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

ICRFS-Plus™ Demonstration videos and powerpoint slide show



ICRFS-Plus™ is a tour de force of interactive software design and computational speed.

An ICRFS-Plus™ corporate database, which is not difficult to create, enables complete executive oversight. This means that that you will be able to find, with just a few mouse clicks, models and reports for any segment of your business in any country, the actuary modelling that segment of the business, capital allocation by LOB and calendar year, reserve risk charge and underwriting risk charge for the aggregate of LOBs, whether outward reinsurance is effective in respect of reducing retained risk, and more. Creation of an ICRFS-Plus™ database from triangles stored elsewhere or unit record transactional data is also seamless and effortless using COM scripts.


One great benefit of ICRFS-Plus™ is that you can manage and measure all your long tail liability risks with a single composite model. Only one model for each company!


Click here to view an powerpoint presentation overview (about 14Mb) of ICRFS-Plus™


A single composite model measures the reserve, underwriting and combined risks for each LOB and the aggregate.


One double click loads the model and reveals pictorially the volatility structure of each long tail LOB in your company and their inter-relationships (correlation structures). All the critical financial information such as risk capital allocation by LOB and calendar year, and Tail Value-at-Risk for different time horizons can be computed in a matter of seconds. A company-wide report can be created effortlessly with a single report template.


In respect of Solvency II Capital Requirements (SCR), Market Value Margins (Risk Margins) and Technical Provisions (Fair Value of Liabilities), for the aggregate of multiple LOBs, video chapter 5 provides Insureware's solution to the one year risk horizon.


View the videos below to experience the numerous unique benefits and applications afforded by a unique paradigm shift.


Some of the (real) case studies modelled 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.


Table of Contents

1. Introduction to ICRFS-Plus™

    2. Applications of the PTF and ELRF modelling frameworks

      3. The MPTF modelling framework

        4. Capital Management of all long tail liabilities

        5. 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

          6. Reports

            7. Schedule P

              8. Importing data into ICRFS-Plus and COM Automation

                9. Additional applications of ICRFS-Plus™

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


                    4. Capital Management of all long tail LOBs


                    One great benefit of ICRFS-Plus™ is that you can manage and measure all your long tail liability risks with a single composite model. Only one model for each company!


                    A single composite model measures the reserve, underwriting and combined risks for each LOB and the aggregate.


                    One double click loads the model and reveals pictorially the volatility structure of each long tail LOB in your company and their inter-relationships (correlation structures). All the critical financial information such as risk capital allocation by LOB and calendar year, and Tail Value-at-Risk for different time horizons can be computed in a matter of seconds. A company-wide report can be created effortlessly with a single report template.


                    This chapter discusses and demonstrates using real data the capital management of long tail lines of business. The data are extracted from A.M.Best Schedule P 2006 and includes Berkshire Hathaway, The Hartford, SwissRe and others.


                    For the selected companies composite models are designed to measure the volatility within each line and the correlation structure between them. The composite model is used to allocate risk capital by LOB and calendar year, and measure the combined reserve and underwriting risks.


                    4.1 Common drivers and Process Correlation


                    How do we know if two LOBs have common drivers?


                    Gross and net of reinsurance data have very much the same trend structure and high process correlation because they have common drivers (especially in the calendar year direction). This is illustrated with a real life example.


                    However, it is very rare to see two LOBs with similar trend structure or significant process correlation. That is, they do not have common drivers.


                    This video also illustrates that for Berkshire Hathaway the process correlation between LOBs CAL and PPA is zero whereas for Swiss Re the same LOBs is significant (0.53).




                    4.2 Design of a single composite model for Berkshire Hathaway - 15 LOBs (schedule P data)


                    A composite model is designed for all the long tail LOBs of Berkshire Hathaway. The starting point is the optimal model designed (identified) for each LOB in the Probabilistic Trend Family (PTF) modelling framework.


                    Clusters are identified based on process correlations between the LOBs. LOBs belong to the same cluster if the process correlation between them is significant. For members in different clusters the process correlation is insignificant and is, accordingly, set to zero.


                    We find that most LOBs do not have significant process correlation. Moreover, LOBs do not share the same trend structure and process variance. Accordingly they do not have common drivers.


                    The composite model that describes the trend structure and process variance in each LOB pictorially and the process correlations between them produce a wealth of critical information. All this information is conditional on an explicit set of assumptions that are transparent and auditable.


                    Forecasting output includes means and standard deviations for:

                    • Log normal distributions for every projected cell for every LOB
                    • The aggregate of all LOBs for each projected cell
                    • Totals by accident year, calendar year, and the equivalent for the aggregate for each LOB and the aggregate of LOBs

                    The above output is created for the current and prior accident years (reserves), for future underwriting years, and the combined reserve and underwriting year risks. Forecast summaries are also provided.




                    4.3 Berkshire Hathaway (Schedule P data) and allocation of risk capital


                    We continue from the previously designed forecast scenario for Berkshire Hathaway and study the forecast summaries.


                    Forecast summaries include:

                    • Reserve distribution correlations
                    • Risk capital allocation (percentages) by LOB
                    • Payment streams by calendar year for each LOB and the aggregate
                    • Risk capital allocation (percentages) by calendar year for each LOB and the aggregate

                    Risk Capital allocation by LOB and calendar year is based on a variance/covariance formula.


                    Calendar year payment streams are critical for the cost of capital calculations. These payment streams are inseparably related to the interaction between of the development period and calendar period parameters. (An accurate projection of the calendar year streams cannot be obtained in any other way).


                    The volatility of ReA is examined. The process volatility in the past is high so we expect to see the same volatility when we project from the model into the future.


                    Forecast scenarios going forward are adjusted so that estimates of the means of the reserve distributions correspond to reserves held. The CV of the aggregate is smaller than the CVs for most of the individual lines.




                    4.4 VaR, T-VaR, Risk Capital Allocation, and Underwriting risk charge versus Reserve risk charge


                    This video is a continuation from the previous video: Berkshire Hathaway and allocation of risk capital.


                    Since there is no analytical form for the sum of log normals, we simulate from the projected correlated log normals in each cell for each LOB to find the distribution of aggregates.


                    Graphs of risk capital allocation for selected VaRs and T-VaRs are discussed.


                    It is shown that the combined risk charge for reserve and underwriting risk is less than the sum of the individual risk charges.




                    4.5 Berkshire Hathaway LOB ReA versus the aggregate of all LOBs and simulation of a composite dataset from the composite model


                    The LOB ReA has the largest CV and if this were the only line written by Berkshire Hathaway it would require a large amount of risk capital. Berkshire Hathaway affords substantial risk diversification credit as a result of the reserve distributions exhibiting essentially zero correlation.


                    A composite dataset is simulated from the composite model for all the long tail LOBs. It is shown to have the same risk characteristics as the real data.




                    4.6 Comparison of Berkshire Hathaway, Swiss Re and The Hartford (Schedule P data)


                    The risk characteristics of the three companies are compared. The same LOBs have different CVs, different correlations and different capital allocations by calendar year. Capital allocation by LOB is also different. Indeed, even the mean payment streams by calendar year are different.


                    Updating the composite triangle group that includes data, models and forecast scenarios is illustrated.



                    4.7 Excel based Report for Berkshire Hathaway (a Company Wide Report)

                    A report is generated in Excel for Berkshire Hathaway using a report template that exhibits reserve summaries for the aggregate across all LOBs and each LOB by accident year and calendar year. Capital allocation tables and graphs are also given for specific VaR.


                    One great benefit of an ICRFS-Plus database is that all reports are linked to the corresponding triangle groups and accordingly a report can be found with just a few mouse clicks.



                    For additional information on ICRFS-Plus™ features - click here.


                    Solvency II Capital requirements for each LOB and the aggregate of all LOBs are only met by ICRFS-Plus™ in a sound statistical framework.