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.

Machine Learning (stat.ML); Machine Learning (cs.LG); Risk Management (q-fin.RM)

arXiv:2609.26445 [stat.ML]

(or arXiv:2609.26445v1 [stat.ML] for this version)

https://doi.org/10.48550/arXiv.2609.26445 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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