Gaussian process models in actuarial science
Abstract Gaussian Process (GP) modeling is a probabilistic, non-parametric framework for describing spatio-temporal dependence that is well-suited for fitting risk-related surfaces. I summarize the main emerging actuarial use cases of GPs, including their applications in longevity modeling, insurance contract valuation, and loss development. The editorial also discusses further contexts with potential for GP-based approaches.
Authors
- Michael Ludkovski (ORCID: https://orcid.org/0000-0001-7887-3870)
Institutions
- University of California, Santa Barbara (US)
Publication Details
- Journal
- Annals of Actuarial Science
- Published
- 2026-02-26
- DOI
- https://doi.org/10.1017/s1748499526100244
- Primary Topic
- Soil Geostatistics and Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00