Micro-level parametric duration-frequency-severity modeling for outstanding claim payments

Abstract

Unlike collective models, individual models have the advantage of keeping the attributes of each claim intact. We propose a three-component parametric individual model that uses this information in the form of explanatory variables. The first component predicts the delays between the occurrence, report, and closure of each claim using parametric survival models. For the second (frequency) and third (severity) components, we use generalized linear models and splice models. Moreover, the elapsed time between report and closure of claims is converted into an exposure variable in the count model. Finally, we discuss estimation procedures, make predictions, and compare the results with other models using a data set from a major Canadian insurance company.

Copula-based Modeling for IBNR Claim Loss Reserving

“…In order to compute the IBNR claim loss reserves, the classical methods apply data exploration to predict future expected losses, such as Bornhuetter-Ferguson (BF) method proposed by Bornhuetter and Ferguson [1], Benktander-Hovinen method proposed by Benktander [2] and Hovinen [3], Cape Cod method proposed by Bühlmann and Straub [4] and Stanard [5], and Chain-Ladder (CL) method proposed by Mack [6]. For more information about deficiency and properties of these methods, one can refer to [7][8][9]. Another method to estimate the IBNR claim reserves is copula approach which models the dependency between occurring time and reporting time of an event.…”