ICRFS-Plus™ 10.2 Demonstration videos
ICRFS-Plus™ is a tour de force of interactive software design and computational speed.
View the videos below to experience the numerous unique benefits and applications afforded by a paradigm shift.
Some of the (real) case studies modeled in the videos are also discussed briefly in the ICRFS-Plus™ brochure.
These videos are arranged in logical order so it is important that you view them that way.
If for any reason you are unable to view the training or demonstration videos, please contact our support staff at support@insureware.com and we will arrange to send you a copy of the videos on CD-Rom. You will be able to run the videos from the CD.
The training videos should be used for hands on training.
We suggest you run the videos on a separate computer using a data projector, and train as a group.
The only way you will learn all the new concepts and be able to
exploit all the immense benefits is by using the system. Experiential
learning is imperative.
It is important that you study the videos in sequential order set
out below.
Table of Contents
1. Introduction to ICRFS-Plus™
2. Applications of the PTF and ELRF modelling frameworks
3. The MPTF modelling framework
6. Importing data into ICRFS-Plus and COM Automation
7. Additional applications of ICRFS-Plus™
7. Additional applications of ICRFS-Plus™
7.1 Pricing high layers (low frequency/high severity) and relationships between gross and net of reinsurance data.
The findings in this chapter corroborate some of the surprising findings in chapter 3. This should have a major impact on reinsurance programs for long tail liabilities.
Using real life data it is shown how to price higher layers even though the triangles for the higher layers are replete with zeros.
A composite model is designed for the layered composite data set Lim 0.5M, Lim 1M,..., Lim 4M and Groundup. Both process correlations and parameter correlations between the layers are very high. These induce high correlations in predicted lognormals between the cells in any two layers.
To price a layer such as 1Mxs1M, for example, the differences of the simulated values for Lim 2M and Lim 1M are used that incorporates a strong covariance term between the two layers. It is found that from the point of view of the cedant the coefficient of variation of net reserves is invariant with regard to attachment points and is almost the same as the coefficient of variation of the gross reserves. Accordingly, the percentage capital required above the mean to subscribe to a particular percentile is also invariant with attachment points.
Insureware's extensive database has many other examples of this phenomenon.
Therefore, there is much empirical evidence to suggest that excess of loss (on individual losses) is not capital efficient for a cedant.
Chapter 3 considered an example where it was shown that the coefficient of variation of net reserves is the same as the coefficient of variation of gross reserves.
Two further real life examples are given here. The net of reinsurance and gross data are modeled in the MPTF modelling framework. The composite models include the high process and parameter correlation between the two triangles.
Click here to view this video.
For additional information on ICRFS-Plus™ features - click here.