Weather Conditions and Telematics Panel Data in Monthly Motor Insurance Claim Frequency Models

Risk analysis in motor insurance aims to identify factors that increase the frequency of accidents. Telematics data is used measure behavioural information drivers. Contextual variables include temperature, rain, wind and traffic conditions are external driver, but may also influence probability having an accident, as well vehicle personal characteristics. This paper uses a monthly panel structure Poisson model predict expected claims over time. Some meteorological included. Two types considered separately: only those related at-fault third-party liability accidents, all including assistance on road. A sample drivers Spain 2018–2019 analysed with claiming per month. Drivers were observed for seven months. Our novel because summaries telematics combined weather structure, revealing affect frequencies. Reckless speeding behaviours intense urban circulation risk which increases windy conditions.