JOINT MODEL PREDICTION AND APPLICATION TO INDIVIDUAL-LEVEL LOSS RESERVING

A. Nii-Armah Okine, Edward W. Frees and Peng Shi

ASTIN Bulletin, 2022, vol. 52, issue 1, 91-116

Abstract: Innon-life insurance, the payment history can be predictive of the timing of a settlement for individual claims. Ignoring the association between the payment process and the settlement process could bias the prediction of outstanding payments. To address this issue, we introduce into the literature of micro-level loss reserving a joint modeling framework that incorporates longitudinal payments of a claim into the intensity process of claim settlement. We discuss statistical inference and focus on the prediction aspects of the model. We demonstrate applications of the proposed model in the reserving practice with a detailed empirical analysis using data from a property insurance provider. The prediction results from an out-of-sample validation show that the joint model framework outperforms existing reserving models that ignore the payment–settlement association.

Date: 2022
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