Welcome to the first issue of Volume 12 of The Journal of Operational Risk.
Our industry continues to live under the shadow of the Basel Committee on Banking Supervision’s final paper on the standardized measurement approach (SMA). The consultative paper on this subject was issued in March 2016, and the committee received industry comments by June 2016. It is very unusual for the committee to take so long to finalize a paper, so this delay certainly signals dissent among the
international regulators on the key points, or even maybe the main idea, of the paper. The industry has been mostly negative about the idea of standardizing and simplifying the measurement of operational risk, and in the last few issues of this journal, our authors have not been shy about offering up papers that show the methodological flaws of the approach. There is one more paper in the current issue that addresses this subject. Off-the-record conversations with participants in the Basel Committee on Banking Supervision discussions suggest that many changes to the consultative paper will take place. We will have to wait and see.
In the meantime I invite authors to continue to submit their thoughts and views on this controversial subject. The Journal of Operational Risk, as the leading publication in this area, aims to be at the forefront of these discussions, and we welcome papers that can shed light on the topic.
In this issue we have two research papers and two forum papers. In both research papers the authors use large loss databases to prove their theories. These papers come with very interesting macro-conclusions – conclusions that regulators, in particular may, wish to take a closer look at. As regards our forum papers, we offer one criticizing SMA and another interesting paper analyzing the roles of the three lines of defence in governance.
In the issue’s first paper, “A nonlinear analysis of operational risk events in Australian banks”,Yifei Li, Neil Allan and John Evans propose a methodology to analyze operational risk events in banks. Their objective is to assess the key characteristics of such risk events and understand the common elements of the causes of the operational risk losses they generate. The authors use a database of operational risk losses in Australian banks over the period 2010–14. Their analysis identifies that there are a small number of key factors common to many operational risk events, and that these “level 1” factors are stable across time, which implies that operational risk losses can arguably be controlled by managing these factors closely. The paper adds value to existing analysis by creating a methodology to identify these key factors in operational risk events.
“Hidden Markov regimes in operational loss data: application to the recent financial crisis”, the second paper in this issue, finds Georges Dionne and Samir Saissi Hassani proposing an interesting method for considering business cycles in the computation of capital for operational risk. The authors examine whether the operational loss data of US banks contains a hidden Markov regime-switching feature between 2001 and 2010, assuming an asymmetric distribution of monthly losses. A high-level regime is
marked by very high loss values during the recent financial crisis, confirming temporal heterogeneity in the data. If this heterogeneity is not considered in risk management models, capital estimations will be biased (ie, banks will hold too much capital during periods of low stress and not enough capital during periods of high stress). Additional capital reached 30% during the period of analysis when regimes were not considered. Good reading for regulators worldwide.
In this issue’s first forum paper, “Operational risk and the three lines of defence in UK financial institutions: is three really the magic number?”, Kumbirai Mabwe, Patrick John Ring and RobertWebb note that interest in financial services firms’ development and implementation of robust systems and structures to manage operational risk has been growing. The authors add that financial institutions are struggling with the qualitative side of operational risk management (ORM). This is particularly the case for financial institutions’ operational risk governance, where the three lines of defence model has become standard. At the same time, corporate scandals since the financial crisis continue to indicate deficiencies in operational risk governance. The paper examines the three lines of defence model in the context of ORM in UK financial institutions, focusing on the roles and responsibilities of the various players within these institutions and then analyzing the effectiveness of the traditional model. The authors find that a lack of common understanding of the lines of defence in financial institutions exists, and this leads to a duplication of roles and gaps in coverage. This is concerning for the industry, for the economy and for regulators.
Our second forum paper, “Standardized measurement approach: is comparability attainable?”, sees Patrick McConnell disputing claims that the SMA will promote “comparability” of estimated operational risk capital across banks. In order to achieve comparability, the collection of operational risk data would have to be standardized across the industry. Through analysis of large operational risk losses, the author claims that such losses are nonstationary and, therefore, cannot be compared directly in terms of estimating operational risk capital.
This paper proposes a methodology applied to complex systems to analyze operational risk events in Australian banks.
The authors propose a method to consider business cycles in the computation of capital for operational risk.
Operational risk and the three lines of defence in UK financial institutions: is three really the magic number?
This paper examines the three lines of defence in the context of ORM in UK financial institutions.
This paper considers the claim of improved comparability of SMA outcomes by considering the ability to compare “internal loss experience” between banks.