Credibility Python Packages

actuarialpy

Purpose-neutral actuarial calculation primitives: metrics, reserving, trend, credibility, pooling, financial math. Foundation of the OpenActuarial ecosystem.

ratingmodels

Manual and experience rating, credibility blending, and rate indication with an audit trail; GLM relativities and frequency-severity modeling.

insurance-credibility

Credibility models for UK non-life insurance pricing: Bühlmann-Straub and Bayesian experience rating

bayesian-pricing

Hierarchical Bayesian models for insurance pricing — PyMC 5, thin-data segments, credibility factors

actuarcredibility

Credibility models for actuarial pricing: Bühlmann, Bühlmann-Straub, Jewell hierarchical, Hachemeister regression, classical, and Bayesian (PyMC). pip install actuarcredibility

insurance-experience

Individual policy Bayesian experience rating for insurance pricing — static, dynamic, surrogate and deep attention credibility models, balance property

credibility

Bühlmann-Straub credibility weighting for insurance pricing - modern Python, CatBoost, Polars

insurance-credibility-transformer

Credibility Transformer — CLS token attention as Bühlmann-Straub credibility, ICL zero-shot pricing, base/deep/ICL variants