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            <title xml:lang="en">Research on Customer Credit Scoring Model Based on Bank Credit Card</title>
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                <forename type="first">Maoguang</forename>
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                <title xml:lang="en">Research on Customer Credit Scoring Model Based on Bank Credit Card</title>
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                  <title>11th International Conference on Intelligent Information Processing (IIP)</title>
                  <date type="start">2020-07-03</date>
                  <date type="end">2020-07-06</date>
                  <settlement>Hangzhou</settlement>
                  <country key="CN">China</country>
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                <editor>Zhongzhi Shi</editor>
                <editor>Sunil Vadera</editor>
                <editor>Elizabeth Chang</editor>
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                <term xml:lang="en">Logistic Regression</term>
                <term xml:lang="en">Information divergence</term>
                <term xml:lang="en">Information Value</term>
                <term xml:lang="en">Personal credit system</term>
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              <p>With the development of China’s economy, especially the maturity of the market economy, credit is important to the society and individuals. At present, credit system is mainly divided into two parts. Enterprise credit system is an important part of social credit system. But at the same time, as the foundation of social credit system, the establishment of the personal credit system is of great significance to reduce the cost of collecting information and improve the efficiency of loan processing. At the bank level, this paper discretizes the credit card data of a bank, selects the features by calculating Weight of Evidence and Information Value, and information divergence, then uses Logistic Regression to predict. Finally, the results of the Logistic Regression are transformed into visualized credit scores to establish a credit scoring model. It is verified that this model has a good prediction effect.</p>
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          <orgName>Central University of Finance and Economics [Beijing]</orgName>
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              <addrLine>Central University of Finance and Economics39 South College Road, Haidian DistrictBeijing, P.R.China　100081</addrLine>
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