PreprintCC BY 4.0arXiv
A Practical Guide on Graphical Model Validation
Abstract
This manuscript formalizes the most popular model validation tools used in general insurance actuarial modeling. These include graphical tools like calibration plots, actual-vs-expected plots, lift charts, Murphy diagrams, as well as classical statistical tools such as Bregman losses, deviance losses, elementary losses, Murphy's decomposition and Gini scores. Particular emphasis is placed on whether calibration and discrimination are studied under a policy-weighted or an exposure-weighted population measure. This distinction is crucial in ensuring that premium schemes are calibrated on the correct scale.
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BibTeX
@misc{wuthrich2026practical,
title = {{A Practical Guide on Graphical Model Validation}},
author = {Mario V. Wüthrich},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.26445},
eprint = {2609.26445},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.26445},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - A Practical Guide on Graphical Model Validation
AU - Mario V. Wüthrich
PY - 2026
DA - 2026/09/22
PB - arXiv
DO - 10.48550/arxiv.2609.26445
UR - https://arxiv.org/abs/2609.26445
AB - This manuscript formalizes the most popular model validation tools used in general insurance actuarial modeling. These include graphical tools like calibration plots, actual-vs-expected plots, lift charts, Murphy diagrams, as well as classical statistical tools such as Bregman losses, deviance losses, elementary losses, Murphy's decomposition and Gini scores. Particular emphasis is placed on whether calibration and discrimination are studied under a policy-weighted or an exposure-weighted population measure. This distinction is crucial in ensuring that premium schemes are calibrated on the correct scale.
ER -