MSc Financial Risk Management

Programme title:
MSc Financial Risk Management
Final award (BSc, MA etc):
(where stopping off points exist they should be
detailed here and defined later in the document)
UCAS code:
(where applicable)
Cohort(s) to which this programme
specification is applicable:
From session 2012/13 intake onwards
(e.g. from 2015 intake onwards)
Awarding institution/body:
University College London
Teaching institution:
University College London
Engineering Sciences
Parent Department:
Computer Science
(the department responsible for the administration of
the programme)
Departmental web page address:
(if applicable)
Method of study:
Criteria for admission to the
An appropriate first degree, at least 2.1 or equivalent
Length of the programme:
One year full-time
(please note any periods spent away from UCL, such
as study abroad or placements in industry)
Level on Framework for Higher
Education Qualifications (FHEQ)
(see Guidance notes)
Relevant subject benchmark statement
(see Guidance notes)
Brief outline of the structure of the
(see guidance notes)
Board of Examiners:
Level 7 (taught master’s degrees)
Master’s degrees in computing 2011
The programme consists of 8 taught modules and a thesis, 4 taught
modules are core and 4 are optional:
Name of Board of Examiners:
Joint Financial Mathematics and Financial Risk Management Board
of Examiners
Professional body accreditation
(if applicable):
None (the programme will be put forward
for BCS/ IET accreditation as appropriate,
at the next opportunity)
Date of next scheduled
accreditation visit: 2014
academic session
The programme aims to create financial risk professionals who are trained simultaneously in mathematics, statistics
and computation and draws on the combined resources of the UCL departments of Computer Science,
Mathematics and Statistical Science.
Risk professionals need:
Mathematical skills to analyse the modern financial models.
Statistical skills to properly characterise real-world data.
Computer science skills to run and analyse complex computer models.
The programme provides opportunities for students to develop and demonstrate knowledge and understanding,
qualities, skills and other attributes in the following areas:
A: Knowledge and understanding
Knowledge and understanding of:
Applications of mathematics, statistics
and computation as applied to problems
in finance.
Teaching/learning methods and strategies:
Provision of lectures, practical classes and problem
solving exercises.
Written papers, coursework and oral examination.
B: Skills and other attributes
Intellectual (thinking) skills:
Ability to solve numerical problems
encountered when applying mathematics,
statistics and computing to finance and
financial risk.
Teaching/learning methods and strategies:
Throughout lectures numerical analysis is used. Typical
problems encountered during professional practice are
discussed. Problem sheets are provided and discussed.
Examination questions are usually a mixture of bookwork and
unseen problem solving calculations.
C: Skills and other attributes
Practical skills (able to):
Teaching/learning methods and strategies:
To to program a computer to solve problems
in financial modelling.
Practical classes will be held to teach these experimental skills.
These skills will be further refined during the research project.
The research project is assessed by a research report and, if
needed, by oral examination. Module work will be assessed
using a mixture of examination and take-home work.
D: Skills and other attributes
Transferable skills (able to):
Teaching/learning methods and strategies:
Able to use software packages to analyse and
present results, to prepare a research
presentation and to prepare a research
Tutorial-type teaching is used on small group basis as needed.
Practice sessions are given for presentation skills.
As part of the project assessment the students have a
presentation to give and a research report to prepare. Both
elements are assessed.
The following reference points were used in designing the programme:
 the Framework for Higher Education Qualifications:
 the relevant Subject Benchmark Statements ( );
 the programme specifications for UCL degree programmes in relevant subjects (where applicable);
 UCL teaching and learning policies;
 staff research.
Please note: This specification provides a concise summary of the main features of the programme and the
learning outcomes that a typical student might reasonably be expected to achieve and demonstrate if he/she takes
full advantage of the learning opportunities that are provided. More detailed information on the learning outcomes,
content and teaching, learning and assessment methods of each course unit/module can be found in the
departmental course handbook. The accuracy of the information contained in this document is reviewed annually
by UCL and may be checked by the Quality Assurance Agency.
Programme Organiser(s)
Dr Tomaso Aste
Date of Production:
1 March 2011
Date of Review:
January 2015
Date approved by Head of
January 2015
Date approved by Chair of
Departmental Teaching
Date approved by Faculty
Teaching Committee
January 2015
January 2015
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