Videos marked with an (*) contain discussion of new content in ICRFS-Plus™ 12.
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9. Layers and the PALD Module
In this video we are studying layers and the predictive aggregate loss distribution (PALD) module.
The Triangle Groups: All 1M, All 1Mxs1M and All 2M are three layers. The structure of the models is very similar in all three layers. Note that the calendar trend in the intermediate layer: 1Mxs1M is not significant.
An identified PTF model predicts log normal distributions for each cell and their correlations. There is no analytical distribution of the sum of log normals. In order to determine the distribution of an aggregate of log normals we need to simulate from each log normal including their correlations. The PALD module provides the facility to conduct simulations in order to obtain distributions of aggregates for accident periods, calendar years and the total reserve. This output can then be used to compute percentiles and VaR tables.
The Reinsurance module is also covered. This module allows the evaluation of varying attachment points with the resultant expected payouts for the Insurer or Reinsurer (compared to no cover).
The output tables from these PALD and Reinsurance modules are explained.
The PALD results are run for the reserve distribution as well as for future pricing years.
It is important to include parameter uncertainty in the forecasting scenarios. Parameters with the same mean but different standard deviations are not the same forecast scenario.