File(s) under permanent embargo
Fast valuation of large portfolios of variable annuities via transfer learning
conference contribution
posted on 2019-01-01, 00:00 authored by X Cheng, Wei LuoWei Luo, G Gan, Gang LiGang LiVariable annuities are important financial products that result in 100 billion sales in 2018. These products contain complex guarantees that are computationally expensive to value, and insurance companies are turning to machine learning for the valuation of large portfolios of variable annuity policies. Although earlier studies, exemplified by the regression modelling approach, have shown promising results, the valuation accuracy is unsatisfying. In this paper, we show that one main cause for the poor valuation accuracy is the inefficient selection of representative policies. To overcome this problem, we propose a novel transfer-learning based portfolio valuation framework. The framework first builds a backbone deep neural network using historical Monte Carlo simulation results. The backbone network provides a valuation-driven representation for selecting the policies that best represent a large portfolio. Furthermore, the transferred network provides a way to adaptively extrapolate from these representative policies to the remaining policies in the portfolio. By overcoming a major difficulty faced by the popular Kriging model, the need of matrix inversion, the transferred network can handle a large number of representative policies to sufficiently cover a diverse portfolio.
History
Event
Pacific Rim International Conference of Artificial Intelligence (2019 : Cuvu, Fiji)Volume
11672Series
Lecture Notes in Computer SciencePagination
716 - 728Publisher
SpringerLocation
Cuvu, FijiPlace of publication
Berlin, GermanyPublisher DOI
Start date
2019-08-26End date
2019-08-30ISSN
0302-9743ISBN-13
9783030298937Language
engPublication classification
E1 Full written paper - refereedEditor/Contributor(s)
A Nayak, A SharmaTitle of proceedings
PRICAI 2019: Trends in Artificial IntelligenceUsage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC