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A test of the feasibility of a common risk accounting metric for enterprise risks

Peter Hughes and Julian Williams
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Peter Hughes: Risk Accounting Standards Board, Durham University Business School, UK

Journal of Risk Management in Financial Institutions, 2018, vol. 11, issue 3, 267-283

Abstract: The risk accounting technique proposed by Grody and Hughes introduces a common enterprise risk measurement framework and a new risk metric — the risk unit (RU) — to express all forms of enterprise risk. The method’s creators contend that the application of an additive, common risk metric enables the consistent and comparable calculation and reporting of exposure to enterprise risks. The method’s alignment with accounting systems provides a single source of risk data derived from official accounting records and a common framework for the control and reporting of both financial and operational risk information. This paper describes the methodology formulated to test the feasibility of the proposed common risk metric, the RU. Fundamental to the approach is the restatement in RUs of publicly available US bank call report data provided by the Federal Reserve Bank of Chicago. Given the exceptionally large volume of data to be examined, non-parametric conditional density analysis will be applied to both call report (US Generally Accepted Accounting Principles (GAAP)) and RU data to conclude on the feasibility of providing complete, accurate, comparable and timely enterprise risk reporting in RUs using the risk accounting method. The existence of inherent predictive properties in RUs will be tested by examining trended data in RUs in the period leading up to and beyond the global financial crisis of 2007/08 and analysing the correlations between RUs and unexpected losses. For this purpose, amounts applied by the US government to purchase equity from banks under its Capital Purchase Program (CPP) as part of the Troubled Assets Relief Program (TARP) will be used as proxies for unexpected losses.

Keywords: risk accounting; enterprise risk; non-parametric conditional density analysis (search for similar items in EconPapers)
JEL-codes: E5 G2 (search for similar items in EconPapers)
Date: 2018
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