401-3936-00L  Data Analytics for Non-Life Insurance Pricing

SemesterSpring Semester 2021
LecturersC. M. Buser, M. V. Wüthrich
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
401-3936-00 VData Analytics for Non-Life Insurance Pricing2 hrs
Tue16:15-18:00HG E 1.2 »
C. M. Buser, M. V. Wüthrich

Catalogue data

AbstractWe 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.
ObjectiveThe student is familiar with classical actuarial pricing methods as well as with modern machine learning methods for insurance pricing and prediction.
ContentWe 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 notesThe lecture notes are available from:
Link
Prerequisites / NoticeThis 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 credits4 credits
ExaminersM. V. Wüthrich, C. M. Buser
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationoral 30 minutes
Additional information on mode of examinationLanguage 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

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

PriorityRegistration for the course unit is only possible for the primary target group
Primary target groupData Science MSc (261000)
Mathematics BSc (404000)
Quantitative Finance MSc (435000)
Mathematics MSc (437000)
Applied Mathematics MSc (437100)
Doctorate Mathematics (439002)
Actuary SAV (448100)

Offered in

ProgrammeSectionType
Data Science MasterInterdisciplinary ElectivesWInformation
Doctoral Department of MathematicsGraduate SchoolWInformation
Mathematics (General Courses)Actuary SAA Education at ETH ZurichWInformation
Mathematics BachelorSelection: Financial and Insurance MathematicsWInformation
Mathematics MasterSelection: Financial and Insurance MathematicsWInformation
Quantitative Finance MasterMathematical Methods for FinanceWInformation