数据挖掘技术在构建银行个人客户金融负债流失预警模型中的应用  

Application of Date Mining Technology in Building a Warning Model for Financial Debt Loss of Personal Customers in Banks

作　　者：蔡天润 Cai Tianrun(Sassex College of Artificial Intelligence,Zhejiang Gongshang University,Hangzhou 310018,China)

机构地区：[1]浙江工商大学萨塞克斯人工智能学院,杭州310018

出　　处：《科技通报》2023年第6期44-49,共6页Bulletin of Science and Technology

摘　　要：本文以数据挖掘技术在商业银行中的应用为研究对象。介绍数据挖掘基本概念、分析流程、技术方法,数据挖掘有关算法的原理、主要方法、相关技术和工具。结合构建银行客户存款流失模型案例,详细介绍大数据挖掘步骤和相关算法应用比对,论证商业银行可结合行内积累的业务数据信息,形成内外数据合力,切实挖掘数据价值,实现以数据赋能业务发展为导向,充分发挥数字化改革的引领、撬动、赋能作用,促进“科技+金融”、“科技+数字”的融合发展,有效提升商业银行数字化作战能力。This paper focuses on the application of data mining technology in commercial banks.First,it introduces the basic concept,analysis process,technical methods of data mining,and the principles,main methods,related technologies and tools of data mining related algorithms.In combination with the case of building a bank customer deposit loss model,the paper introduces in detail the big data mining steps and the application comparison of related algorithms,and demonstrates that commercial banks can combine the business data information accumulated within the bank to form a resultant force of internal and external data,effectively tap the value of data,achieve data enabling business development oriented,give full play to the leading,leveraging and enabling role of digital reform,and promote the integrated development of“science and technology+finance”“science and technology+digital”,effectively improves the digital combat capability of commercial banks.

关 键 词：数据挖掘 大数据平台 存款流失 分层分类 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]