Machine Learning in Insurance

Machine Learning in Insurance

Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand...

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Kolejni autorzy: Nielsen, Jens Perch (Redaktor), Asimit, Alexandru (Redaktor), Kyriakou, Ioannis (Redaktor)
Format: Rozdział
Wydane: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020
Hasła przedmiotowe:
History of engineering & technology
deposit insurance
implied volatility
static arbitrage
parameterization
machine learning
calibration
dichotomous response
predictive model
tree boosting
GLM
validation
generalised linear modelling
zero-inflated poisson model
telematics
benchmark
cross-validation
prediction
stock return volatility
long-term forecasts
overlapping returns
autocorrelation
chain ladder
Bornhuetter-Ferguson
maximum likelihood
exponential families
canonical parameters
prior knowledge
accelerated failure time model
chain-ladder method
local linear kernel estimation
non-life reserving
operational time
zero-inflation
overdispersion
automobile insurance
risk classification
risk selection
least-squares monte carlo method
proxy modeling
life insurance
Solvency II
claims prediction
export credit insurance
semiparametric modeling
VaR estimation
analyzing financial data
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