ICFS-Plus: Actuarial Software for the Property and Causality Insurance Industry

Videos marked with an (*) contain discussion of new content in ICRFS-Plus™ 12.

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 as set out below.

Table of Contents

1. Introduction to ICRFS-Plus™ 12 and modelling modules

    2. Modelling using the Link Ratio Techniques and Extended Link Ratio Family modelling framework

      3. Introduction to the Probabilistic Trend Family modelling framework

        4. Modelling real data (CTP) in the PTF modelling framework

          5. TG CS5: heteroscedasticity and varying parameters

            6. TG ABC: modelling wizard, simulations, and release of capital as profit

              7. Importing of data from other applications and COM Automation

                8. Further PTF Modelling Examples

                  9. Layers and the PALD Module

                    10. Introduction to MPTF

                      11. Clusters and MPTF Concepts

                      12. Capital Management of long tail liabilities

                        13. Solvency II one year risk horizon: SCR, Best Estimate of Liabilities (BEL), Technical Provisions (TP), and Market Value (Risk) Margins (MVM) for the aggregate of long-tail LOBs

                          14. Other applications of the MPTF modelling framework

                            15. The Bootstrap: how it shows the Mack method doesn't work

                              16. Updates from 10.6 to 11

                                11. Clusters and MPTF Concepts

                                11.1 MPTF Clusters Case Study Segments Seg 1, 2, ... 10

                                In this video we demonstrate the method of creating clusters. For this example, we use the composite triangle group: SEGx10 that comprises 10 segments of an LOB.

                                Process correlation between any two members in a cluster is significant whereas inter cluster correlations are insignificant and are accordingly set to zero.

                                There are two main ways of automatically creating clusters. You can retain all significant correlations (which might include some insignificant correlations) or you can remove all insignificant correlations (which may remove some significant correlations).

                                We analyze the scenario with removing all insignificant correlations.

                                Simultaneous, clusters, independent modelling and propagation of an action (add parameter, for example) to a dataset is discussed.

                                We also simulate a composite dataset from the optimal composite model. Trend structures, process variability and forecasts are then compared and are shown to be very similar. That is, the composite simulated dataset and the real composite dataset have similar volatility and correlations.

                                11.2 MPTF Modelling Principles Using 1M 1Mxs1M and 2M

                                In this video we continue with a discussion of the MPTF modelling framework in the context of the CDS 1M 2M 1Mxs1M. Process correlations between these layers are very high.

                                Functionality discussed in this video includes:

                                • Model Templates
                                • Loading models (including related models)
                                • Replicate models
                                • Simultaneous, clusters, independent modelling and testing
                                • Constraints
                                • Optimization buttons
                                • Hetero
                                • Logbook (as per PTF, but with aggregate statistics)

                                MPTF Options in the Modelling preferences are set.

                                The typical example of optimizing a MPTF model for layers is illustrated by example.

                                It is found that the reserve distribution of (limited to) 1M and (limited to) 2M have the same CV!

                                The risk capital as a % of the mean reserve based on VaR or T-VaR is the same for (limited to) 1M and (limited to) 2M.