DocumentCode :
127221
Title :
Feature selection of nonperforming loans in Chinese commercial banks
Author :
Zhang Yu ; Yu Guang ; Guan Yong-sheng ; Yang Dong-hui
Author_Institution :
Sch. of Manage., Harbin Inst. of Technol., Harbin, China
fYear :
2014
fDate :
17-19 Aug. 2014
Firstpage :
1208
Lastpage :
1215
Abstract :
In recent years, huge amounts of nonperforming loans (NPLs) of commercial banks have become one of the biggest obstacles constraining reform and development in Chinese commercial banks. Finding a way to control the banks´ NPLs is a core issue that it continues to be explored and researched in the finance. In this paper, PCA and relief algorithm in data mining methods were adopted to extract and analyze NPLs characteristics in commercial banks through contrasting the performing and nonperforming loans records, based on the predecessors´ literatures. In this paper, a bank´s loans data with 96 features and 10415 samples is collected. At last, we construct nonperforming loans of commercial banks classification model. Our research is very important for capturing warning signal timely, detection of NPLs and sound operation of commercial banks.
Keywords :
banking; data mining; feature selection; financial data processing; fraud; pattern classification; principal component analysis; Chinese commercial banks; NPL characteristics; PCA; bank loan data; commercial bank classification model; data mining methods; feature selection; nonperforming loans records; reform and development; relief algorithm; warning signal capturing; Analytical models; Data mining; Economics; Feature extraction; Indexes; Predictive models; Principal component analysis; PCA-relief algorithm; commercial banks; feature selection; nonperforming loans;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management Science & Engineering (ICMSE), 2014 International Conference on
Conference_Location :
Helsinki
Print_ISBN :
978-1-4799-5375-2
Type :
conf
DOI :
10.1109/ICMSE.2014.6930367
Filename :
6930367
Link To Document :
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