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Credit Card Application Process and Customer Segmentation Model Study

Author: LiangJinZhao
Tutor: WangJianZhou
School: Lanzhou University
Course: Applied Mathematics
Keywords: Customer Segmentation Ghana model Principal Component Analysis Cluster analysis Particle Swarm BP neural network
CLC: F832.2
Type: Master's thesis
Year: 2010
Downloads: 107
Quote: 2
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Abstract


2008 , the global economic crisis began in the U.S. subprime crisis , and gradually spread to the real economy , as Lehman Brothers and a number of century history of investment banks and bank failures , the financial crisis has gradually become the economic crisis , to the global economy had a disastrous effect . People unemployed for doubtful debts and bad debts are mortgages and credit card loans have become more developed companies before the credit business , the more serious the harm . With China's rapid economic development in recent years , the credit card business in China has also been a the unprecedented golden period of development , and huge client resources and considerable profit for the various commercial banks , but a high degree of competition makes the issuing bank for the audit to apply for credit cards the more relaxed the restrictions , ignoring the risk management and control . In this paper, through careful analysis and research credit card holders , raised the bank to control the risk of credit card operations , can be considered in two ways : first , by credit card customer segmentation , identify quality customers , star customers , the general public customers and risk customers , for each of the sub-groups , the bank should develop corresponding marketing and maintenance strategy , effective use of bank resources , reduce business risk . Second, to establish intelligent credit card application audit model , quickly and accurately from a large number of credit card applicants selected to meet the requirements of the clients issuing credit cards . Therefore, these two aspects separately proposed the audit model corresponding customer segmentation models and credit card applications , credit card data and the German public to do empirical analysis study . This article was first BP neural network model based on particle swarm algorithm applied to the credit card application review and to compare with the traditional BP neural network model , results showed that the traditional BP neural network model soon ran into a local minimum , both for training data or test data accuracy are significantly lower than the BP neural network model based on particle swarm optimization . Customer segmentation model is a segmentation model based on principal component analysis and cluster analysis , credit card customers ultimately broken down into four categories , and give the corresponding customer marketing and maintenance strategy .

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CLC: > Economic > Fiscal, monetary > Finance, banking > China's financial,banking > Banking system and business
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