinsic correlation between the data and some information that is hidden behind in the data.Insurance Data Management System allows enterprise employees to get the required data from a large number of data more quickly, and in the same time it will meet some requirements and conditions in the company's data processing, which makes it possible for us to manage the data more efficiently. The data query will be answered faster, and data will be classified more structured. It not only saves a lot of management overheads but also makes work efficient.On the basis of good management on the large amounts of data resources, we also need to study and analysis these data to find the similarities and differences between different customer groups and their tendency to purchase products or the common law of customer buying behavior so as to help enterprises to access new profit growth point. It can not be truly reflected the role of these resources only having these data without finding the intrinsic link between the data and make full good use of the information hidden behind in the business data that is benefit for the corporation. In recent years, with the development of data analysis, data mining and decision-making technology, the model, to find existing laws by means of the analysis of current business data, offers a way of the enterprise for the further development, which of course brings a new opportunity.The first chapter describes the purpose and the meaning of this article, the current status at home and abroad and what has been done. In second chapter, it outlines some of the technologies and modules to build the assisted decision support system for the insurance companies:data management system, knowledge base design, data mining techniques. The third chapter mainly tells the design and implementation of data management systems for the insurance company, according to the practical needs of enterprise. In the forth and the fifth chapter, it is said that how to apply data mining clustering algorithms and decision tree algorithms to build models and improves the model continuously on the basis of the use of insurance data management system to generate a sample library which meets the requirements of user and helps the businesses to complete the classification of the customer, the main customer groups and found what they have in common, providing personalized service for different customer group and makes it possible to get more potential customers. The sixth chapter is mainly for the preceding analysis of the data and concludes.