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401-3936-DRL 1 Credits DR D-MATH

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Data Analytics for Non-Life Insurance Pricing

Lecturers: Prof. Dr. Mario Valentin Wüthrich, Dr. Christoph Markus Buser

Examiners: Prof. Dr. Mario Valentin Wüthrich

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 ( ) with the course number. The email should have the subject „Graduate course registration (ETH)“.

VVZ CR n/a

Last Updated: 2026-02-05 16:22:19

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.

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

Resources

Lecture Notes

The lecture notes are available from:M.V. Wüthrich, C. Buser. Data Analytics for Non-Life Insurance Pricinghttp://ssrn.com/abstract=2870308

Literature

M.V. Wüthrich, M. Merz. Statistical Foundations of Actuarial Learning and its Applications http://ssrn.com/abstract=3822407

General Information

Language: English
Levels: DR
Frequency: Yearly recurring

Examination

Type: session examination
Mode: oral 30 minutes

Registration & Places

Priority: Registration for the course unit is only possible for the primary target group

Course Components

Type	Title	Time & Place	Hours
lecture	Data Analytics for Non-Life Insurance Pricing	Tue 16:15-18:00 (HG E 1.2)	2 h weekly

Offered In

Doctorate Mathematics (More Information at: )
- Subject Specialisation (The list of courses (together with the allocated credit points) eligible for doctoral students is published each semester in the newsletter of the ZGSM.)
  - Graduate School (Official website of the Zurich Graduate School in Mathematics: )