401-3928-00L  Reinsurance Analytics

Courses

Catalogue data

Abstract	This course provides an introduction to reinsurance from an actuarial perspective. The objective is to understand the fundamentals of risk transfer through reinsurance and models for extreme events such as natural or man-made catastrophes. The lecture covers reinsurance contracts, Experience and Exposure pricing, natural catastrophe modelling, solvency regulation, and insurance linked securities
Learning objective	This course provides an introduction to reinsurance from an actuarial perspective. The objective is to understand the fundamentals of risk transfer through reinsurance and the mathematical approaches associated with low frequency high severity events such as natural or man-made catastrophes. Topics covered include: - Reinsurance Contracts and Markets: Different forms of reinsurance, their mathematical representation, history of reinsurance, and lines of business. - Experience Pricing: Modelling of low frequency high severity losses based on historical data, and analytical tools to describe and understand these models - Exposure Pricing: Loss modelling based on exposure or risk profile information, for both property and casualty risks - Natural Catastrophe Modelling: History, relevance, structure, and analytical tools used to model natural catastrophes in an insurance context - Solvency Regulation: Regulatory capital requirements in relation to risks, effects of reinsurance thereon, and differences between the Swiss Solvency Test and Solvency 2 - Insurance linked securities: Alternative risk transfer techniques such as catastrophe bonds
Content	This course provides an introduction to reinsurance from an actuarial perspective. The objective is to understand the fundamentals of risk transfer through reinsurance and the mathematical approaches associated with low frequency high severity events such as natural or man-made catastrophes. Topics covered include: - Reinsurance Contracts and Markets: Different forms of reinsurance, their mathematical representation, history of reinsurance, and lines of business. - Experience Pricing: Modelling of low frequency high severity losses based on historical data, and analytical tools to describe and understand these models - Exposure Pricing: Loss modelling based on exposure or risk profile information, for both property and casualty risks - Natural Catastrophe Modelling: History, relevance, structure, and analytical tools used to model natural catastrophes in an insurance context - Solvency Regulation: Regulatory capital requirements in relation to risks, effects of reinsurance thereon, and differences between the Swiss Solvency Test and Solvency 2 - Insurance linked securities: Alternative risk transfer techniques such as catastrophe bonds
Lecture notes	Slides and lecture notes will be made available. An excerpt of last year's lecture notes is available here: https://sites.google.com/site/philipparbenz/reinsuranceanalytics
Prerequisites / Notice	Basic knowledge in statistics, probability theory, and actuarial techniques
Competencies	Subject-specific Competencies Concepts and Theories assessed Techniques and Technologies assessed Method-specific Competencies Analytical Competencies assessed Decision-making assessed Media and Digital Technologies assessed Problem-solving assessed Project Management fostered Social Competencies Communication assessed Cooperation and Teamwork fostered Customer Orientation fostered Leadership and Responsibility fostered Self-presentation and Social Influence fostered Sensitivity to Diversity fostered Negotiation fostered Personal Competencies Adaptability and Flexibility assessed Creative Thinking fostered Critical Thinking fostered Integrity and Work Ethics fostered Self-awareness and Self-reflection fostered Self-direction and Self-management fostered

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits	4 credits
Examiners	P. Arbenz, P. Antal
Type	session examination
Language of examination	English
Repetition	The performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examination	oral 20 minutes
Additional information on mode of examination	Language of examination: English or German / Prüfungssprache: Deutsch oder Englisch
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

Groups

Restrictions

Offered in

Programme	Section	Type
Data Science Master	Interdisciplinary Electives	W
Mathematics (General Courses)	Actuary SAA Education at ETH Zurich	W
Mathematics Bachelor	Selection: Financial and Insurance Mathematics	W
Mathematics Master	Selection: Financial and Insurance Mathematics	W
Quantitative Finance Master	Mathematical Methods for Finance	W