Unit 7: An Introduction to the Concepts of Quantitative Risk Modelling

This unit provides an overview of various methods used in quantitative risk modelling, including probabilistic approaches such as Monte Carlo simulations and Bayes theorem-based methods, as well as multi-criteria decision analysis techniques like TOPSIS, AHP, and ANP.

Key Concepts Covered

  • Quantitative Risk Modelling (QRM): Understanding the concept and its significance.
  • Approaches to QRM: Review of Monte Carlo Simulations and Bayes theoretical models.
  • Principles and Antipatterns: Discussion of the principles and common pitfalls for each approach.

The seminar provided practical insights into applying quantitative risk modelling techniques in real-world scenarios. To the right is the reflective piece with the artefacts linked on this unit:

Reflection on Unit 7

In this unit, I gained insights into various quantitative risk modelling techniques, including Monte Carlo simulations and Bayes theorem-based methods. The lecturecast provided a comprehensive overview of these methods and their practical applications, which was instrumental in preparing for the assignments. Furthermore, the reading from Fundamentals of Risk Management: Understanding, Evaluating and Implementing Effective Risk Management by Olson & Desheng (2020) was particularly enlightening. It deepened my understanding of Monte Carlo simulations, which I plan to apply in the Unit 11 assignment. This knowledge has been essential for developing robust risk models and making informed decisions based on probabilistic approaches.