We analyse a large telematics data with 65 driving variables (DVs) and insurance claim counts for 14,157 drivers. Our aim is to predict future claims according to driving behaviour measured by the DVs, to identify important DVs that differentiate driving behaviours, classify drivers according to...

We leverage telematics data on driving behavior variables to assess driver risk and predict future insurance claims in a case study utilising a representative telematics sample. In the study, we aim to categorise drivers according to their driving habits and establish premiums that accurately...

Managing market expectations about monetary policy through communication is important for central banks. However, this expectation management often shows inefficiency in practice, leading to the misalignment between central banks and market participants. This misalignment is likely to influence...