Machine learning in individual claims reserving

Mario V. Wüthrich

102 citations0/0 files storedScandinavian Actuarial Journal

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Probability and Risk Models Insurance and Financial Risk Management Insurance, Mortality, Demography, Risk Management

Abstract

Machine learning techniques make it feasible to calculate claims reserves on individual claims data. This paper illustrates how these techniques can be used by providing an explicit example in individual claims reserving.

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References

1993Distribution-free Calculation of the Standard Error of Chain Ladder Reserve Estimates 2013Micro-level stochastic loss reserving for general insurance

Cited by

2017Data Analytics for Non-Life Insurance Pricing 2018Neural networks applied to chain–ladder reserving 2019DeepTriangle: A Deep Learning Approach to Loss Reserving 2019A machine learning approach for individual claims reserving in insurance 2018An Individual Claims History Simulation Machine 2020Machine Learning in P&C Insurance: A Review for Pricing and Reserving 2021Recent Challenges in Actuarial Science 2019Individual Loss Reserving Using a Gradient Boosting-Based Approach

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