标题： 一种量化模型风险的新方法 显示英文标题

标题： A Novel Approach to Quantification of Model Risk for Practitioners

摘要： 模型在工业中的使用范围和复杂性继续不断扩大。全球监管要求金融机构以与其他类型风险相同的严重程度来管理和应对模型风险，这除了定义模型风险为基于错误和误用模型输出和报告的决策可能带来的负面后果外，还强调了这一点。模型风险量化不仅对于满足这些要求至关重要，也是机构基本内部运营的必要条件。然而，这是一个复杂的任务，因为任何全面的量化方法至少应考虑用于构建模型的数据、其数学基础、IT基础设施、整体性能以及（最重要的是）使用情况。此外，当前模型的数量和不同的数学建模技术令人应接不暇。我们的建议是将模型风险量化定义为对属于巴拿赫空间中某些适当函数范数的计算，该巴拿赫空间定义在一个带有费舍尔-劳度量的加权黎曼流形上。本文的目的是双重的：介绍一个足够通用且坚实的数学框架，以涵盖上述要点，并说明从业者如何识别相关的抽象概念并加以应用。 显示英文摘要

摘要： Models continue to increase their already broad use across industry as well as their sophistication. Worldwide regulation oblige financial institutions to manage and address model risk with the same severity as any other type of risk, which besides defines model risk as the potential for adverse consequences from decisions based on incorrect and misused model outputs and reports. Model risk quantification is essential not only in meeting these requirements but for institution's basic internal operative. It is however a complex task as any comprehensive quantification methodology should at least consider the data used for building the model, its mathematical foundations, the IT infrastructure, overall performance and (most importantly) usage. Besides, the current amount of models and different mathematical modelling techniques is overwhelming. Our proposal is to define quantification of model risk as a calculation of the norm of some appropriate function that belongs to a Banach space, defined over a weighted Riemannian manifold endowed with the Fisher--Rao metric. The aim of the present contribution is twofold: Introduce a sufficiently general and sound mathematical framework to cover the aforementioned points and illustrate how a practitioner may identify the relevant abstract concepts and put them to work.