The General Insurance Machine Learning in Reserving working party (MLR WP) is a group of over 70 volunteers, bringing together a range of data scientists, actuaries and academics from around the globe.
When we started out in 2019, our premise was to find out why, whilst machine learning techniques are widespread in pricing, they are not being adopted ‘on the ground’ in reserving (certainly in the UK). Since then we have been working to help GI reserving actuaries develop data science skills, and are looking at ways that machine learning can be incorporated into reserving practice.
On this site you will find information from our various workstreams:
- Foundations – where do I start/how do I learn machine learning?
- Literature Review – we have reviewed over 60 papers and have highlighted a few of the best.
- Research – we are conducting a variety of research projects. We always aim to share the code so you can try it for yourself.
- Practical considerations – how to interpret ML models/explainability, how to deal with the issues reserving teams come across.
- Data – what data is available to develop ML techniques on?
- Survey – why has uptake of machine learning in reserving been slow and what are UK and Canadian companies doing in-house (from 2020)?