E73 - Katja Hanewald - From the Frontier of Population Ageing Research

Katja Hanewald is a Senior Lecturer in the School of Risk and
Actuarial Studies at UNSW Sydney, which has been ranked 1st in
the world for Actuarial Science, Risk Management and Insurance
research. She is also the Coordinator of the Actuarial Co-op
Program at the university. Apart from that, Katja is the Director
of Research of the Ageing Asia Research Hub, which is hosted by
the ARC Centre of Excellence in Population Ageing Research
(CEPAR).


Katja’s major expertise and research interests are risk
management for retirement financial products and insurance
responses to population ageing. Her research papers and articles
have been published in all leading international insurance and
actuarial journals and major economics journals.


Katja has been a research-driven academician for over a decade
from the very beginning of her career. After obtaining her
doctoral degree from the School of Business and Economics at
Humboldt-Universität zu Berlin in November 2010, she worked as a
postdoc researcher in the ARC Centre of Excellence in Population
Ageing Research (CEPAR) at UNSW Sydney from 2011 to 2013. She
moved back to Germany in 2013 to work for the German Federal
Ministry of Finance from 2013 to 2015. In 2016, she returned to
Sydney to re-join CEPAR and UNSW Sydney, and is now a Senior
Lecturer in the School of Risk & Actuarial Studies.


This episode starts with Katja sharing with us about her
background in research and what led her to focus on economics,
actuarial, insurance, and risk management.


Following this, the discussion moves through the following areas:


How the School of Risk and Actuarial Studies at UNSW is
helping actuarial students to explore different career paths,
such as traditional actuarial works as well as data science.

Katja’s research work around retirement insurance product
development.

Deep dive into creating a new model for the insurers,
combining the General Linear Model (GLM) and neural network.

How the new model addresses some of the shortcomings of the
GLM.

How the model allows analytics professionals and actuaries to
incorporate additional factors, linear and nonlinear
relationships among variables, and emphasize expert opinion.

How the insurers could benefit from this new model in
multiple ways, including understanding the mortality modelling
using individual-level data, solving risk classification problems
for insurance claims, microsimulation health models, and long
term care insurance pricing.



If you are an actuary or data scientist working on building
analytics models for your applications, not only will you find
Katja’s proposals to be uniquely refreshing, but you will also
learn new perspectives in combining different models to solve the
problems you may have at hand.


If you are a senior executive in the insurance or reinsurance
industry, this could be useful in understanding and developing a
new insurance product for the ever-changing consumer needs.