The loss distribution approach (LDA) has evolved as the industry standard for operational risk models despite a number of known weaknesses. In particular, LDA’s traditional focus on historical loss data often neglects expert knowledge that is available for operational risk types of a more predictable nature. In this paper, we present an alternative quantification technique, so-called exposure-based operational risk (EBOR) models, which aim to replace historical severity curves by measures of current exposures and use event frequencies based on actual exposures instead of historical loss counts. We introduce a general mathematical framework for exposure-based modeling that is applicable to a large number of operational risk types.As an example, an EBOR model for litigation risk is presented. Further, we discuss the integration of EBOR and LDA models into hybrid frameworks facilitating the migration of operational risk subtypes from a classical to an exposure-based treatment. The implementation of EBOR models is a challenging task since new types of data and a higher degree of expert involvement are required. In return, EBOR models provide a transparent quantitative framework for combining forward-looking expert assessments, point-intime data (eg, current portfolios) and historical loss experience. Individual loss events Corresponding author: M. Einemann Print ISSN 1744-6740 j Online ISSN 1755-2710 © 2018 Infopro Digital Risk (IP) Limited 1 Journal of Operational Risk To subscribe to a Risk Journal visit subscriptions.risk.net/journals or email info@risk.net www.risk.net/journals

中文翻译：

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超越损失分布方法的操作风险计量：一种基于敞口的方法

尽管存在许多已知的弱点，但损失分布方法 (LDA) 已发展成为操作风险模型的行业标准。特别是，LDA 对历史损失数据的传统关注往往忽略了可用于更可预测的操作风险类型的专家知识。在本文中，我们提出了一种替代的量化技术，即所谓的基于暴露的操作风险 (EBOR) 模型，其目的是用当前暴露的度量代替历史严重性曲线，并使用基于实际暴露而非历史损失计数的事件频率。我们介绍了适用于大量操作风险类型的基于风险敞口的建模的通用数学框架。例如，提出了诉讼风险的EBOR模型。更多，我们讨论了将 EBOR 和 LDA 模型整合到混合框架中，促进操作风险子类型从经典处理迁移到基于暴露的处理。EBOR 模型的实施是一项具有挑战性的任务，因为需要新类型的数据和更高程度的专家参与。作为回报，EBOR 模型提供了一个透明的量化框架，用于结合前瞻性专家评估、时间点数据（例如，当前投资组合）和历史损失经验。个人损失事件 通讯作者：M. Einemann Print ISSN 1744-6740 j Online ISSN 1755-2710 © 2018 Infopro Digital Risk (IP) Limited 1 Journal of Operational Risk 要订阅风险期刊，请访问 subscriptions.risk.net/journals 或发送电子邮件info@risk.net www.risk.net/journals EBOR 模型的实施是一项具有挑战性的任务，因为需要新类型的数据和更高程度的专家参与。作为回报，EBOR 模型提供了一个透明的量化框架，用于结合前瞻性专家评估、时间点数据（例如，当前投资组合）和历史损失经验。个人损失事件 通讯作者：M. Einemann Print ISSN 1744-6740 j Online ISSN 1755-2710 © 2018 Infopro Digital Risk (IP) Limited 1 Journal of Operational Risk 要订阅风险期刊，请访问 subscriptions.risk.net/journals 或发送电子邮件info@risk.net www.risk.net/journals EBOR 模型的实施是一项具有挑战性的任务，因为需要新类型的数据和更高程度的专家参与。作为回报，EBOR 模型提供了一个透明的量化框架，用于结合前瞻性专家评估、时间点数据（例如，当前投资组合）和历史损失经验。个人损失事件 通讯作者：M. Einemann Print ISSN 1744-6740 j Online ISSN 1755-2710 © 2018 Infopro Digital Risk (IP) Limited 1 Journal of Operational Risk 要订阅风险期刊，请访问 subscriptions.risk.net/journals 或发送电子邮件info@risk.net www.risk.net/journals 当前投资组合）和历史损失经验。个人损失事件 通讯作者：M. Einemann Print ISSN 1744-6740 j Online ISSN 1755-2710 © 2018 Infopro Digital Risk (IP) Limited 1 Journal of Operational Risk 要订阅风险期刊，请访问 subscriptions.risk.net/journals 或发送电子邮件info@risk.net www.risk.net/journals 当前投资组合）和历史损失经验。个人损失事件 通讯作者：M. Einemann Print ISSN 1744-6740 j Online ISSN 1755-2710 © 2018 Infopro Digital Risk (IP) Limited 1 Journal of Operational Risk 要订阅风险期刊，请访问 subscriptions.risk.net/journals 或发送电子邮件info@risk.net www.risk.net/journals