In recent years, predictive modelling has changed important aspects of actuarial practice. Predictive modelling enhances traditional actuarial models with modern statistical tools and analysis. It uses emerging volumes of data to provide important insights into life and health insurance business, including how to identify appropriate risks, manage the risks insurance companies face, and improve the accuracy of actuarial projection models.

Predictive modelling impacts many areas of life and health insurance – from underwriting, to risk identification, to assumption setting and financial modelling. In underwriting, predictive modelling can be used to select the policyholders that meet desired risk profiles and to improve the accuracy of risk classification schemes. For existing blocks of business, predictive modelling allows actuaries to identify key risk factors impacting financial performance, creating opportunities to proactively manage those risk. As a projection tool, actuaries use predictive modelling to identify the key factors impacting actuarial assumptions, and to appropriately fit the assumptions used in financial projection models to historical data, potentially improving the accuracy of actuarial projections.

As actuaries enhance their focus on and knowledge of predictive analytic tools, it is likely that predictive modelling will play an increasingly important role in actuarial practice in the future. This seminar is designed to provide actuaries with the technical tools needed to be prepared for the ways in which actuarial practice may evolve in the coming years.

Organised by the EAA - European Actuarial Academy GmbH in cooperation with the Col·legi d’Actuaris de Catalunya.

The seminar is intended as a technical introduction for actuaries wishing to develop fundamental skills in predictive modelling techniques. It is designed for those who will be directly involved in the construction and analysis of predictive models. The seminar presumes no prior knowledge of predictive modelling or multivariate regression. However, attendees should have a working knowledge of basic statistics, simple linear regression, and life and health actuarial models.

Attendees are encouraged to bring a laptop computer with Microsoft Excel and R installed. The seminar will presume a working knowledge of statistics, linear regression, and programming in R. Attendees should review these concepts before arriving at the seminar; the first session of the seminar will include a brief review of this material.

The seminar will cover a broad range of topics in predictive modeling that are relevant to actuarial practice. The seminar begins with a review of the software R, including packages that are most commonly used in actuarial practice. The first day continues with a review of simple linear regression, and quickly shifts to more advanced, multivariate regression techniques that form the basis for many of the models that can be used in actuarial practice. The first day also features lessons aimed at identifying key variables for inclusion in actuarial models. Case studies will be used throughout the day to illustrate the important concepts and allow attendees to learn the techniques by building their own models.

The second day uses a case study format to explore several applications of predictive modeling to actuarial practice. The day begins with a case study on using logistic regression to predict claim events. The day concludes with an in-depth, technical exploration of generalized linear models that can be used to fit actuarial assumptions, and a demonstration of how this can improve the accuracy of financial models.

Andrew H. Dalton
Andrew is a Principal and Consulting Actuary in Milliman’s Philadelphia office. Andrew’s professional experience includes work on actuarial appraisals for mergers and acquisitions, asset and liability analysis, predictive modeling, and economic capital for life and health companies. Andrew is a Fellow of the Society of Actuaries and a Member of the American Academy of Actuaries. He holds a Masters Degree in Business Administration, concentrating in Finance and Statistics, from the Leonard N. Stern School of Business of New York University.

Robert Eaton
Robert is a Consulting Actuary in Milliman’s Tampa, Florida office. Robert specializes in long-term care, life insurance, and combination life and health insurance products. Robert is the Chairperson of the Society of Actuaries’ Long-Term Care Section Council. He serves on the Executive Committee for the Intercompany Long-Term Care Insurance conference. Robert is a Fellow in the Society of Actuaries and a Member of the American Academy of Actuaries. He holds Bachelor’s degrees in Mathematics and Industrial Engineering from the University of Florida.

Dominik Sznajder
Dominik is an actuarial consultant in Milliman’s Brussels office. He is a leader of Data Analytics team at Milliman Benelux which supports insurance companies in predictive analytics, data visualizations, data management, processes automation and big data projects. His work experience includes parameter studies and assumption setting (mortality, lapse and disability rates) for life insurance products and developing cost equalization schemes for the Dutch Health regulator. Dominik holds a PhD in Mathematical Statistics from KU Leuven in Belgium and a master degree in Actuarial Sciences from the University of Warsaw in Poland.