SHE Level 5
SCQF Credit Points 15.00
ECTS Credit Points 7.50
Module Code MMN324995
Module Leader Dawn Anderson
School Glasgow School for Business and Society
Subject Risk
  • B (January start)
  • A (September start)
  • C (May start)

Pre-Requisite Knowledge


Summary of Content

This module covers the theoretical and practical elements required in accurate risk analysis and modelling, based on current understandings and applications of modern risk analysis. The overall aim is to equip the student with highly sought-after practical risk analysis and modelling skills. This module provides students with the practical tools and knowledge to confidently assess, model and predict risk. The student will develop real-world applicable skills and utility from an organisational perspective; with real data examples, students can model and calculate financial risk concerns such as credit/bankruptcy risk which is an attractive skill to organisation. In addition, students are shown how to const ruct a non-financial risk model for assessing practical risk of any type of scenario, based on a qualitative assessment of risk.


-360-2582 1. Introduction to risk analysis and modelling. -360-2582 2. Using Excel and @Risk 3. Probability in risk analysis 4. Financial risk analysis (quantitative) 5. Credit (and Bankruptcy?) risk 6. Enterprise Risk 7. Qualitative risk modelling 8. Digital security/data security -360

Learning Outcomes

On successful completion of this module, the student should be able to:1. Confidently utilise risk software tools to quantify risk in an organisational context2. Successfully analyse scenarios to provide an appraisal on credit risk in a financial institution3. Critically analyse and develop a model a risk scenario using risk analysis and modelling software4. Collate and synthesise complex risk data output into an appropriate reporting format for decision makers

Teaching / Learning Strategy

The programme is focused on the development of both theoretical and practical business skills, and aims to engage students in analysis, research and discussion of contemporary, real life issues. The teaching and learning strategy aims to embed these attributes. All of the modules will be delivered on a campus-based and distance learning mode. The teaching strategy involves a mix of traditional lectures and labs to teach the key elements of the course. For those aspects requiring more complex mathematical theory and software usage a more in-depth assistance will be given both during lab times and through online learning content that will provide students with a narrated walkthrough using annotated videos. These can be hosted online or through the GCU Learn platform to further assist students through interactive multimedia and it is expected that this will be most beneficial to those distance learners who normally would not be able to participate on campus. Distance Learning delivery will be facilitated through interactive multimedia within the primary learning environment: GCU Learn. Software applications including Padlet, Collaborate and Camtasia will be used to formulate lessons and guided interactive tutorials, ensuring distance students can engage and participate fully despite being off-campus. In this manner, distance learners can communicate in a classroom environment; enjoying peer-to-peer collaboration and learning with each other as well as with the campus taught cohort. It is understood that most Risk Management students will not necessarily be prepared for mathematical modelling on this scale so each learning block will be built upon gradually to maintain the student experience and encourage those with no background in mathematics or statistics. Communication between students is facilitated through GCU Learn to encourage and foster a peer support network and collaborative learning experience between cohorts. Students are provided with formative and summative feedback via a variety of mechanisms. Feedback on coursework is provided within 3 working weeks of submission.

Indicative Reading

-2582 Indicative Reading Garlick, M. (2007) Estimating Risk: A Management Approach, Gower. Pidd, M. (2004) Computer Simulation in Management Science, Wiley. Manzo, J. (2004) Excel 2007 in Business (Comprehensive Version), Pearson, ISBN 0-13-99171-1 Project Risk Analysis and Management Guide (2nd edition) (2004) APM Publishing Limited Updated: Guerrero, H. (2011): Excel Data Analysis Modelling and Simulation https://link-springer-com.gcu.idm.oclc.org/content/pdf/10.1007%2F978-3-642-10835-8.pdf @Risk Guides Guide to Using RISKOptimizer Simulation Optimization for Microsoft Excel (Palisade) : https://www.palisade.com/downloads/manuals/EN/RISKOptimizer5_EN.pdf (Note: Palisade provide online video support for the use of risk tools) This module is practical and support material is provided to the students weekly as part of the lecture notes and study guidance. -360

Transferrable Skills

-2582 1. Creative problem solving with use of software to model solutions to risk problems 2. Gain skills in reporting of risk outcomes to management, preparing risk reports and understanding practical risk concepts such as risk registers and matrixes

Module Structure

Activity Total Hours
Lectures (FDL) 12.00
Independent Learning (FDL) 84.00
Practicals (FT) 16.00
Independent Learning (FT) 84.00
Seminars (FDL) 8.00
Assessment (FT) 30.00
Seminars (FT) 8.00
Practicals (FDL) 16.00
Assessment (FDL) 30.00
Lectures (FT) 12.00

Assessment Methods

Component Duration Weighting Threshold Description
Coursework Report n/a 100.00 50% Quantitative risk model development & 2,000 words analytical report