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Open AccessFeature PaperArticle

Analysis of Stochastic Reserving Models By Means of NAIC Claims Data

1
Department of Probability Theory and Statistics, Eötvös Loránd University, Pázmány Péter sétány 1/C, 1117 Budapest, Hungary
2
NN Group, Prinses Beatrixlaan 35, 2595 AK The Hague, The Netherlands
Risks 2019, 7(2), 62; https://doi.org/10.3390/risks7020062
Received: 26 February 2019 / Revised: 26 May 2019 / Accepted: 28 May 2019 / Published: 4 June 2019
In the past two decades increasing computational power resulted in the development of more advanced claims reserving techniques, allowing the stochastic branch to overcome the deterministic methods, resulting in forecasts of enhanced quality. Hence, not only point estimates, but predictive distributions can be generated in order to forecast future claim amounts. The significant expansion in the variety of models requires the validation of these methods and the creation of supporting techniques for appropriate decision making. The present article compares and validates several existing and self-developed stochastic methods on actual data applying comparison measures in an algorithmic manner. View Full-Text
Keywords: stochastic claims reserving; probabilistic forecast; comparison metrics; credibility; Monte Carlo stochastic claims reserving; probabilistic forecast; comparison metrics; credibility; Monte Carlo
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Martinek, L. Analysis of Stochastic Reserving Models By Means of NAIC Claims Data. Risks 2019, 7, 62.

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