This course is a practical, hands-on introduction to various aspects of modelling, dealing with and managing risks across different industries, contexts and applications.
Our main goal is helping students understand what is required of the 21st century’s risk manager. To do so, the course provides a qualitative and quantitative introduction to the various risks that societies and businesses face and to their management. The course encourages students to think critically about models and mathematical representations of risks. Finally, it aims at conveying the current challenges of managing today’s risks given available technologies. After taking this course, students should be able to identify and formulate a risk analysis problem with quantitative methods in a particular field.
The course describes the building blocks of risk modelling: uncertainty, vulnerability, resilience, decision-making under uncertainty. It examines at different approaches to modelling and dealing with as well as mitigating different kind of risks in different industries.
The lectures emphasize the decision-making processes in various business and how risk-management relates to 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.
Moreover, the course highlights the data-driven approach to smart algorithms applied to risk modelling and management.
The panel of lecturers comprises risk professionals from various industries and government as well as academics from different disciplines.
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 past speakers can be found here: Link
The course materials are provided via the Moodle application.
Additional readings will be discussed during the lectures.
Voraussetzungen / Besonderes
The course is opened to students from all backgrounds. Some experience with quantitative disciplines such as probability and statistics, however, is useful.
Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)