Free 12-module course: Modern Insurance Pricing with Python and Databricks. GLMs, GBMs, SHAP relativities, conformal prediction, Bayesian credibility, rate optimisation, causal demand modelling, monitoring, spatial territory rating.

End-to-end insurance pricing pipeline: CatBoost frequency model, SHAP relativities, fairness audit, monitoring, and conformal intervals on a single synthetic UK motor dataset

D-vine copula model for multi-year policyholder claim modelling

ARCHIVED — merged into insurance-quantile

Zero-Inflated Tweedie Double GLM — three-head CatBoost EM (mu, phi, pi), balance check, Vuong test

Temporal cross-validation for insurance pricing models. Walk-forward splits respecting policy/accident year structure and IBNR development buffers.

ARCHIVED — merged into insurance-severity

SDID for causal rate change evaluation in insurance pricing — event study, HonestDiD sensitivity, FCA evidence pack (170 tests)

Bandit algorithms for GIPP-compliant price experimentation — UCB1, Thompson Sampling, LinUCB, ENBP constraints, FCA audit trail

GAMLSS for insurance pricing in Python — model variance, shape, and tail parameters as functions of covariates

Density ratio correction for insurance pricing book shifts — CatBoost/RuLSIF/KLIEP, LR-QR conformal, FCA SUP 15.3 diagnostics

Proxy discrimination diagnostics — LRTW 2026 D_proxy, Owen 2014 Shapley attribution, Côté 2025 proxy vulnerability, HTML/JSON audit reports

Conformal anomaly detection for claims fraud — BH FDR control, integrative conformal p-values, IFB Fisher combination, Mondrian stratification

Algorithmic recourse for FCA Consumer Duty in UK personal lines insurance pricing

Long-term fairness monitoring for insurance pricing - temporal drift in proxy discrimination metrics, cohort tracking

Joint longitudinal-survival models — Wulfsohn-Tsiatis SREM, EM+GHQ, DynamicPredictor for telematics mid-term repricing

Spatially Clustered Mixture of Experts for joint frequency-severity insurance pricing (NAAJ 2025)

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

Targeted Maximum Likelihood Estimation — doubly robust causal inference, Poisson TMLE with exposure offset, SuperLearner, CV-TMLE

Hierarchical Bayesian models for thin-data insurance pricing segments. PyMC 5, non-centered parameterization, credibility factors.