 Enhancing claim classification with feature extraction from anomaly‐detection‐derived routine and peculiarity profilesFrancis Duval, Jean‐Philippe Boucher and Mathieu Pigeon Journal of Risk & Insurance, 2023, vol. 90, issue 2, 421-458 Abstract: 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 (AD) to vehicles' trip summaries, we develop a method allowing to derive a “routine” and a “peculiarity” anomaly profile for each vehicle. To this end, AD algorithms are used to compute a routine and a peculiarity anomaly score for each trip a vehicle makes. The former measures the anomaly degree of the trip compared with the other trips made by the concerned vehicle, while the latter measures its anomaly degree compared with trips made by any vehicle. The resulting anomaly scores vectors are used as routine and peculiarity profiles. Features are then extracted from these profiles, for which we investigate the predictive power in the claim classification framework. Using real data, we find that features extracted from the vehicles' peculiarity profile improve the classification. Date: 2023 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:jrinsu:v:90:y:2023:i:2:p:421-458 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of Risk & Insurance is currently edited by Joan T. Schmit More articles in Journal of Risk & Insurance from The American Risk and Insurance Association Contact information at EDIRC. |
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