The measurement of operational risk has surely been one of the biggest challenges for
banks worldwide. Most banks worldwide have opted for a value-at-risk (VaR) approach,
based on the success achieved with market risk, to measure and quantify operational risk.
The problem banks have is that they do not always find it difficult to calculate this VaR
figure, as there are numerous mathematical and statistical methods and models that can
calculate VaR, but they struggle to understand and interpret the values that are produced
by VaR models and methods. Senior management and normal staff do not always
understand how these VaR values will impact their decision-making and they do not
always know how to incorporate these values in their day-to-day management of the
bank.
This study therefore aims to explain and discuss the calculation of VaR for operational
risk as well as the factors that influence this figure, and then also to discuss how this
figure is managed and the impact that it has on the management of a bank. The main
goal of this study is then to explain the management of VaR for operational risk in order
to understand how it can be incorporated in the overall management of a bank. The
methodology used includes a literature review, in-depth interviews and a case study on a
South African Retail Bank to determine and evaluate some of the most renowned
methods for calculating VaR for operational risk.
The first objective of this study is to define operational risk and all its elements in order
to distinguish it from all the other risks the banking industry faces and to better
understand the management thereof. It is the view of this study that it will be impossible
to manage and measure operational risk if it is not clearly defined, and it is therefore
important to have a clear and understandable definition of operational risk.
The second objective is to establish an operational risk management process that will
ensure a structured approach to the management of operational risk, by focusing on the
different phases of operational risk. The process discussed by this study is a combination
of some of the most frequent used processes by international banks, and is intended to
guide the reader in terms of the steps required for managing operational risk.
The third objective of this study is to discuss and explain the qualitative factors that play
a role in the management of operational risk, and to determine where these factors fit
into the operational risk process and the role they play in calculating the VaR for
operational risk. These qualitative factors include, amongst others, key risk indicators
(KRIs), risk and control self-assessments and the tracking of operational losses.
The fourth objective is to identify and evaluate the quantitative factors that play a role in
the management of operational risk, to distinguish these factors from the qualitative
factors, and also to determine where these factors fit into the operational risk
management process and the role they play in calculating VaR for operational risk. Most
of these quantitative factors are prescribed by the Base1 Committee by means of its New
Capital Accord, whereby this new framework aims to measure operational risk in order to
determine the amount of capital needed to safeguard a bank against operational risk.
The fifth objective is to discuss and explain the calculation of VaR for operational risk by
means of discussing all the elements of this calculation. This study mainly bases its
discussion on the loss distribution approach (LDA), where the frequency and severity of
operational loss events are convoluted by means of Monte Carlo simulations. This study
uses real data obtained from a South African Retail Bank to illustrate this calculation on a
practical level.
The sixth and final objective of this study is to explain how VaR for operational risk is
interpreted in order for management to deal with it and make proper management
decisions based on it. The above-mentioned discussion is predominantly based on the
two types of capital that are influenced by VaR for operational risk. / Thesis (Ph.D. (Risk Management))--North-West University, Potchefstroom Campus, 2007.
Identifer | oai:union.ndltd.org:NWUBOLOKA1/oai:dspace.nwu.ac.za:10394/1676 |
Date | January 2006 |
Creators | Esterhuysen, Ja'nel Tobias |
Publisher | North-West University |
Source Sets | North-West University |
Detected Language | English |
Type | Thesis |
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