The Actuary and IBNR Techniques: A Machine Learning Approach
53 Pages Posted: 11 Nov 2020 Last revised: 13 Nov 2020
Date Written: August 14, 2020
Abstract
Actuarial reserving techniques have evolved from the application of algorithms, like the chain-ladder method, to stochastic models of claims development, and, more recently, have been enhanced by the application of machine learning techniques. Despite this proliferation of theory and techniques, there is relatively little guidance on which reserving techniques should be applied and when. In this paper, we revisit traditional reserving techniques within the framework of supervised learning to select optimal reserving models. We show that the use of optimal techniques can lead to more accurate reserves and investigate the circumstances under which different scoring metrics should be used.
Keywords: IBNR, machine learning, reserving, short-term insurance, non-life insurance
JEL Classification: G22
Suggested Citation: Suggested Citation