arXiv:2604.21893v1 Announce Type: new Abstract: Geographic context is often consider relevant to motor insurance risk, yet public actuarial datasets provide limited location identifiers, constraining how this information can be incorporated and evaluated in claim-frequency models. This study examines how geographic information from alternative data sources can be incorporated into actuarial models
Revealing Geography-Driven Signals in Zone-Level Claim Frequency Models: An Empirical Study using Environmental and Visual Predictors
Sherly Alfonso-S\'anchez, Cristi\'an Bravo, Kristina G. Stankova·arXiv stat.ML··1 min read
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