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摘要翻译：
信用评级的覆盖是由统计评级模型确定的评级的重要更正。金融机构和银行监管机构同意这一点，因为一方面，企业或银行评级的错误可能会对贷款机构造成致命后果；另一方面，统计方法的错误可以减至最低，但不能完全避免。尽管如此，为了掩盖借款人甚至整个投资组合的真实风险，评级覆盖可能被滥用。这就是为什么通常严格管理和仔细记录评等覆盖。但是，在预定义的时间段内，对于给定的评等模型，覆盖的频率是否合适尚不清楚。本文认为，存在一个与统计评级模型相关的自然错误率，该模型可以用来评估观察到的覆盖率是否足够。自然错误率与评级模型的判别能力密切相关，可以很容易地计算出来。
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英文标题：
《Bounds for rating override rates》
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作者：
Dirk Tasche
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最新提交年份：
2012
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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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一级分类：Statistics 统计学
二级分类：Applications 应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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英文摘要：
Overrides of credit ratings are important correctives of ratings that are determined by statistical rating models. Financial institutions and banking regulators agree on this because on the one hand errors with ratings of corporates or banks can have fatal consequences for the lending institutions and on the other hand errors by statistical methods can be minimised but not completely avoided. Nonetheless, rating overrides can be misused in order to conceal the real riskiness of borrowers or even entire portfolios. That is why rating overrides usually are strictly governed and carefully recorded. It is not clear, however, which frequency of overrides is appropriate for a given rating model within a predefined time period. This paper argues that there is a natural error rate associated with a statistical rating model that may be used to inform assessment of whether or not an observed override rate is adequate. The natural error rate is closely related to the rating model's discriminatory power and can readily be calculated.
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PDF链接：
https://arxiv.org/pdf/1203.2287
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