Research On Financial Loss Customer Mining Model Based On K-MEANS Clustering And Association Model

With the advent of the era of economic globalization and network big data,financial banks are experiencing a period of transformation and upgrading.Facing a series of challenges such as financial internationalization and online finance,there have been single products and services,customer loyalty,and customer churn.As a popular technology,data mining is constantly recognized by society.Through data mining tools,analysis and mining of business information data can be realized.Use data mining tools to mine the huge data resources that banks currently have,and provide enterprises with the support of data operations.Utilizing digital operations to promote the development of financial banks towards refined management and maintain their core competitiveness in the market in the era of big data.Supporting financial banks' operating strategies with massive data storage and data mining can effectively promote the management revolution and technology of financial banks revolution.As an important technical means,how to combine data mining with customer relationship management and use information technology means to provide theoretical models and practical cases for precise marketing of financial banks has become a deep topic.This article mainly studies the data loss in the customer management of financial banks as the starting point to explore the application of data mining in financial banks.Combine the characteristics of financial bank customer management,use K-MEANS clustering and association rules to mine and predict churn customers,describe the churn customers,and use the marketing of predicted churn customers to evaluate the entire research results in the later stage and feedback.This article will focus on describing the full life cycle process of data mining in the scenario of predicting customer churn,using a real-world database case in a commercial warehouse's data warehouse,using R language modeling,and focusing on K-MEANS clustering and association rules.The performance of churn customer modeling results,especially the feedback and application effect evaluation applied to customer management marketing,so as to use this solution to build a marketing management system for data mining and customer management marketing activities for industry reference.