Enhancing actuarial non-life pricing models via transformers

DOI10.1007/s13385-024-00388-2MaRDI QIDQ6649330

Alexej Brauer

Publication date: 5 December 2024

Published in: European Actuarial Journal (Search for Journal in Brave)

zbMATH Keywords

transformerregression modelstabular datadeep learningnon-life insurance

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Actuarial mathematics (91G05)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Generalized additive models
• Autocalibration and Tweedie-dominance for insurance pricing with machine learning
• Bayesian Deep Net GLM and GLMM
• LocalGLMnet: interpretable deep learning for tabular data
• The balance property in neural network modelling
• Non-Life Insurance Risk Classification Using Categorical Embedding
• Time-series forecasting of mortality rates using transformer
• The use of autoencoders for training neural networks with mixed categorical and numerical features
• Statistical Foundations of Actuarial Learning and its Applications
• A multi-task network approach for calculating discrimination-free insurance prices

This page was built for publication: Enhancing actuarial non-life pricing models via transformers