Ground-breaking study of the Risk Unit's applicability in operational risk quantification

We are thrilled that our latest research paper, produced in collaboration with the Durham and Leicester University Business Schools, is now available in the Journal of Risk Management in Financial Institutions (JRMFI Vol. 14 No. 2).

The paper reports on ground-breaking tests of the Risk Accounting method that involved the restatement into RUs of publicly available GAAP accounting data relative to fifteen of the largest banks in the USA.

The headline finding is that exposure to OpRisk of these banks, expressed in RUs, may have increased by as much as 60% during the eight years leading up to the financial crisis of 2007-’08.

We believe this is the first time that pre-crisis growth in OpRisk exposure has been made observable with such clarity through explicit quantification.

(You can find the paper embedded below – the window can be made full screen for easy reading or the paper can be downloaded using the buttons on the low-right corner)

A test of the inherent predictiveness of the RU, a new metric to express all forms of operational risk in banks

Research paper by Peter Hughes and Mahmoud Marzouk

In 2016 Allan D. Grody and Peter J. Hughes proposed a method and system termed ‘Risk Accounting’, an integrated financial and risk accounting framework. Risk Accounting incorporates a novel operational risk exposure quantification technique based on the Risk Unit (RU), a new common additive metric designed to express all forms of operational risk in banks.

In this paper, we report on initial tests of the inherent predictiveness of the RU. The test focused on the period leading up to the global financial crisis of 2007-8 and involved the restatement into RUs of publicly available accounting data in the United States relative to a subset of large US banks.


In this study...

We contend that the RU’s inherent predictiveness could be concluded if it is demonstrated that an accelerated increase in trended operational risk RUs and subsequent material unexpected losses are positively correlated. We further describe how a monetary value can be stochastically derived and assigned to the RU over time. The inclusion of valued RUs in accounting systems will potentially enable the systematic adjustment of financial performance and condition relative to accepted nonfinancial risks to complement the accounting treatment already applied to financial (credit and market) risks.

The resulting harmonisation of the accounting treatment applied to both financial and non-financial risks based on stochastic modeling will enable risk-adjusted economic profit to be adopted as the primary business performance metric and economic capital as the primary method of determining both operating and regulatory capital requirements. The real-time or near-real-time production of portfolio views of operational risk exposures based on the RU adds analytical rigor to their management and causes risk mitigation to become both a risk reduction and a profit optimisation initiative. The more effective management, oversight and governance of exposures to operational risks is the anticipated outcome.