Workshop on Time to Event Data and Machine Learning
The Danish pension system has evolved over the last few decades leading to more flexible pension products with more choice on types of investments and when to retire. Currently, topics such as choice of pension type and questions about when people retire are under-researched. Both topics are highly relevant to both business and society, for example by
- A refinement of predictive methods on an individualized level that will provide for better resource allocation and improve risk assessments.
- A deepening of the causal understanding of pension choices and retirement decisions that will improve our ability to assess policy decisions as well as to provide personalized counselling.
The availability of large amounts of high quality administrative and firm data, we have in Denmark, as well as the rapid development of methods for handling large datasets makes this problem ideal for collaborations between statisticians, insurance mathematicians and economists.
KU: Christian Furrer, Thomas Gerds, Snorre Jallbjørn, Nikolaj Thams
CBS: Benjamin Christoffersen, Shuolin Shi
External: Jens Perch Nielsen (CASS Business School)
Pension Industry: Søren Jarner (ATP), Kristian Buchardt (PFA)
Organisers: Niels Richard Hansen (KU), Søren Feodor Nielsen (CBS), Ralf Andreas Wilke (CBS)