תאריך האירוע : 11/02/2021
פרטים אודות ההרצאה:
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 talk, we present recent work on reframing traditional reserving techniques within the framework of supervised learning, with the goal of selecting 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.
פרטים אודות המרצה:
Ron is an experienced actuary and risk manager, currently an Associate Director at QED Actuaries and Consultants, where he is responsible for client work on life and general insurance clients and performing research into applications of machine learning and AI to actuarial and insurance topics. Before this, he led the Enterprise Risk Management and Actuarial Functions for the AIG group within Africa for several years. Ron is a Fellow of the Institute and Faculty of Actuaries (IFoA) and the Actuarial Society of South Africa (ASSA), holds practicing certificates in Short Term Insurance and Life Insurance from ASSA, and a Masters of Philosophy in Actuarial Science, with distinction, from the University of Cape Town.
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