IMPROVING AUTOMOBILE INSURANCE CLAIMS FREQUENCY PREDICTION WITH TELEMATICS CAR DRIVING DATA

DOI10.1017/asb.2021.35zbMath1492.91306OpenAlexW4200053638MaRDI QIDQ5866172

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Publication date: 13 June 2022

Published in: ASTIN Bulletin (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/asb.2021.35

zbMATH Keywords

generalized linear modeltelematics car driving datalimited fluctuation credibility modelclaims frequencyone-dimensional convolutional neural networkautomobile insurance pricing

Mathematics Subject Classification ID

Actuarial mathematics (91G05)

Cites Work

• Classification of scale-sensitive telematic observables for riskindividual pricing
• Making Tweedie's compound Poisson model more accessible
• Multilayer feedforward networks are universal approximators
• Boosting Poisson regression models with telematics car driving data
• THE USE OF ANNUAL MILEAGE AS A RATING VARIABLE
• Can Automobile Insurance Telematics Predict the Risk of Near-Miss Events?

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