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

                                10. Introduction to MPTF

                                10.1 LOB 1 and LOB 3 (part 1)

                                In this video we introduce the MPTF (Multiple PTF) modelling framework. This modelling framework has a number of applications including:

                                • Multiple lines of business - diversification and a company wide picture
                                • Multiple segments
                                • Layers
                                • Credibility modelling
                                • Splitting triangles: change of mix of business or change in trend (or process variance) structure.

                                A single composite model can be designed for multiple LOBs that measures the volatility in each LOB (trend structure plus process variance(s)) and the different types of correlations between them. Output includes capital allocation by LOB and calendar year based on selected VaRs and T-VaRs. See video chapter 12.3

                                The concepts of correlations and linearity are clarified. These concepts are fundamental to the MPTF modelling framework. Some misconceptions about correlations are discussed.

                                The identified PTF models for two TGs LOB 1 and LOB 3 are run and discussed.

                                10.2 LOB 1 and LOB 3 (part 2)

                                In this second part of the introduction to the MPTF modelling framework we begin by creating a composite triangle group (CTG) of the basic TGs, LOB 1 and LOB 3, as discussed in the previous training video. The objects contained in CTG are detailed.

                                The starting point for the MPTF modelling framework is the identified PTF model for each LOB. These are found under the related button in the CTG Models tab and can be loaded directly into MPTF.

                                New buttons covered include:

                                • Oc - Optimisation of Residual Correlations
                                • Co - Correlations and Covariances
                                • Oi - Optimisation (individual dataset) one step
                                • OOi - Optimisation (individual dataset) complete

                                The relationship between parameter correlation and future forecast scenarios is illustrated. The removal of parameter constraints between datasets is explained.

                                The forecast scenario summary information is presented.

                                The variance Capital allocation formula is shown along with the corresponding output in the forecast summary tab.

                                The PALD simulations for the aggregate loss distributions are compared with zero correlation (assuming independence between lines) and the model including correlations (optimal). In this scenario the two lines are highly correlated, including in the reserve correlation, and there is no credit for diversification - a much greater capital risk charge is required due to the reserve correlation.

                                10.3 LOB 1 and LOB 3 (part 3) (*)

                                The information in the forecast tables (F button) for the aggregate of the two LOBs, and the forecast summary (FS button) tables is illustrated.

                                The PALD simulations for the aggregate loss distributions are compared with zero correlation (assuming independence between the two lines) and the model including correlations (optimal). The two lines are highly correlated and there is little credit for risk diversification - a much greater capital risk charge is required due to the reserve distribution correlation.

                                Capital allocation by LOB based on selected VaRs and T-VaRs is also discussed.