An Empirical Evaluation of Machine Learning Methods for the Insurance Industry

Dammann, Michael; Gnoss, Nicolai Achim; Kunert, Pamela; Ramcke, Eike-Christian; Schreier, Tobias Cedric; Steffens, Ulrike; Zukunft, Olaf

doi:10.1007/978-981-16-2380-6_82

Publisher DOI:	10.1007/978-981-16-2380-6_82
Title:	An Empirical Evaluation of Machine Learning Methods for the Insurance Industry
Language:	English
Authors:	Dammann, Michael Gnoss, Nicolai Achim Kunert, Pamela Ramcke, Eike-Christian Schreier, Tobias Cedric Steffens, Ulrike Zukunft, Olaf
Editor:	Yang, Xin-She Sherratt, Simon Dey, Nilanjan Joshi, Amit
Keywords:	Classification; Initial reserve; Insurance claims; Machine learning; Regression
Issue Date:	1-Jan-2022
Publisher:	Springer
Part of Series:	Proceedings of Sixth International Congress on Information and Communication Technology
Volume number:	2
Journal or Series Name:	Lecture notes in networks and systems
Volume:	236
Startpage:	933
Endpage:	941
Conference:	International Congress on Information and Communication Technology 2021
URI:	http://hdl.handle.net/20.500.12738/12313
ISBN:	978-981-16-2379-0 978-981-16-2381-3 978-981-16-2380-6
ISSN:	2367-3370
Edition / version:	1st ed. 2022
Institute:	Department Informatik Fakultät Technik und Informatik
Type:	Chapter/Article (Proceedings)
Appears in Collections:	Publications without full text