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摘要翻译：
为满足新巴塞尔协议对操作风险先进计量方法的监管要求，银行内部模型应利用内部数据、相关外部数据、情景分析以及反映业务环境和内部控制制度的因素。操作风险中尚未解决的挑战之一是将这些数据源适当地结合起来。在本文中，我们着重于量化低频高冲击损失超过一些高阈值。我们提出了一种完全可信度理论方法，通过考虑银行内部数据、专家意见和行业数据来估计这些损失的频率和严重程度分布。
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英文标题：
《A "Toy" Model for Operational Risk Quantification using Credibility
Theory》
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作者：
Hans B\"uhlmann, Pavel V. Shevchenko and Mario V. W\"uthrich
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最新提交年份：
2009
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分类信息：
一级分类：Quantitative Finance 数量金融学
二级分类：Risk Management 风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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英文摘要：
To meet the Basel II regulatory requirements for the Advanced Measurement Approaches in operational risk, the bank's internal model should make use of the internal data, relevant external data, scenario analysis and factors reflecting the business environment and internal control systems. One of the unresolved challenges in operational risk is combining of these data sources appropriately. In this paper we focus on quantification of the low frequency high impact losses exceeding some high threshold. We suggest a full credibility theory approach to estimate frequency and severity distributions of these losses by taking into account bank internal data, expert opinions and industry data.
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PDF链接：
https://arxiv.org/pdf/0904.1772
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