Machine Learning in Insurance - Couverture rigide

Couverture rigide

ISBN 10 : 3039364472 ISBN 13 : 9783039364473

Editeur : Mdpi AG, 2020

Synopsis

Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand and how any solution may affect the company and its customers. One aspect that has, perhaps, not been so well developed among actuaries is validation. Discussions among actuaries' "preferred methods" were often without solid scientific arguments, including validation of the case at hand. Through this collection, we aim to promote a good practice of machine learning in insurance, considering the following three key issues: a) who is the client, or sponsor, or otherwise interested real-life target of the study? b) The reason for working with a particular data set and a clarification of the available extra knowledge, that we also call prior knowledge, besides the data set alone. c) A mathematical statistical argument for the validation procedure.

Détails de l'édition

• Éditeur: Mdpi AG
• Date d'édition: 2020
• Langue: anglais
• ISBN 10: 3039364472
• ISBN 13: 9783039364473
• Reliure: Relié
• Nombre de pages: 260
• Éditeur: Nielsen Jens Perch, Asimit Vali, Kyriakou Ioannis
• Coordonnées du fabricant: non disponible
• Personne responsable: gpsr@libri.de; gpsr@libri.de; ; Europaallee 1; Bad Hersfeld; 36244; Allemagne