This 3-day workshop, funded by the Duncan Laboratory for Insurance Data Science, will focus on applications of machine learning and data science in insurance, health and mortality.
The use of big data and machine learning algorithms has become more prevalent in recent years in the insurance industry, the health sector and academia, leading to new insights in a variety of areas of application including: the modelling of natural hazards; quantifying mortality and health inequalities; the evolving impact of climate extremes; insurance pricing and reserving; telematics; and epidemiology.
The workshop will focus on applications of machine learning and data science and on the interpretability of modelling results. We aim to bring together leaders in both academia and industry to share ideas about what the most effective tools are for a range of insurance and health-related applications, but we will also discuss what the limitations are of specific methods to help avoid inappropriate use in specific settings.
Participation
Academics and practitioners interested in presenting on a topic related to the themes above can submit a summary or abstract via the application form. Please click “Apply Here” on top of this page.
We will also have a limited number of places for non-speakers. Please fill out the application form as well if you are interested to attend.
A member of ICMS staff will be in touch regarding your participation mid to late October.
