Time: Wed, Aug 24, 2022 09:00 AM - 10:30 AM CST

About This Event

In traditional GLM modelling, categorical features are often treated with one-hot encoding. However, this method of encoding removes any ordering information inherent in the data. With accurate GLM, we propose to utilize an alternative encoding approach which allows us to preserve the ordering information, without requiring that the variable be converted to numeric form. In this presentation, we will introduce the accurate GLM approach to modelling, discuss what motivated the approach, and illustrate the approach through simulated data modelling exercises and a case study.

Key Messages

GLM as a model structure is a known and often used tool for a pricing actuary. Despite this maturity, it is good to be reminded we can design algorithms and approaches to enrich the GLM modeling process. Accurate GLM, an approach conceived by Hirokazu Iwasawa and introduced in the 2021 Hachemeister Prize winning co-authored paper "AGLM: A Hybrid Modeling Method of GLM and Data Science Techniques", showcases this by offering a way to handle the shaping of the relationship between the ordered data and response. We hope the practical illustrations in this presentation will both introduce a new tool for the actuaries and spark a call to look at the modeling process with fresh eyes.

Learning Objective

• Become familiar with the concepts and motivations behind the accurate GLM technique
• Learn how to set up data and carry out modelling using the accurate GLM technique