401-3936-DRL Data Analytics for Non-Life Insurance Pricing
| Semester | Spring Semester 2023 |
| Lecturers | M. V. Wüthrich, C. M. Buser |
| Periodicity | yearly recurring course |
| Language of instruction | English |
| Comment | Only for ETH D-MATH doctoral students and for doctoral students from the Institute of Mathematics at UZH. The latter need to send an email to Jessica Bolsinger (info@zgsm.ch) with the course number. The email should have the subject „Graduate course registration (ETH)“. |
Courses
| Number | Title | Hours | Lecturers | ||||
|---|---|---|---|---|---|---|---|
| 401-3936-00 V | Data Analytics for Non-Life Insurance Pricing | 2 hrs |
| M. V. Wüthrich, C. M. Buser |
Catalogue data
| Abstract | We study statistical methods in supervised learning for non-life insurance pricing such as generalized linear models, generalized additive models, Bayesian models, neural networks, classification and regression trees, random forests and gradient boosting machines. |
| Learning objective | The student is familiar with classical actuarial pricing methods as well as with modern machine learning methods for insurance pricing and prediction. |
| Content | We present the following chapters: - generalized linear models (GLMs) - generalized additive models (GAMs) - neural networks - credibility theory - classification and regression trees (CARTs) - bagging, random forests and boosting |
| Lecture notes | The lecture notes are available from: M.V. Wüthrich, C. Buser. Data Analytics for Non-Life Insurance Pricing http://ssrn.com/abstract=2870308 |
| Literature | M.V. Wüthrich, M. Merz. Statistical Foundations of Actuarial Learning and its Applications http://ssrn.com/abstract=3822407 |
| Prerequisites / Notice | This course will be held in English and counts towards the diploma of "Aktuar SAV". For the latter, see details under www.actuaries.ch Good knowledge in probability theory, stochastic processes and statistics is assumed. |
Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| ECTS credits | 1 credit |
| Examiners | M. V. Wüthrich |
| 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 30 minutes |
| This information can be updated until the beginning of the semester; information on the examination timetable is binding. | |
Learning materials
| No public learning materials available. | |
| Only public learning materials are listed. |
Groups
| No information on groups available. |
Restrictions
| Priority | Registration for the course unit is only possible for the primary target group |
| Primary target group | Doctorate Mathematics (439002)
Doctorate Computational Science and Engineering (439102) |
Offered in
| Programme | Section | Type | |
|---|---|---|---|
| Doctorate Mathematics | Graduate School | W |  |