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Neural Networks in Insurance


Neural Networks in Insurance

Goulet, Magali-Chen (2021) Neural Networks in Insurance. Masters thesis, Concordia University.

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To date, in the insurance industry, the premium for a given risk is based on the expected claim amount since the models used are only meant to calculate a mean response. However, getting more information about the distribution of each single risk would be useful for risk assessment. A method in Neural Networks (NN) called Tractable Approximate Gaussian Inference (TAGI) by Goulet et al. (2020) allows to study each response individually since each output follows its own Normal distribution. The main contributions of this thesis are to make this technique available through an open source package, to apply TAGI in insurance and compare it to other techniques and to study risk measures with it.

Divisions:Concordia University > Faculty of Arts and Science > Mathematics and Statistics
Item Type:Thesis (Masters)
Authors:Goulet, Magali-Chen
Institution:Concordia University
Degree Name:M. Sc.
Date:23 July 2021
Thesis Supervisor(s):Mailhot, Mélina
ID Code:988930
Deposited On:29 Nov 2021 16:44
Last Modified:29 Nov 2021 16:44
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