Journal of Operational Risk
Editor-in-chief: Marcelo Cruz
Volume 9, Number 1 (March 2014)
Welcome to the first issue of the ninth volume of The Journal of Operational Risk.
Regulators in the United States are asking banks to significantly increase their operational risk capital from current levels. This change is mostly motivated by the increase in so-called systemic operational risk events that might require significant commitment from banks to settle. Banks are only now resolving the mortgage litigation cases that arose from the 2008 crisis, and they are being investigated for their role in the manipulation in the LIBOR, foreign exchange and commodities markets. There is the potential for several billions more dollars to be spent settling these investigations. A paper in the Forum section of this issue investigates one of these events and the role of brokers in them. In the United Kingdom and Europe these "systemic operational risk events" are mostly called "conduct risk", as banks and insurers failed to perform their functions according to their own policies and procedures and are at risk of having to pay fines and face litigation for these failures.
I would like to ask potential authors to continue to submit to The Journal of Operational Risk regarding the state of operational risk research, and I would again like to emphasize that the journal is not solely for academic authors. Please note that we do publish papers that do not have a quantitative focus, with one example of this in the current issue. We at The Journal of Operational Risk would be happy to receive more submissions containing practical, current views of relevant matters as well as papers focusing on the technical aspects of operational risk.
There are three very interesting research papers in this issue. One discusses the role of diversification in operational risk capital, another considers the universe of loss data consortiums and suggests an optimal design for these entities, and a third offers us a stochastic model for handling operational risk in trading systems.
In the issue's first paper, "The limit of diversification: a lower bound on firm-wide operational risk capital", Emre Balta and Matthias Degen tackle the important issue of the quantification of diversification benefit, which plays a critical role in quantitative risk models and is of particular interest to financial regulators as diversification can reduce regulatory capital significantly. The uncertainty surrounding the modeling of dependencies makes quantitative analysis of diversification a challenging task. Using well-known mathematical theory, the authors develop a methodology for establishing a lower bound on risk concentration in the presence of dependent underlying risk factors, and hence for deriving a theoretical lower bound for firm-wide advanced measurement approach (AMA) capital. This paper provides bank supervisors with a potential tool for benchmarking and ranking the risk concentrations that banks report for their operational risk AMA capital. The authors show that aggregation methods are overly reliant on modeling choices and assumptions, and that some banks have a very aggressive reduction in firm-wide operational risk capital because of that.
In our second paper, "On the optimal design of operational risk data consortiums", Hubert Janos Kiss and Daniel Homolya discuss the organization and structure of operational risk loss data consortiums. Although existing data consortiums seem to work appropriately, the authors examined whether participating banks report their losses properly, since in several countries where new data consortiums are planned, there are fears that banks may choose to hide information, fearing disclosure and loss of anonymity. The authors show that loss misreporting might not be properly detected and then assess two types of possible sanctions for misreporting losses. When punishment is nonmonetary (eg, exclusion from the consortium for a given number of periods), even the harshest punishment cannot bring about proper reporting. Nonetheless, a numerical example suggests that by designing the data consortium adequately, the cause of proper reporting can be advanced, without overly compromising anonymity. When a monetary fine is imposed on misreporting banks, a sufficiently severe punishment results in proper reporting.
The third paper in the issue, "Assimilating operational risks in common trading systems" by Dror Parnes, presents a stochastic model that incorporates operational hazards into ordinary trading systems. Parnes develops a simple compartmental theory that utilizes a predetermined lower threshold in the total assets' value to differentiate between operative and inoperative cycles in portfolio management. He then distinguishes between two general failure modes, which may evolve due to either exogenous (market) or endogenous (operational) factors. He derives the pertinent time-related likelihoods of being in each state of nature, the accumulated probabilities of remaining operative or breaching the predetermined lower boundary, and the expected time to portfolio termination, and hence the mean time to failure. He further simulates these derivations to demonstrate how the model works.
In this section of the journal we publish papers that report day-to-day experiences in operational risk management. We have one paper in the Forum section of this issue.
In "LIBOR manipulation: operational risks resulting from brokers' misbehavior", Patrick McConnell discusses the role of brokers in the financial markets and the many operational risk events that have recently been caused by these players, with particular focus on the LIBOR manipulation case. Brokers perform a key role in many financial markets. They introduce buyers to sellers, perform a useful role in price discovery and provide a source of market information and commentary to market participants and the general public. In well-organized markets, brokers are trusted to be honest and to undertake these tasks in the best interests of their clients (buyers or sellers). But there is an inherent and well-understood conflict of interest in the role of the broker. Brokers are rewarded according to their success in bringing buyers and sellers together, but their source of income is based solely on the completion of a successful transaction. There is therefore a constant temptation for a broker to trade the best interests of their client against completing a deal that would help improve the broker's bottom line. McConnell examines the key role of brokers in the LIBOR manipulation scandal and, using reports from published inquiries, identifies the illicit activities of some brokers in assisting banks to manipulate the LIBOR benchmark. The perpetrators of these "white collar" crimes were traders and managers in some of the largest banks in the world, but the manipulation would not have been as widespread or as successful without the willing participation and illegal actions of brokers in several firms. The paper argues that the actions of the traders in various banks around the world in the LIBOR manipulation scandal are examples of systemic operational risk, and in particular people risk. The paper makes specific suggestions to bank boards and regulators about how such misconduct could be managed in the future.
Papers in this issue
The limit of diversification: a lower bound on firm-wide operational risk capital
On the optimal design of operational risk data consortiums
LIBOR manipulation: operational risks resulting from brokers’ misbehavior
Assimilating operational risks in common trading systems