DeepTriangle: A Deep Learning Approach to Loss Reserving

Kevin Kuo
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Kevin Kuo: Kasa AI, 3040 78th Ave SE #1271, Mercer Island, WA 98040, USA

Risks, 2019, vol. 7, issue 3, 1-12

Abstract: We propose a novel approach for loss reserving based on deep neural networks. The approach allows for joint modeling of paid losses and claims outstanding, and incorporation of heterogeneous inputs. We validate the models on loss reserving data across lines of business, and show that they improve on the predictive accuracy of existing stochastic methods. The models require minimal feature engineering and expert input, and can be automated to produce forecasts more frequently than manual workflows.

Keywords: loss reserving; machine learning; neural networks (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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