大数据下的零售客群数据模型设计与研究

Design and Research of Retail Customer Data Model under Big Data

针对利率市场化改革和客户需求,银行零售业务的成功要素渐渐由过去的关系营销与激励驱动、不断持续补充资本、客户结构以大客户和中大客户为中心所主导的粗放式经营模式发展为科技引领、数据驱动、以客户为导向中心的专业服务、模式创新等关键因素引领的精细化客群管理化模式。试图结合新常态下的信息元素,以银行业庞大的存量客户群为基础,利用数据为抓手构建零售客群数据模型,创新性地提出一种“因果预测分析+线性分类+迭代修正”的新数据挖掘模型和一种定其“位”+验其“效”+探其“好”的贵宾客户提升数据挖掘模型,为商业银行各级管理人员清晰地展示客群经营转型的精细化目标和管理方法。

For the market-based reform of interest rates and customer requirements,the success factor of the retail banking business,the extensive business model,which is dominated by the past relationship marketing and incentive drive,continuous supplemental capital and big and medium customers-oriented structure,has been developed into the fine customer base management model led by key factors,such as the technology-led,data-driven and customer-oriented professional services and model innovation,etc.This paper aims to explore and ana⁃lyze the operational transformation of the retail customer base using data based on the enormous stocking customer base of the banking in⁃dustry according to information elements under the new normal,which mainly includes a combined mode of causal forecasting and analysis,linear classification and iterated revision for the application of new data mining,and a method to increase and mine VIP customers by posi⁃tioning its location,verifying the effect and exploring the benefit.