Automatic analysis of insurance reports through deep neural networks to identify severe claims - Sorbonne Université Access content directly
Journal Articles Annals of Actuarial Science Year : 2021

Automatic analysis of insurance reports through deep neural networks to identify severe claims

Abstract

In this paper, we develop a methodology to automatically classify claims using the information contained in text reports (redacted at their opening). From this automatic analysis, the aim is to predict if a claim is expected to be particularly severe or not. The difficulty is the rarity of such extreme claims in the database, and hence the difficulty, for classical prediction techniques like logistic regression to accurately predict the outcome. Since data is unbalanced (too few observations are associated with a positive label), we propose different rebalance algorithm to deal with this issue. We discuss the use of different embedding methodologies used to process text data, and the role of the architectures of the networks.
Fichier principal
Vignette du fichier
neural-nouveau-mieux.pdf (608.25 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02570584 , version 1 (12-05-2020)

Identifiers

  • HAL Id : hal-02570584 , version 1

Cite

Isaac Cohen Sabban, Olivier Lopez, Yann Mercuzot. Automatic analysis of insurance reports through deep neural networks to identify severe claims. Annals of Actuarial Science, 2021. ⟨hal-02570584⟩
319 View
416 Download

Share

Gmail Facebook X LinkedIn More