关系数据:当前金融基础设施缺失的一环

I. Leonova, N. Jenkinson
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引用次数: 1

摘要

提高对金融实体之间复杂关系的理解对于风险管理者和负责多种政策目标的金融当局至关重要。企业内部和企业间都缺乏高质量的信息来支持对财务网络的分析。简而言之,当前关系数据的质量和数量不足以实现最终目标。为了讨论的目的,我们使用一个非常通用的术语关系的定义,有点类似于用来描述人类关系的定义。就像在人际关系的例子中,我们不会说只有婚姻和血缘关系才是你的亲戚,也会说借一本书、爱、恨和合租一套公寓才是你的亲戚。在财务环境中,这种关系可能取决于会计规则,例如,国际财务报告准则或美国公认会计准则,以及风险管理、市场完整性、了解客户、网络分析和统计合并等领域的监管要求。金融业和监管机构花了无数时间争论所有权的定义。问题在于问题本身。我们建议,作为任何关系数据系统的一部分,最好的方法是把这个问题放在一边,避免陷入概念和实践的泥潭。相反,我们建议收集和存储关于公司之间实际法律和经济关系的不那么主观的细粒度数据,这提供了一个灵活的框架,任何用户都可以从中回答他或她认为在给定时间合适的公司关系问题。令人鼓舞的是,技术解决方案可以在单个解决方案中容纳这种需求的多样性。本文概述了阻碍高质量关系数据发展的实际挑战,以及如何克服这些挑战。
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Relationship Data: The Missing Link of the Current Financial Infrastructure
Improving understanding of the complex relationships among financial entities is critically important for risk managers and for financial authorities charged with multiple policy objectives. High quality information is lacking at both the intra- and inter-enterprise levels and to support analysis of the financial network. Put simply, the current quality and quantity of relationship data is not sufficient to deliver on the ultimate objectives. For the purpose of this discussion we use a very generic definition of a term relationship somewhat similar to the definition used to describe human relationships. And like in the human relationships case we will not claim that only marriage and blood connection makes your relatives, but also loaning a book, loving, hating and sharing a flat. In the financial context, the relationships may be determined by accounting rules set, for example, by IFRS or US GAAP, as well as regulatory requirements in areas of risk management, market integrity, know-your-client, network analysis and statistical consolidation. The financial industry and regulators have spent countless hours arguing and debating the definition of ownership. The problem lies in the question itself. We suggest that as part of any relationship data system the best approach is to put the question aside and avoid a conceptual and practical quagmire. Rather, we recommend collecting and storing less-subjective granular data on theactual legal and economic relationships between firms, which provides a flexibleframework from which any user can answer the question on corporate relationships he or she determines is appropriate at a given time. Encouragingly, technological solutions are available to accommodate this multiplicity of requirements in a single solution. The paper outlines where the practical challenges are that inhibit the development of high quality relationship data and how they can be overcome.
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