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A checklist-based weighted fuzzy severity approach for calculating operational risk exposure on foreign exchange trades under the Basel Ⅱ regime

机译:基于清单的加权模糊严重度方法,用于计算巴塞尔Ⅱ制度下外汇交易的操作风险敞口

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摘要

It is well-known that any risk management activity is a cost to the organization. However, optimized risk management practices satisfy regulatory capital requirements and gain the confidence of investors who take calculated risks. A bank's risk management division will generate a profit if it can develop methodologies to decrease the nonworking regulatory capital. This may be achieved only when the risks are measured using data from internal and external sources in conjunction with scenario analysis. One such method of measuring operational risk (OR) is the advanced measurement approach. This involves quantifying ORs across the various nodes within a bank following the loss distribution approach, in which the frequency and severity distributions of the loss-generating OR events are estimated from the data sources. These distributions are then used to generate the scenarios for frequency and its associated severity for estimating the OR capital. In our approach, the various levels of loss severity are mapped to a percentage of total trade exposure, and the occurrence frequency of an OR event is assumed to follow a binomial distribution.
机译:众所周知,任何风险管理活动都是组织的成本。但是,优化的风险管理实践可以满足监管资本要求,并获得承担经过计算的风险的投资者的信心。如果银行的风险管理部门能够开发出减少非正常监管资本的方法,则将产生利润。仅当使用来自内部和外部来源的数据并结合情景分析来衡量风险时,才能实现这一目标。一种测量操作风险(OR)的方法是高级测量方法。这涉及按照损失分配方法对银行内各个节点之间的OR进行量化,其中从数据源估算产生损失的OR事件的频率和严重性分布。这些分布然后用于生成频率及其相关严重性的方案,以估计OR资本。在我们的方法中,各种程度的损失严重程度被映射到总交易风险的百分比,并且假定OR事件的发生频率遵循二项式分布。

著录项

  • 来源
    《The Journal of Operational Risk》 |2014年第4期|105-124|共20页
  • 作者单位

    Institute for Development and Research in Banking Technologies, Castle Hills, Masab Tank, Hyderabad 500 057, India and Foundation for Scientific Research and Technological Innovation, H No. 13-405, Vadrevu Nilayam, Hyderabad 500 035 (AP), India;

    HCL Technologies Ltd, Electronic City, Hosur Road, Bangalore 560 100, India;

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