401-3936-00L Data Analytics for Non-Life Insurance Pricing
Semester | Spring Semester 2018 |
Lecturers | C. M. Buser, M. V. Wüthrich |
Periodicity | yearly recurring course |
Language of instruction | English |
Courses
Number | Title | Hours | Lecturers | |||||||
---|---|---|---|---|---|---|---|---|---|---|
401-3936-00 V | Data Analytics for Non-Life Insurance Pricing On 20 February 2018 the course will start in ML D 28. | 2 hrs |
| C. M. Buser, M. V. Wüthrich |
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, gradient boosting machines and support vector machines. Moreover, we present unsupervised learning methods applied to telematics car driving data. |
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) - credibility theory - classification and regression trees (CARTs) - bagging, random forests and boosting - support vector machines (SVMs) - unsupervised learning methods - telematics car driving data |
Lecture notes | The lecture notes are available from: Link |
Prerequisites / Notice | This course will be held in English and counts towards the diploma of "Aktuar SAV". For the latter, see details under Link 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 | 4 credits |
Examiners | M. V. Wüthrich, C. M. Buser |
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 | written 120 minutes |
Written aids | None / Keine |
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
There are no additional restrictions for the registration. |