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

                                1. Introduction to ICRFS-Plus™ 11

                                1.1 Introduction to ICRFS-Plus 11 and database structures


                                The database functionality and navigation is studied. Data, models and links to reports all reside in one relational database. A database can either be remote (on a server that is shareable) or local. Communication between two databases has the same intuitive feel as using Windows Explorer for communicating between two sub-folders. The objects in the database are Triangle Groups (TG) and Composite Triangle Groups (CTG). TGs (and CTGs) also contain objects, namely, triangles, exposures, premiums, data sets, models and links to reports.


                                This video demonstrates:

                                • database manipulation
                                • database structure
                                • triangle group structure
                                • using variables and values to filter triangle groups
                                • system navigation
                                • creation of new databases and communication between two databases
                                • new triangle types



                                1.2 Overview of ICRFS-Plus 11 Modelling frameworks


                                In this video, a brief overview of the modelling frameworks included in ICRFS-Plus 11 is presented.


                                These frameworks include:

                                • Link Ratio Techniques (LRT) including Bornhuetter-Ferguson
                                • Extended Link Ratio Family (ELRF) as discussed in the paper "Best Estimate for Reserves"
                                • Probabilistic Trend Family (PTF) modelling framework
                                • Multiple Probabilistic Trend Family (MPTF) modelling framework

                                There is a paradigm shift between link ratio techniques (LRT) and the probabilistic modelling frameworks PTF and MPTF. The ELRF modelling framework provides the bridge between the two frameworks.


                                An identified model in the PTF modelling framework gives a succinct description of the volatility in the data. The description of the volatility is represented by four graphs, which tell a story about the data.


                                Benefits of the ICRFS-Plus™ software package include:

                                • A user configured, easily navigated database
                                • The database is a repository for the data, models, and forecast scenarios
                                • Uneven sampling periods: for example, Accident year reserves versus quarterly evaluations.
                                • Models are saved in the triangle groups
                                • Monitoring and updating every review period is a seamless operation
                                • Diagnostics for existing link ratio methods
                                • Pricing both retrospective and prospective reinsurance structures
                                • Pricing for different limits for different years
                                • Future accident (underwriting) period segmentation pricing
                                • Understandable probabilistic models summarised by four interrelated pictures.
                                • Correlations (all three types: process, parameter, and reserve) and trends are measured from the data.
                                • Economic Capital: risk charges for combined reserve and underwriting risks. (Note there is usually additional diversification credit obtained for the combined risk charge on reserves and underwriting).
                                • Modelling wizard
                                • Reinsurance evaluation

                                Modelling multiple triangles simultaneously in the MPTF module has additional applications and benefits including risk diversification analysis, capital allocation analysis, credibility modelling, and many other applications as seen in subsequent chapters.




                                1.3 Uncertainty and Variability


                                Variability and uncertainty are two distinct concepts and cannot be used interchangeably. Variability is an observed phenomenon that is to be measured and where appropriate explained. Uncertainty, on the other hand, refers to knowledge about variability.


                                This is easiest to explain by way of example. We demonstrate by comparing two games of chance where the parameters of the games are known. In this case, we have no uncertainty in our knowledge about either game. We 'know' the mean, standard deviation, and indeed the probabilities of all the outcomes.


                                Parameter uncertainty leads to uncertainty in the variability of the process- our knowledge about the variability is uncertain. The inherent variability (process variance) cannot be reduced.




                                1.4 Manual creation of Triangle Groups


                                In this video, manual creation of a triangle group is illustrated. Although triangle groups are usually created via an importing macro, it can be useful to create triangle groups and triangle manually for small projects.


                                Creating triangle types and triangles are also demonstrated along with transferring data and models between similarly sized triangle groups.