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中国银行业操作风险外部损失事件的跨机构数据库 1986-2023年
Xiaoqian Zhu1,2, Yanpeng Chang3,4, Jianping Li5,6
1School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China.
Scientific data
|August 28, 2024
概括
本研究介绍了一种使用文本挖掘的自动化框架,用于构建公共-中国运营损失数据 (P-COLD) 数据库,克服了用于运营风险分析的手动数据收集限制.
科学领域:
- 金融风险管理 金融风险管理
- 数据科学数据科学数据科学
- 计算语言学 计算语言学
背景情况:
- 目前的运营风险数据收集是劳动密集型的,导致数据缓慢,不一致和不足.
- 在公开可用的运营风险数据库中存在一个重要的缺口,用于有效的风险分析.
研究的目的:
- 开发一个针对运营风险的自动化数据收集框架.
- 构建和扩展公共-中国运营损失数据 (P-COLD) 数据库.
主要方法:
- 网络扫描用于自动收集运营风险新闻.
- 文本挖掘技术用于内容分析和关键信息提取.
- 每个记录有12个关键数据点的数据库构建.
主要成果:
- 创建了P-COLD数据库,包含从1986年到2023年的3723条记录.
- 它是中国最大和最全面的外部运营风险数据库之一.
- 每个记录都详细说明了操作风险事件,包括发生时间和损失金额等信息.
结论:
- 自动化框架显著提高了运营风险数据收集效率和质量.
- P-COLD数据库为金融机构提供了宝贵的资源.
- 该数据库预计将推进运营风险资本计算,依赖性分析和内部控制.
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