Within a loss distribution approach (LDA) framework, we propose to model catastrophic operational risk using a compound Neyman–Scott clustering model. The particularity of this compound model is that it relies on a Neyman–Scott process (the frequency component of the LDA) to model the occurrence behavior of catastrophic operational loss events. The motivation behind this is that catastrophic operational risk may be the manifestation of a two-level risk generation mechanism: on the first level, natural and human-made catastrophes (referred to as operational storms) occur and trigger, on the second level, clusters of catastrophic operational loss events. A graphical analysis based on a historical series of 334 extreme operational loss events supports the clustering structure of the event occurrences. The calibration of the Neyman–Scott process reveals a satisfactory model fitness and underlines the high vulnerability of financial organizations to eventual operational storms.

中文翻译：

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使用复合 Neyman-Scott 聚类模型对灾难性操作风险进行建模

在损失分布方法 (LDA) 框架内，我们建议使用复合 Neyman-Scott 聚类模型对灾难性操作风险进行建模。这种复合模型的特殊性在于它依赖于 Neyman-Scott 过程（LDA 的频率分量）来模拟灾难性运营损失事件的发生行为。这背后的动机是，巨灾操作风险可能是两级风险产生机制的表现：第一级，自然和人为灾难（简称操作风暴）发生并触发，第二级，集群灾难性的运营损失事件。基于 334 个极端运营损失事件的历史系列的图形分析支持事件发生的聚类结构。