top of page
Rechercher
  • Photo du rédacteurHélène Dufour

Neural networks for insurance pricing with frequency and severity data.

The paper explores the use of machine learning, particularly deep learning techniques, in insurance pricing by modeling claim frequency and severity data. It compares the performance of various models, including generalized linear models and neural networks, on insurance datasets with diverse input features. The authors use autoencoders to process categorical variables and create surrogate models for neural networks to translate insights into practical tariff tables.


Posts récents

Voir tout

Comments on the Final Trilogue Version of the AI Act

“This paper provides a comprehensive analysis of the recent EU AI Act, the regulatory framework surrounding Artificial Intelligence (AI), focusing on foundation models, open-source exemptions, remote

Commenti


bottom of page