Machine Learning in Risk and Insurance

ETH D-Math and FIM Nachdiploma Lectures

ETH Zurich: lectures take place on Wed mornings 10:15-noon from 27th Sept 2017 to 20-Dec 2017 (13 lectures)

Gratitude to ETH D-Math, RiskLab and Forschungsinstitut fuer Mathematik (FIM) for kindly inviting this lectures series and facilitating the course.

Particular thank you goes to Prof. Mario Wuthrich, Prof. Paul Embrechts and Prof. Patrick Cheridito

for the invitation and support offered by ETH D-Math and RiskLab.

Statistical Machine Learning and Data Analytic Methods

for Risk and Insurance.

Lecture Created and Delivered by Prof. Gareth W. Peters

Feedback, comments, suggestions welcome at garethpeters78@gmail.com

NOTE: Content from this lecture series will form the elements of the forthcoming book on unsupervised learning methods that are applicable to Risk and Insurance modelling:

Prof. Gareth W. Peters.

"Unsupervised Statistical Machine Learning Methods for Risk and Insurance"

Zurich Lectures in Advanced Mathematics,

European Mathematical Society Publishing House.

Further, the coverage of semi-supervised and supervised machine learning and data analytic methods will form the basis of aspects of a forthcoming book:

Macrina A. and Peters G.W.

"Innovations in Computational Statististics, Data Analytics and Machine Learning for Insurance and Risk Management".

CRC Press Oxford

A pre-print lecture notes draft version Text 1 "Unsupervised Statistical Machine Learning Methods for Risk and Insurance" is available as draft LECTURE NOTES:

Peters, Gareth William, Statistical Machine Learning and Data Analytic Methods for Risk and Insurance.

Available at SSRN: https://ssrn.com/abstract=3050592