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Open AccessFeature PaperArticle

Claim Watching and Individual Claims Reserving Using Classification and Regression Trees

1
Department of Statitistical Sciences, Sapienza University of Rome, Rome 00185, Italy
2
Department of Economics, University of Perugia, 06123 Perugia, Italy
3
Alef – Advanced Laboratory Economics and Finance, 00198 Rome, Italy
*
Author to whom correspondence should be addressed.
Risks 2019, 7(4), 102; https://doi.org/10.3390/risks7040102
Received: 21 August 2019 / Revised: 28 September 2019 / Accepted: 2 October 2019 / Published: 12 October 2019
(This article belongs to the Special Issue Claim Models: Granular Forms and Machine Learning Forms)
We present an approach to individual claims reserving and claim watching in general insurance based on classification and regression trees (CART). We propose a compound model consisting of a frequency section, for the prediction of events concerning reported claims, and a severity section, for the prediction of paid and reserved amounts. The formal structure of the model is based on a set of probabilistic assumptions which allow the provision of sound statistical meaning to the results provided by the CART algorithms. The multiperiod predictions required for claims reserving estimations are obtained by compounding one-period predictions through a simulation procedure. The resulting dynamic model allows the joint modeling of the case reserves, which usually yields useful predictive information. The model also allows predictions under a double-claim regime, i.e., when two different types of compensation can be required by the same claim. Several explicit numerical examples are provided using motor insurance data. For a large claims portfolio we derive an aggregate reserve estimate obtained as the sum of individual reserve estimates and we compare the result with the classical chain-ladder estimate. Backtesting exercises are also proposed concerning event predictions and claim-reserve estimates.
Keywords: individual claims reserving; claim watching; classification and regression trees; machine learning individual claims reserving; claim watching; classification and regression trees; machine learning
MDPI and ACS Style

Felice, M.D.; Moriconi, F. Claim Watching and Individual Claims Reserving Using Classification and Regression Trees. Risks 2019, 7, 102.

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