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从长期动态角度来看,随着用户在网时间的不断增长,用户的缴费行为习惯、消费账单的组成情况等将越来越清晰,就可针对具体用户提供个性化信用度服务。在此期间,具体信用度数值还会随着用户选择业务的变化而发生变化,故应在基准信用度的基础上,就相关事件对具体客户群信用度的影响予以评定,以向用户提供更加符合其真实需求、更能带来价值的产品和服务。
From a long-term dynamic point of view, personalized credit service can be provided for specific users as the user’s online time grows, the user’s payment habits, the composition of consumer bills, etc. become clearer and clearer. During this period, the specific credit value will change with the change of the user’s choice of business. Therefore, based on the benchmark credit rating, the impact of relevant events on the creditworthiness of the specific customer base should be assessed to provide the user with information that is more realistic Demand, more to bring value to the products and services.