A new dimension to Risk Assessment
(2014) MASM01 20141Mathematical Statistics
- Abstract (Swedish)
- Traditional risk assessment frameworks have been focused primarily on the
factors of likelihood and impact, utilizing either a numerical (e.g. 1 to 5) or
qualitative (e.g.low,medium, high) rating scale, resulting in the traditional
two dimensional framework. The challenge of this model is that the focus is
too narrow to eectively assess constantly changing risk environments and
fails to dierentiate between events that could take eect tomorrow and those
which may arise over the business planning horizon (three to ve years)
or over an even longer time. Recently a third dimension has been added
to the discussion of risk: velocity. However, this new concept has been
implemented in only a few companies and is treated more as a... (More) - Traditional risk assessment frameworks have been focused primarily on the
factors of likelihood and impact, utilizing either a numerical (e.g. 1 to 5) or
qualitative (e.g.low,medium, high) rating scale, resulting in the traditional
two dimensional framework. The challenge of this model is that the focus is
too narrow to eectively assess constantly changing risk environments and
fails to dierentiate between events that could take eect tomorrow and those
which may arise over the business planning horizon (three to ve years)
or over an even longer time. Recently a third dimension has been added
to the discussion of risk: velocity. However, this new concept has been
implemented in only a few companies and is treated more as a complement
to the traditional approach rather than as an integrated part of the risk
assessment.
The aim of this thesis is to develop a new model combining all these three
factors (likelihood, impact and velocity) into a single risk velocity assessment
and, hence, give accuracy and relevance to risk assessments. Therefore it is
crucial that a company has an understanding of how the use of risk velocity
can aect the risk assessment and enable risk management to focus on the
most relevant and immediate risks.
In this study we implement this risk assessment by using statistical tech-
niques. Based on the idea of the loss distribution approach (LDA), we will
estimate two probability distribution functions for each risk type; one on sin-
gle event impact and the other on event frequency for the next three years.
These distributions will be estimated from values obtained following a tra-
ditional risk assessment process - capturing risk velocity and retaining as
much information as possible from the process to assist in calibrating the
distributions. Based on the two estimated distributions, we then compute
the probability distribution function of the cumulative operational loss over
dierent time horizons and use this to develop a single velocity adjusted risk
metric which can be used to prioritize risks.
We then show that a risk assessment which consider risk velocity can
provide more valuable information and make the risk assessment process a
more precise and useful tool. This will enable management to understand
which risks require more attention and how dierent risk can aect business
plans over dierent time horizons. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/4330718
- author
- Ruiz Chaparro, Marta
- supervisor
- organization
- course
- MASM01 20141
- year
- 2014
- type
- H2 - Master's Degree (Two Years)
- subject
- language
- English
- id
- 4330718
- date added to LUP
- 2014-02-24 15:07:41
- date last changed
- 2014-02-24 15:07:41
@misc{4330718,
abstract = {{Traditional risk assessment frameworks have been focused primarily on the
factors of likelihood and impact, utilizing either a numerical (e.g. 1 to 5) or
qualitative (e.g.low,medium, high) rating scale, resulting in the traditional
two dimensional framework. The challenge of this model is that the focus is
too narrow to eectively assess constantly changing risk environments and
fails to dierentiate between events that could take eect tomorrow and those
which may arise over the business planning horizon (three to ve years)
or over an even longer time. Recently a third dimension has been added
to the discussion of risk: velocity. However, this new concept has been
implemented in only a few companies and is treated more as a complement
to the traditional approach rather than as an integrated part of the risk
assessment.
The aim of this thesis is to develop a new model combining all these three
factors (likelihood, impact and velocity) into a single risk velocity assessment
and, hence, give accuracy and relevance to risk assessments. Therefore it is
crucial that a company has an understanding of how the use of risk velocity
can aect the risk assessment and enable risk management to focus on the
most relevant and immediate risks.
In this study we implement this risk assessment by using statistical tech-
niques. Based on the idea of the loss distribution approach (LDA), we will
estimate two probability distribution functions for each risk type; one on sin-
gle event impact and the other on event frequency for the next three years.
These distributions will be estimated from values obtained following a tra-
ditional risk assessment process - capturing risk velocity and retaining as
much information as possible from the process to assist in calibrating the
distributions. Based on the two estimated distributions, we then compute
the probability distribution function of the cumulative operational loss over
dierent time horizons and use this to develop a single velocity adjusted risk
metric which can be used to prioritize risks.
We then show that a risk assessment which consider risk velocity can
provide more valuable information and make the risk assessment process a
more precise and useful tool. This will enable management to understand
which risks require more attention and how dierent risk can aect business
plans over dierent time horizons.}},
author = {{Ruiz Chaparro, Marta}},
language = {{eng}},
note = {{Student Paper}},
title = {{A new dimension to Risk Assessment}},
year = {{2014}},
}