Machine Learning in Insurance

Abstract

The Machine Learning Working Party of the CAS identified one barrier to entry for actuaries interested in machine learning (ML) as being the fact that published research in an insurance context is sparse. The purpose of this paper is to provide references and descriptions of current research to act as a guide for actuaries interested in learning more about this field and for actuaries interested in advancing research in machine learning.

Volume
Winter
Year
2022
Keywords
machine learning, modeling, predictive analytics
Description
The Machine Learning Working Party of the CAS identified one barrier to entry for actuaries interested in machine learning (ML) as being the fact that published research in an insurance context is sparse. The purpose of this paper is to provide references and descriptions of current research to act as a guide for actuaries interested in learning more about this field and for actuaries interested in advancing research in machine learning.
Publications
Casualty Actuarial Society E-Forum
Authors
Marco De Virgilis
Daniel Lupton
Liam McGrath
Marjan Qazvini
Seth Roby
Leslie Vernon
Formerly on syllabus
Off