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Abstract
This paper firstly discussed several credit scoring models and their development history, then designed the target system of individual credit scoring with individual housing loans data of a stated-owned commercial bank and logistic method, and established an individual credit scoring model including testing. Finally, the paper discussed the application of the individual credit scoring model in consumer credit domain, and brought forward corresponding conclusions and policies.
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Authors and Affiliations
School of Management, Graduate University of Chinese Academy of Sciences, Beijing, 100190, China
Yihan Yang & Lingling Zhang
Chinese Academy of Sciences Research Center on Fictitious Economy and Data Science, Beijing, 100190, China
Guangli Nie & Lingling Zhang
- Yihan Yang
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- Guangli Nie
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- Lingling Zhang
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Editor information
Editors and Affiliations
Center for Computation & Technology, Louisiana State University, 216 Johnston Hall, LA 70803, Baton Rouge, USA
Gabrielle Allen
Poznań Supercomputing and Networking Center, Poznań, Poland
Jarosław Nabrzyski
Center for Computation and Technology, Louisiana State University, LA 70803, Baton Rouge, USA
Edward Seidel
Department of Mathematics and Computer Science, University of Amsterdam, Kruislaan 403, 1098 SJ, Amsterdam, The Netherlands
Geert Dick van Albada
Computer Science Department, University of Tennessee, TN 37996-3450, Knoxville, USA
Jack Dongarra
Faculty of Sciences, Section of Computational Science, University of Amsterdam, Kruislaan 403, 1098 SJ, Amsterdam, The Netherlands
Peter M. A. Sloot
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Yang, Y., Nie, G., Zhang, L. (2009). Retail Exposures Credit Scoring Models for Chinese Commercial Banks. In: Allen, G., Nabrzyski, J., Seidel, E., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds) Computational Science – ICCS 2009. ICCS 2009. Lecture Notes in Computer Science, vol 5545. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01973-9_71
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