This course provides an introduction to various aspects of modelling, dealing and managing risk across different industries, contexts and applications. Classes will alternate between risk professionals from industry and government and academics coming from different disciplines.
Learning objective
Students get familiar with the building blocks of risk modelling: uncertainty, vulnerability, resilience, decision-making under uncertainty. The course looks at different approaches to modelling and dealing as well as mitigating different kind of risks in different industries and get to understand the relation to the decision-making process in business and the value chain of a company. Cases range from enterprise risk management, natural catastrophes, climate risk, energy market risk, risk engineering, financial risks, operational risk, cyber risk and more. An additional emphasis will be on the data-driven approach to smart algorithms applied to risk modelling and management. After taking this course, students should be able to demonstrate that they can identify and formulate a risk analysis problem with quantitative methods in a particular field.
Content
The course covers the following areas: 1. Fundamentals of Risk Modelling: Probability, Uncertainty, Vulnerability, Decision-Making under Uncertainty 2. Fundamentals of Risk Management and Enterprise Risk Management 3. Risk Modelling and Management across Different areas with invited Speakers The list of Speakers can be found here: Link
Lecture notes
Lecture notes and slides will be provided via moodle
Performance assessment
Performance assessment information (valid until the course unit is held again)