Advancing Pay‑as‑You‑Drive Insurance with Bayesian Models: Risk Prediction and Factor Causal Mapping
This study explores a Bayesian approach to Pay‑As‑You‑Drive (PAYD) insurance, using Naive Bayes classifiers and Bayesian Networks for risk assessment. It achieved 87.5% accuracy in predicting risk and improved interpretability over traditional models, optimizing pricing strategies and promoting affordable coverage by dismissing geographic grouping in insurance pricing.