Augmenting zone-level MTPL claim frequency models with coordinates, environmental features at 5 km scale, and image embeddings improves predictive accuracy on unseen postcodes across GLM, regularized GLM, and tree-based models.
Claim frequency estimation in motor third-party liability (mtpl): Classical statistical models versus machine learning methods
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Revealing Geography-Driven Signals in Zone-Level Claim Frequency Models: An Empirical Study using Environmental and Visual Predictors
Augmenting zone-level MTPL claim frequency models with coordinates, environmental features at 5 km scale, and image embeddings improves predictive accuracy on unseen postcodes across GLM, regularized GLM, and tree-based models.