Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: Machine learning applications in non‐life insurance : discussion rejoinder
Authors: Grize, Yves-Laurent
Fischer, Wolfram
Lützelschwab, Christian
et. al: No
DOI: 10.1002/asmb.2564
Published in: Applied Stochastic Models in Business and Industry
Volume(Issue): 36
Issue: 4
Page(s): 545
Pages to: 547
Issue Date: 2020
Publisher / Ed. Institution: Wiley
ISSN: 1524-1904
Language: English
Subject (DDC): 004: Computer science
332.38: Insurances
Abstract: We are much grateful to the editors for having organized a discussion of our paper. Our thanks also go to our distinguished discussants for their insightful contributions and the provided additional references. In our rejoinder, we first discuss the topic of interpretability, then briefly review the applications of machine learning (ML) to non-life insurance, and finally select a few stimulating remarks made by the discussants for further comments.
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Appears in collections:Publikationen School of Engineering

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