9 citations · 17 across the 6 of their papers we have counts for
6 papers
Telematics Combined Actuarial Neural Networks for Cross-Sectional and Longitudinal Claim Count Data
Francis Duval, Jean-Philippe Boucher, Mathieu Pigeon
We present novel cross-sectional and longitudinal claim count models for vehicle insurance built upon the Combined Actuarial Neural Network (CANN) framework proposed by Mario Wüthr…
Enhancing Claim Classification with Feature Extraction from Anomaly-Detection-Derived Routine and Peculiarity Profiles
Francis Duval, Jean-Philippe Boucher, Mathieu Pigeon
Usage-based insurance is becoming the new standard in vehicle insurance; it is therefore relevant to find efficient ways of using insureds' driving data. Applying anomaly detection…
Individual Claims Reserving using Activation Patterns
Marie Michaelides, Mathieu Pigeon, Hélène Cossette
The occurrence of a claim often impacts not one but multiple insurance coverages provided in the contract. To account for this multivariate feature, we propose a new individual cla…
How much telematics information do insurers need for claim classification?
Francis Duval, Jean-Philippe Boucher, Mathieu Pigeon
It has been shown several times in the literature that telematics data collected in motor insurance help to better understand an insured's driving risk. Insurers that use this data…
A Claim Score for Dynamic Claim Counts Modeling
Jean-Philippe Boucher, Mathieu Pigeon
We develop a claim score based on the Bonus-Malus approach proposed by [7]. We compare the fit and predictive ability of this new model with various models for of panel count data.…
Macro vs. Micro Methods in Non-Life Claims Reserving (an Econometric Perspective)
Arthur Charpentier, Mathieu Pigeon
Traditionally, actuaries have used run-off triangles to estimate reserve ("macro" models, on agregated data). But it is possible to model payments related to individual claims. If…