我国商业银行不良贷款的特征选择

Zhang Yu, Yu Guang, Guan Yong-sheng, Yang Donghui
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引用次数: 2

摘要

近年来,商业银行的巨额不良贷款已成为制约我国商业银行改革与发展的最大障碍之一。如何控制银行不良贷款是金融领域不断探索和研究的核心问题。本文在前人文献的基础上,采用数据挖掘方法中的PCA和relief算法,通过对比商业银行的不良贷款记录,提取和分析商业银行的不良贷款特征。本文收集了某银行96个特征、10415个样本的贷款数据。最后,构建了商业银行不良贷款分类模型。本文的研究对于及时捕捉预警信号,发现不良贷款,促进商业银行的健康经营具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Feature selection of nonperforming loans in Chinese commercial banks
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.
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