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™ 10.3 and modelling modules
2. Modelling using the Link Ratio Techniques and Extended Link Ratio Family modules
3. Introduction to the Probabilistic Trend Family modelling framework
4. Modelling real data (CTP) in the PTF modelling framework
8. Further PTF Modelling Examples
10. Uneven Sampling periods, updating, and various other topics
13. Capital Management of long tail liabilities
- 13.1 Common drivers and Process Correlation
- 13.2 Design of Composite Model from individual PTF models
- 13.3 LOB WC versus the aggregate of all LOBs and simulation from the composite model
- 13.4 Review of the output created by a composite model and a simulation
13. Capital Management of long tail liabilities
This chapter discusses and demonstrates using real data the capital management of long tail lines of business.
Subsequent to working through the capital management training videos
it may prove useful to view the Chapter 4. "Capital Management
of all long tail liabilities" section (click
here) where different companies are compared using Schedule P 2006
data.
No two companies are the same in respect of volatility for the same LOB nor are they the same in respect of correlations between LOBs.
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 risk.
One double click loads the composite model and reveals pictorially the volatility structure of each long tail LOB and their inter-relationships (correlation structures). All the critical financial information including VaR, T-VaR and Cost of Capital are computed in a matter of seconds. A company-wide report is created effortlessly with a single report template.
13.1 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.
The video "Common drivers and Process Correlation Credibility Modelling" is viewable here (10 minutes).
13.2 Design of Composite Model from individual PTF models
A composite model is designed for the long tail LOBs starting with the (PTF) model for each line for Company Z. Clusters are identified based on the process correlations.
Composite forecast scenarios going forward are created from the individual LOB PTF forecast scenarios. The CV of the aggregate is smaller than the CVs for most of the individual lines. Risk Capital allocation by LOB and calendar year is based on a variance/covariance formula.
The composite model is also used to compute ultimate cost distributions for the next underwriting year for the aggregate of all the LOBs, by LOB and by calendar year. It is shown that the combined reserve and underwriting risk is less than the sum of the reserve risk and the underwriting risk.
A report is generated in Excel 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.
The video "Design of Composite Model from individual PTF models" is viewable here (20 minutes).
13.3 LOB WC versus the aggregate of all LOBs and simulation from the composite model
The LOB WC has a large CV and if this were the only line written by Company Z it would require a large amount of risk capital. Company Z affords substantial risk diversification credit as a result of the reserve distributions exhibiting essentially zero correlations.
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.
The video "LOB WC versus the aggregate of all LOBs and simulation from the composite model" is viewable here (20 minutes).
13.4 Review of the output created by a composite model and a simulation
There is much output created by a composite model that includes (i) liability streams by calendar year for the aggregate of all LOBs and each LOB, (ii) Reserve distribution correlations, (iii) Risk Capital allocation by calendar year for the aggregate of all LOBs, and each LOB, (iv) Risk Capital allocation by LOB and (v) VaR tables.
A composite dataset is simulated from the composite model fitted to all the 15 LOBs. We find that the simulated composite dataset is ‘indistinguishable’ in respect of trend structures and process variabilities.
The video "Review of the output created by a composite model and a simulation" is viewable here (8 minutes).
