A Research Of Improving XX Financial Services Company Screening System Of Potential Customers

The rapid development of Chinese economy led to the rapid rise of the SMEs, but SMEs relative to large enterprises, small-scale enterprises, low quality of personnel, R & D investment, lack of sufficient resilience in the fierce competition in the market, which often make SMEs at a disadvantage status. Therefore, in financial sector SMEs are considered high risk in its credit. As a company engaged in financial services enterprises in this market environment, XX company addresses to Solve the SMEs financing problem of slow and difficult.now many SMEs face difficulties, the company’s business development encounter some hinder, the company realizes that the need to develop their business at the same time is improving their own management system. XX company has a huge number of potential customers, it is necessary to improve its screening management system. Through the screening of potential customers, the company can control the risk from the source and increase the company’s business, improve customer service efficiency, so as to provide the majority of SME customers more services to ease the plight of the moment.This article will use the research methods combining theory with practice, and then analyze the practice of progress and documentation relevant studies since the reform and opening up, finally perfect screening system for potential customers.Innovations article may involve three main areas:The first, different from the common existing customer management research, we devote to research on potential customers, and use customized CRM database management system for recording cases of potential customers. The second, for screening index in Screening system for potential customers, we use rough set theory attribute reduction method and the Delphi method for qualitative and quantitative analysis, more objectivity. The third, combining the actual situation of XX financial services company, Screening System question arises at work are which I can come into contact with, so that apply perfected system to actual business work, and make full use of the policy development level and regional differences, before and after the application of statistical data, and then make comparative summary, finally put forward some vision for the financial services and follow-up recommendations in the big data era of rapid development industry.