Model documentation, audit trails, explainability requirements, and the gap between what regulators say and what they actually inspect. Python tools that produce the evidence files regulators ask for. 9 articles.
The FCA has explicitly flagged pet insurance for monitoring in its 2026 regulatory priorities. FOS complaint upheld rates hit 52% in Q1 2025 — the highest of any UKGI business l...
FCA Consumer Duty PRIN 2A requires insurers to tell policyholders what they can change to get a better outcome. Most pricing teams have not built this. insurance-recourse does i...
FCA PS24/1 confirms enhanced Consumer Duty requirements from April 2026. EP25/2 flags ongoing fair value supervision in motor and home. No single technical checklist exists for ...
Mutual information, proxy R-squared, and SHAP proxy scores all flag proxy discrimination but catch different things. A practical guide to interpreting conflicting signals in ins...
The FCA expects pricing teams to demonstrate their models don't proxy-discriminate under Consumer Duty. Most teams do this in Excel. Here is how to do it properly in Python, usi...
Most UK insurers don't hold ethnicity, religion, or disability status. Consumer Duty still requires evidence of fair outcomes. PrivatizedFairnessAudit solves this with local dif...
Active Consumer Duty investigations in home and travel insurance. What a defensible pricing model actually requires under PRIN 2A, and what the FCA thematic review said about mo...
Detect and correct proxy discrimination in UK insurance using SHAP and insurance-fairness. Protected characteristic leakage detection under FCA Consumer Duty.