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3 résultats pour « insurance pricing »

A novel k‑generation propagation model for cyber risk and its application to cyber insurance.

27 août 2024 Autre, cyber risk, insurance pricing, tree-shaped topology, risk propagation, aggregate loss

This paper develops a k-generation risk contagion model in a tree-shaped network for cyber insurance pricing. It accounts for contagion location and security level heterogeneity. Using Bayesian network principles, it derives mean and variance of aggregate losses, aiding accurate cyber insurance pricing. Key findings benefit risk managers and insurers.

Sensitivity‑Based Measures of Discrimination in Insurance Pricing

20 août 2024 Autre, insurance pricing, global sensitivity analysis, demographic parity, algorithmic fairness, Proxy discrimination

This paper emphasizes the need for metrics to assess discriminatory effects and trade-offs. It introduces a sensitivity-based measure for proxy discrimination, defining admissible prices and using L2-distance for measurement, and proposes local measures for policyholder-specific analysis.

Neural networks for insurance pricing with frequency and severity data.

20 oct. 2023 Autre, insurers, machine learning, insurance pricing, deep learning, performance comparison, claim frequency, gradient-boosted tree model, feed-forward neural network, autoencoders, data preprocessing, input features, insurance datasets, tariff table, severity data, CANN, actuarial toolbox, generalized linear models, benchmark study, surrogate models, tabular insurance data, categorical variables

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.

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