Financial Condition Reporting Recalibration Project

Transcription

1 Financial Condition Reporting for South African Short Term Insurers Recalibration Project December 2009 December 2009

2 Contents 1 Executive Summary Introduction Results Conclusion Introduction Scope Approach adopted Limitations Changes to framework Discounted reserves Diversification and correlation calculation Investment and expense allowance Data provided Data sources Data issues and limitations Points relating to the various analyses performed: Overview of prescribed model Reserves Claims reserves Premium reserves Insurance capital charge Initial framework Gross stand-alone risk capital Net stand-alone capital Allowance for diversification and correlation Allowance for investment returns Revised framework Parameterisation of the simulation model Maximum Event Retention Introduction Data received Framework Asset capital charge Credit risk capital charge Operational risk Solvency Capital Required Combine capital charges Innovation Group - Page i

3 26. Covariance effects and Grossing-up Worked example Reserves Insurance capital charge Asset capital charge Combining the insurance capital charge and the asset capital charge Discussion of results Recalibrated capital grids Recalibration of the reserving parameters Changes made to framework Impact of allowing for MER Summary of results Conclusion and recommendations Appendices Glossary of Terms Appendix A: ULR comparison initial calibration (2005) and the recalibration Appendix B: Means and Standard Deviations of ULR s Appendix C: Reserving Ratios per Class of Business Appendix D: CV of Reserving Ratio vs Gross Reserves Appendix E: Discount factor for IBNR Appendix F: Gross Stand-alone Capital Grids - Graphs Appendix G: Capital Grids comparison of initial calibration (2005) and the recalibration Appendix H: Gross Stand-alone Capital Grids Tables 99.5% sufficiency Appendix I: Gross Stand-alone Capital Grids Tables 99.0% sufficiency Appendix J: Gross Stand-alone Capital Grids Tables 98.0% sufficiency Appendix K: Gross Stand-alone Capital Grids expressed as a percentage of Gross Written Premiums Tables 99.5% sufficiency Appendix L: Gross Stand-alone Capital Grids expressed as a percentage of Gross Written Premiums Tables 99.0% sufficiency Appendix M: Gross Stand-alone Capital Grids expressed as a percentage of Gross Written Premiums Tables 98.0% sufficiency Innovation Group - Page ii

4 1 Executive Summary 1. Introduction The Financial Services Board ( FSB ) has requested Actuarial & Insurance Solutions at Deloitte & Touche ( Deloitte ) to recalibrate, for the Short Term Insurance Industry of South Africa, the Financial Condition Report ( FCR ) prescribed method of capital calculation previously developed by Deloitte. The project involved the following three main parts: Simplify the framework to enable easier application & recalibration Recalibrate the framework to include the latest data, ensuring sensible overall levels of results Introduce additional features/aspects to the framework This calibration focussed specifically on the typical insurers and excluded data from Reinsurers, Captive and Cell-captives. The decision remains with the FSB on how to apply the results of the calibration to non-typical insurers. This document only serves as an update to the initial calibration process. Hence, certain sections of the report are not as comprehensive as in the report for the initial calibration. For this reason this report should be read in conjunction with the initial report. Broadly, the aim of the FCR prescribed method of capital calculation is a formula, which would be an appropriate basis for a solvency requirement for the industry, for those companies that choose not to use an approved Internal Model. The calibration of the formula is carried out using data from STAR Returns and Dynamic Financial Analysis. 2. Results In general the recalibration of and the changes made to the prescribed model resulted in a reduction of the capital adequacy requirement. The table below shows a summary of the results split by the different types of insurers. As mentioned earlier, the data for Reinsurers, Captive and Cell Captive insurers were not included in the calibration. The solvency capital requirement was, however, calculated for all insurers by applying the calibrated parameters. Financial Services Board - Page 1

5 3. Conclusion The existing FCR framework has been updated to include the more recent data collected since the previous calibration, but also to incorporate specific adjustments and enhancements to the existing methodologies. The main areas of the recalibration can therefore be summarised as follows: Area of change Incorporation of recent STAR return data Exclusion of Reinsurers, Cells & Captives Discounting of reserves Simplification of diversification & correlation allowance Removal of investment return and expense allowance in NSC calculation Introduction of credit risk Overall impact Removal of approximate non-proportional reinsurance allowance through premiums Allowance for non non-proportional reinsurance through MER Operational risk A minimum level of capital based on 13 weeks of operating expenses Impact of change (where possible to tell) Reduction in reserves & capital Reduction in reserves Reduction in capital requirement Reduction in capital requirement Increase in capital requirement Reduction Not modelled explicitly. However, we expect a reduction in capital requirement for companies with sound non-proportional reinsurance protection. Not tested Not tested due to lack of useable data Financial Services Board - Page 2

6 The impact of the recalibration exercise is illustrated below: For the industry as a whole, the changes are as follows: Financial Services Board - Page 3

7 Note: Financial Condition Reporting Recalibration Project - While the recalibration exercise was performed only for typical insurers (i.e. excluding Reinsurers, Captives & Cells), the derived framework has been applied to all insurers to derive the results in this report. - The results shown do not include any allowance for the impact of an MER-based non-proportional reinsurance approach - The results do not include any allowance for Operational risk - The results do not include a minimum level of capital based on operating expenses The exact form and application of the MER allowance is yet to be decided by the FSB. This may involve a reduction in the stand-alone capital requirements, with an addition for the net effect of MER. This could be achieved by modelling stand-alone capital with various reductions in risk volatility, and then testing the impact of adding estimated levels of MER. We recommend that this be undertaken as an explicit exercise and that it be done in close consultation with the members of the Solvency Assessment Management (SAM) task groups. The FSB may wish to undertake impact studies for MER allowance in the form of industry feedback sessions, or quizzes, similar to what has been done with the development of the Solvency II framework in the EU. Certain aspects of the exercise also depend on information required directly from companies, such as reinsurer and assets credit ratings, operational expenses and MER estimates. We note that the information received in this regard was generally of a poor quality and it did not always allow the reliable testing and inference of results. FSB may also wish to investigate whether the capital grids (expressed as percentage capital requirements based on premium) could be replaced with linear curves fitted through the various points. In aggregate, the recalibration exercise has led to a reduction in the capital requirements of Short Term insurers. The final impact may well depend on the extent of further developments to the framework, as decided upon by the FSB (with input from SAM task groups). Please note that a number of limitations apply to this report. These have been set out earlier in this document and apply to all results contained within this report. It has been a pleasure working on this project and we would like to thank the FSB for the cooperation and assistance received throughout. Financial Services Board - Page 4

8 2 Introduction 4. Scope The Financial Services Board ( FSB ) has requested Actuarial & Insurance Solutions at Deloitte & Touche ( Deloitte ) to recalibrate, for the Short Term Insurance Industry of South Africa, the Financial Condition Report ( FCR ) prescribed method of capital calculation previously developed by Deloitte. The project involved the following three main parts: Simplify the framework to enable easier application & recalibration Recalibrate the framework to include the latest data, ensuring sensible overall levels of results Introduce additional features/aspects to the framework This document only serves as an update to the initial calibration process. Hence, certain sections of the report are not as comprehensive as in the report for the initial calibration. For this reason this report should be read in conjunction with the initial report. 5. Approach adopted Broadly, the aim of the FCR prescribed method of capital calculation is a formula, which would be an appropriate basis for a solvency requirement for the industry, for those companies that choose not to use an approved Internal Model. The calibration of the formula is carried out using data from STAR Returns and Dynamic Financial Analysis. The application of a central formula to the Short Term Industry as a whole inevitably lead to situations where the formula does not fit individual companies with specific circumstances. To limit this shortcoming it was decided, after discussions with the FSB, that the data for Reinsurers, Captive and Cell Captive insurers should be removed from the recalibration exercise. The FSB will at a later stage decide on the framework to be applied to these insurers. Therefore this recalibration can be said to be for typical insurers only. Even though the data for these insurers were removed, the impact of the recalibration was considered for all insurers (i.e. the results shown in the report include results for Reinsurers, Captive and Cell Captive). A number of technical discussions were also held with a special FCR sub-committee established by the FSB. These discussions yielded various input and views on possible solutions. 6. Limitations This report is produced on instruction of and for the purposes of the Financial Services Board. It is based on data and information provided to us, which, although we checked and cleansed such information as far as possible, we cannot guarantee the accuracy of. The approach taken in this report is for the purposes of an industry calibration, and should be interpreted in the context of an industry-wide regulatory framework. We make no guarantees on the effectiveness of this framework applied to a particular company or a group of companies and we accept no responsibility for the solvency of one or more companies in the industry where this framework is applied, as solvency can be impacted by many other factors that cannot be taken into account in an industry solvency capital requirement (SCR), such as inappropriate management action, etc. We do not accept responsibility for the application of the concepts explained here to a specific company and recommend that professional advice be obtained if a company wishes to determine an appropriate level of risk-based capital. Financial Services Board - Page 5

9 The scope of this report is limited to an industry calibration for Financial Condition Reporting purposes. Further, at several stages of the project we were faced with inadequate data that prevented us from refining our calibration of the model. We therefore make some comments on areas where it may be appropriate to collect more data in STAR returns. This report represents our recommendations to the FSB and does not necessarily represent the final format and way in which the solvency capital requirement will be implemented in practice. It is beyond the scope of this report to consider other factors that may impact on the format in which the FSB finally decides to implement an industry calibration, such as Black Economic Empowerment within the industry. As discussed above, the FSB may well allow a company to meet solvency capital requirements under a special dispensation. Financial Services Board - Page 6

10 3 Changes to framework After various discussions the Sub-Committee determined a number of changes to the prescribed method that should be investigated. These changes are discussed in detail below. 7. Discounted reserves Due to significant changes in accounting principles, the FSB requested that the model should be able to allow for outstanding claims reserves to be discounted. This feature of the model will not necessarily be implemented, but was merely developed should it be needed in the future. Each individual company will be responsible for determining their own best estimate reserve for outstanding reported claims, and so the FSB decided that these reserves would not be subjected to discounting. The IBNR best estimate reserves are calculated by the prescribed model and a discount factor was calibrated, based on the estimated timing of the reserve run-off. IBNR reserves are obtained by multiplying earned premium by an appropriate percentage varying by class and development year. The discounted IBNR reserves are obtained in a similar manner by multiplying earned premium by an appropriate percentage, which is adjusted with a factor to allow for discounting. The derivation of the adjustment factor is shown in the Appendices. 8. Diversification and correlation calculation The diversification and correlation allowance applied to the total net stand-alone capital in determining the insurance capital charge is a complex calculation. It was decided that this should be simplified by changing the calculation to applying a heuristic approach (i.e. square root of the sum of squares, applied to the net stand-alone capital of each business class). 9. Investment and expense allowance The original approach was for companies to take into account investment return, over the coming financial year, on all assets backing the premiums liabilities (unearned premium reserve, unexpired risk reserve) and claims liabilities (outstanding reported claims reserve and incurred but not reported claims reserve). The net capital required was reduced by this estimate of investment returns. In the event of a worst-case insurance loss the company will also incur expenses in the normal course of business. These expenses thus need to be allowed for in the required capital by adding them to the risk capital. In an attempt to simplify the prescribed model these allowances were removed. This change will reduce the solvency capital required to the extent that the expense allowance outweighed the impact of the investment return. Financial Services Board - Page 7

11 4 Data provided 10. Data sources The main source of information for this exercise was the historic STAR returns of all companies in the short-term insurance industry in South Africa. During the initial calibration the FSB provided us with STAR returns dating back from 1990 to This data has now been augmented with returns from the years 2005, 2006 and The first phase of this project involved extracting the appropriate data from the STAR returns and creating the appropriate data stores for the investigations needed (such as those for underwriting risk and reserving risk). The following additional data, as at 2007 financial year ends, was also requested from all South African short-term insurers: Summarised information regarding Maximum Event Retention (MER) was obtained to investigate alternative ways to allow for non-proportional reinsurance. By requesting this information, the FSB aimed to get a better understanding of the likely maximum claims events to which each insurer is exposed, taking into account concentration of risk and a return period of 1 in 200 years. In addition the mitigating effects of non-proportional reinsurance on such catastrophic claims events is to be considered in making allowance for the impact of non-proportional reinsurance on the solvency capital required of the insurer. Detailed information regarding the credit ratings of insurers assets and reinsurers was requested to make allowance for credit risk. Information regarding operating expenses was requested to consider the impact of including a minimum capital requirement of 13 weeks operating expenses. The FSB provided a definition of operating expenses in its data requirement. Refer to the FSB communication to public officers, dated 1 July Detailed information regarding cash-back bonus reserves within the unearned earned premiums reserves 11. Data issues and limitations Included in the additional returns received were 5 returns that covered irregular financial periods (i.e. not covering 12 months) due to changes in company financial year-ends. These returns were excluded from the exercise. The format of the STAR return changed in 1999, 2006 and A mapping of the different formats was constructed and subsequently allowed for when extracting data from the STAR returns. All returns pre 2006 did not include the insurer number, hence these returns for each insurer had to be linked using the insurer s name. The FSB provided us with a list of company name changes to enable us to do this. For the reasons mentioned earlier the data for Reinsurers, Captive and Cell Captive insurers were removed from the recalibration exercise. 12. Points relating to the various analyses performed: Triangle extraction This exercise highlighted to a great extent where data was unreliable or incomplete. Blank diagonals were often noticed, indicating that companies did not complete a particular development triangle in a particular year. Interpolation and/or extrapolation was applied in certain cases to estimate individual blank cells to avoid losing a significant amount of otherwise valuable data. This exercise of trying to salvage data was of particular importance since the data was generally sparse to begin with. Financial Services Board - Page 8

12 4.1.2 ULR (Ultimate Loss Ratio) analysis While calculating and analysing claims run-off patterns, we found the calculated development factors were very useful in identifying tainted data. Claims were considered in relation to premiums, thus providing a better view of the reasonability of the magnitudes of the recorded claim amounts. Extreme ULR s (e.g. 3000%, -80%) indicated potentially incorrectly recorded earned premiums. Where these were identified the points were excluded from our analyses. Where it was fairly obvious that a data capturing error had been made (e.g. a zero left off the end of a figure), the data was corrected and included in further analyses. Where claims triangles had one or two blanks but otherwise contained reasonable data, linear interpolation was used to estimate the blanks from the surrounding data. This was done so that we were still able to calculate development factors for a company from its data and include the resulting ULR estimates in the subsequent statistical analyses. Where no earned premium data was available, we could not calculate ULR s for the relevant companies. However, where earned premium values were not recorded for a year but a reasonable amount of data existed around the missing value we estimated it by linear interpolation. In doing so we avoided losing potentially valuable data Reserving Risk analyses As with the ULR analyses, further insight into the overall reasonability of the data was obtained by considering the claims development triangles in relation to the OCR and IBNR development triangles. The OCR and IBNR development areas in the STAR returns were often filled out poorly. Cells are often left blank as opposed to explicitly being recorded as being zero. Often it is not clear whether the data is not available or actually zero. Judgement had to be applied on a company-by-company basis to determine which of the above applied IBNR Analysis We extracted the IBNR triangles from the STAR returns for this analysis. In some cases insufficient data existed for the purposes of calculating chain ladder development factors, yet the data was sufficient to calculate at least two years IBNR figures. In these cases industry average development factors (weighted by gross earned premium) were calculated from the reliable data and used to estimate the relevant companies IBNR figures. Financial Services Board - Page 9

13 5 Overview of prescribed model The prescribed model and calibration process can be summarised into four main components: Reserves, Insurance Charge, Asset Charge and Solvency Capital Required (SCR) (see illustration in Figure 1). Each component will be explained in detail below. Solvency Capital requirement Figure 1: Overview of model Financial Services Board - Page 10

14 6 Reserves The prescribed model estimates insurance liabilities (i.e. reserves) that are 75% sufficient, which is achieved by adding a prescribed margin to the best estimates. Solvency Capital Requirement Figure 2: Overview of model - reserves 13. Claims reserves The best estimate of Incurred but not reported claims (IBNR) will be reserved for on the prescribed basis described below. Individual companies will be responsible for determining their own best estimate reserve for outstanding reported claims. The combination of these two best estimate reserves will be scaled-up to obtain an overall claims reserve with a 75% sufficiency level. The difference between the best estimate and 75% level is referred to as the prescribed margin Best estimate IBNR reserves IBNR reserves (gross and net) are obtained by multiplying earned premium (gross and net) by an appropriate percentage varying by class and development year. For this purpose, earned premium for the last six historic years was considered. The following table contains factors for incurred but not reported claims for each development period: Financial Services Board - Page 11

15 Table 1: Percentage of claims outstanding at the end of year Development period 6 refers to reserves for accidents which occurred 6 years ago. Traditional chain ladder methods were used to obtain best estimate IBNR reserves based on the IBNR development triangles filled out by insurers in the STAR returns. These reserves were then expressed as a proportion of earned premium and curves were fitted to the resulting values. One of the changes to the framework was to enable the model to allow for the IBNR reserves to be discounted. This is discussed in detail in section 33. The calibrated discounted mean terms for the IBNR development is shown in the figure below. Similar to the above table development period 6 refers to reserves for accidents which occurred 6 years ago. Figure 3: Discounted Mean Term for IBNR development In determining the discount factor we assumed a risk free rate of 8,58%. This is the mark to market yield of the R203 government bond, as at March 2009, which has a 6 year duration. Financial Services Board - Page 12

16 The table below shows the IBNR factors after allowing for discounting: Table 2: Percentage of claims outstanding at the end of year (allowing for discounting) Best estimate Outstanding reported claims Reserves As stated above, the outstanding reported claims will be estimated by each company on a best estimate basis. For the purposes of our industry impact analysis we have taken the current OCR levels as best estimates of outstanding reported claims. Depending on the prudence included in current reserving practices this may or may not be accurate Prescribed margins The use of prescribed margins aims to yield reserves that have a 75% level of sufficiency. The prescribed margin formula is applied to liabilities calculated on a best estimate basis. It must be noted that all prescribed margins can be offset against the total capital requirements. The best estimate IBNR reserves produced by the factors above are combined with the best estimate OCR reserves and scaled up by the prescribed margin formula to obtain reserves with 75% sufficiency. The prescribed margin formula operates as a function of the gross best estimate claims reserves. The prescribed margin formula has the following functional form for each class of business: PrescibedMargin = a + b(grossclaimsreserves) c The specific parameters used for each class of business are given in the table below. These curves are calculated so as to increase the level of sufficiency of a best estimate reserve to 75%. Table 3: Parameters for prescribed margin on claims reserves Financial Services Board - Page 13

17 14. Premium reserves For premium reserves (UPR, URR, etc) it is felt that the degree of prudence contained using current estimation techniques (365ths method for instance) may be broadly equivalent to that required through the application of prescribed margins. The primary reason for this is that an unearned premium reserve implicitly contains some profit margin. Where a company has specific knowledge that their premiums are inadequate, appropriate prudence would need to be borne in mind when setting an additional unexpired risk reserve. This URR would also form part of the insurance liabilities and would have to be set at a 75% level of sufficiency. Since the calculation of the URR would depend on the context and the specific circumstances of the company, it is not appropriate to prescribe a formula for the URR. For the purposes of our industry impact analysis we have thus assumed that the premium reserves inherently contain a 75% level of sufficiency. Calculation of the prescribed margin for premium reserves is thus used to quantify the credit towards required capital only. The following formula is applied to the net unearned premium reserve to determine the amount of prescribed margins contained therein. UPR _ PM MAX (0;1 a b( GEP) c ) The parameterisation of the above formula varies by class of business as follows: Table 4: Parameters for prescribed margin on premium reserves Financial Services Board - Page 14

18 7 Insurance capital charge 15. Initial framework For the insurance capital charge the two primary data investigations centred on the analysis of claims paid triangles (for the purposes of determining suitable ultimate loss ratios) and reserve run-off triangles (for the purpose of determining reserving uncertainty). Solvency Capital Requirement Figure 4: Overview of model - insurance capital charge The diagram below shows how the insurance capital is built-up from various components. This diagram is best understood from the bottom-up, since each component of risk feeds upwards into the component above it. The workings of the diagram are given below, with more detailed explanations of each component. Kindly note that this diagram sets out the initial framework, the revised framework (i.e. taking into account the required changes) is shown later in the report. Financial Services Board - Page 15

19 Insurance Capital Charge Investment income and capital gains Diversification / Correlation Net stand-alone capital Retention Retention Expenses Expenses Gross stand-alone risk capital Capital Grids GWP GWP GUPR GUPR ACC ENG PROP GTEE LIAB TRANS MISC MOT Figure 5: Build-up of Insurance Capital initial framework 16. Gross stand-alone risk capital This is an estimate of the capital required for pure insurance risks (underwriting and reserving) before allowance for reinsurance and expenses. Stand-alone capital is what an insurer needs to hold without reference to any of the other classes of business being underwritten. The eight business classes as defined in the STAR return are: Accident (ACC) Engineering (ENG) Guarantee (GTEE) Liability (LIAB) Miscellaneous (MISC) Motor (MOT) Property (PROP) Transport (TRA) A class/account with a higher gross written premium and/or gross unearned premium is likely to exhibit lower volatility due to having a greater number of risks on the books. The data suggests that larger accounts tend to exhibit lower volatility and in some cases the larger accounts also exhibited greater pricing power. Financial Services Board - Page 16

20 The following two items are used as a measure of the size of the account: Gross written premium (GWP) Gross unearned premium (GUPR) In essence we are building up the capital required in the coming financial year so we need to consider the specifics of each class of business in the coming financial year. As such, the gross written premium used needs to be an estimate of gross written premium in the coming year. The Gross stand-alone capital is read off the Capital Grid, relating to the specific class of business using the GWP and the GUPR. The capital grids used to determine the Gross Stand-alone Risk Capital represents the underwriting results, at a specific level of sufficiency, from the Dynamic Financial Analysis (DFA) simulations. The Prophet DFA library was used as the DFA engine (also known as the simulation model). Kindly refer to our report on the initial FCR calibration, which sets out the formula and workings of the simulation model. 17. Net stand-alone capital As with gross written premium above, companies will need to consider the specifics of each class of business in the coming financial year. As such, the following estimates need to be made for each class of business: Retention Expenses The retention percentage for the coming financial year can be estimated with reference to the past financial year if the reinsurance strategy for that class has not changed. Where changes in reinsurance strategy are known, they should be taken into account in determining the retention percentage to use. The gross stand-alone risk capital is multiplied by the anticipated retention percentage (considering only proportional reinsurance) in each class of business to give a net stand-alone risk capital. It is important to note that the allowance for reinsurance in the calculation is not ideal, in particular for non-proportional reinsurance. However, we did not have detailed data available in STAR returns for a more in-depth calibration taking into account the type of reinsurance taken out by a company. A more accurate allowance for non-proportional reinsurance is discussed later in this report. In the event of a worst-case insurance loss (as envisaged by the net stand-alone risk capital calculated at this point) the company will also incur expenses in the normal course of business. These expenses thus need to be allowed for in the capital requirements of each class of business by adding them to the net stand-alone risk capital. Companies can use their current level of expenses as an indication of the likely level of expenses in the coming year. Further, should companies feel that their expenses would rise significantly in times of high insurance losses they should estimate their expenses on this basis. Revisions to the allowance for expenses are also discussed later in this report. 18. Allowance for diversification and correlation The total net stand-alone capital above does not take into account the following effects from writing multiple lines of business: Diversification effects due to writing more than one class of business (these will in general reduce the capital required) Correlation effects between the different classes of business (these will in general increase the capital required since classes tend to be positively correlated) If it is expected that the worst-case insurance event will occur at the same time for each class of business then we would hold the sum of the net stand-alone capitals calculated above as insurance capital against such an event. However, the risks in the eight separate classes of business are not perfectly correlated. In the initial calibration we allow for this by multiplying the sum of the net stand-alone Financial Services Board - Page 17

21 capitals by a statistically determined factor that allows for the relative mix of business in each class. In an attempt to simplify the framework, after discussions within the FSB s FCR sub-committee, this was changed to applying a heuristic rule of summing the squares of the two capital charges and taking the square root. 19. Allowance for investment returns The final allowance is for investment returns on assets backing the relevant liabilities. The argument is that even in a worst case scenario, a company will still earn some return on its existing assets, and this can be used to reduce the capital requirement. The default approach is for companies to take into account investment return, over the coming financial year, on all assets backing the premiums liabilities (unearned premium reserve, unexpired risk reserve) and claims liabilities (outstanding reported claims reserve and incurred but not reported claims reserve). The net capital required (after adjustment for correlation and diversification between the classes of business) is reduced by this estimate of investment returns. Kindly refer to our initial calibration report for more detail on the allowance for investment returns. 20. Revised framework In section 3 we discussed the changes to the framework. These include the simplification of the diversification and correlation calculation and the removal of the investment and expense allowance. The allowance for MER and Credit Risk components are also included in the Insurance Capital Charge. These items and how they are combined with the Net Stand-alone Capital are discussed in detail later in the report. Note that the connecting line for MER is a dotted line; this is to point out that the results shown in the report excludes allowance for MER. Insurance Capital Charge Diversification / Correlation MER Credit Risk Charge Diversification / Correlation Net stand-alone capital Retention Retention Gross stand-alone risk capital Capital Grids GWP GWP GUPR GUPR ACC ENG PROP GTEE LIAB TRANS MISC MOT Figure 6: Build-up of Insurance Capital revised framework Financial Services Board - Page 18

22 As discussed above the gross stand-alone capital is read off a Capital Grid, relating to the specific class of business using the GWP and the GUPR. These capital grids can be seen in the in Appendix F. The following graph is an example of the grid for the motor class: Figure 7: Gross Stand-alone Capital Grid Motor The changes in the capital grids are shown in Appendix G. The graph below is an example of how the Gross Stand-alone capital reduced for the motor class: Financial Services Board - Page 19

23 Figure 8: Capital Grids comparison of initial calibration (2005) and the recalibration Motor In an attempt to simplify the framework the possibility of fitting a straight line to the capital grid was investigated. This approach is not feasible, due to the fact that the shape of the curve a straight line significantly over states the capital required for many companies. 21. Parameterisation of the simulation model Within each class of business the framework links the underlying risks to certain observable risk factors. The main risks underlying the insurance capital charge can be labelled as: Underwriting risk Reserving risk Underwriting risk is the risk that premium earned in future periods will be insufficient to cover claims incurred in those periods. Inherently, underwriting risk is forward looking. Reserving risk is the risk that claims incurred in historic periods will be greater than anticipated (and reserved for) in those periods. Inherently, reserving risk is backward looking. Calibrating the uncertainty in both of these risks formed a major part of this exercise and the resulting data analysis is discussed more fully in later sections. We use the results of this analysis to parameterise our simulation model. Financial Services Board - Page 20

24 Underwriting Risk Reserving Risk DFA Engine Simulation Results Figure 9: Simulation model Underwriting risk One of the primary risks faced by insurers is underwriting risk: the risk that premium earned in future periods will be insufficient to cover claims incurred in those periods. We have applied simulated loss ratios to earned premium in our simulation model to take this risk into account. The simulated loss ratios are derived from log-normal distributions specifically parameterised for each class of business and for the account size of the notional company concerned. The starting point of this analysis is the results of the ultimate loss ratio investigation described in the Data section. These results paired each ultimate loss ratio with its corresponding gross earned premium. The results of the ultimate loss ratio investigation can be seen in Appendix A. We have fitted means and standard deviations to this data and the results can be found in Appendix B. The primary patterns emerging from the data are as follows: In general, as gross earned premium increases, the ultimate loss ratio tends to stabilise (and thus exhibit lower volatility). In some classes the average ultimate loss ratio decreases slightly as gross earned premiums increase. This may be indicative in some instances of greater pricing power associated with bigger players in the market and in other instances with an ability to price more accurately for the risk. Appendix B also contains comparisons of the initial calibration and the recalibration results. In general the fitted mean ultimate loss ratios for the current calibration are lower than for the previous calibration. It is also evident that the variance of the ultimate loss ratios for some business classes reduced. This is specifically true for the miscellaneous class. One reason for this is the fact that insurers are starting to split their business between classes more accurately. In the past, many insurers tended to report results were reported under the miscellaneous class incorrectly, resulting in a class of business with very varied results. We then fitted a statistical distribution to the ULR s the lognormal distribution. The parameters used for the log-normal distribution are derived via a method of moments transformation applied to the mean and standard deviation applicable to the particular class and notional company size. Financial Services Board - Page 21

25 It is important to note that the ultimate loss ratios used in the above investigations are all net ultimate loss ratios even though they are paired with gross earned premium. Using net ULR allows for the use of reinsurance and in particular for the use of non-proportional reinsurance. This is because all forms of reinsurance are implicitly shown in the volatility of the net ULR data. In other words, while we did not have sufficient data to explicitly calibrate the model for different reinsurance programmes, we still make an approximate allowance for the use of proportional and non-proportional reinsurance to the extent that its impact on ULR s is contained in the data. As mentioned, this is a less than ideal solution, but the only one available to us given the lack of reinsurance data in STAR returns. A more accurate allowance for non-proportional reinsurance is discussed in more detail later in this report. The following graph shows the mean net ULR level for each class of business versus gross earned premium: Figure 10: Ultimate loss ratio mean The following graph shows the standard deviation of net ULR for each class of business versus gross earned premium: Financial Services Board - Page 22

26 Figure 11: Ultimate loss ratio - standard deviation Financial Services Board - Page 23

27 7.1.2 Reserving risk Another primary insurance risk is reserving risk: the risk that claims incurred in historic periods will be greater than anticipated and reserved for. The purpose of this investigation is to estimate the risk of under-reserving inherent in outstanding claims reserves (OCR). The investigation is based on the claims triangle data extracted in the data section above. In our definition, OCR includes both IBNR and notified but outstanding claims. As in the ULR investigation above we perform our investigations for each class of business since each is likely to have its own inherent volatility. We calculate the following ratio for the purposes of estimating reserving risk: Re serveratio Re serve k 1 Re serve In other words, we compare the reserve set up at the end of a period with the sum of the reserve set up in the following period and the claims paid in the following period. Over a one year period this ratio exhibits perfect reserving (in hindsight) if it is equal to one. If the ratio is greater than one it theoretically exhibits under-reserving and similarly if it is lower than one it theoretically exhibits over-reserving. It is this reserving uncertainty, as measured over a one year time period, that is allowed for in our industry model. The reserving ratio as given above has a highly heterogeneous distribution. This can be seen in the distribution of reserving ratios for each class of business in Appendix C. The following graph is an example of this distribution for the motor class (both the 2005 and current calibration results are shown): Paid k k 1 Figure 12: Distribution of reserving ration - Motor As in the ULR analysis we investigated the possibility that the reserving uncertainty may be linked to the size of the account. In this instance we measured the size of the account by the gross reserve size attaching to each reserving ratio. The resulting scatter-plots can be seen in Appendix D. The uncertainty Financial Services Board - Page 24

28 inherent in reserving exhibits a similar pattern to the ULR investigation in that larger account sizes appear to be associated with less uncertainty. We have fitted a functional form to the coefficient of variation (CV) of the Reserving Ratio as it varies by account size, the results of which can also be seen in Appendix D. The CV is the ratio that the standard deviation of the Reserving Ratio bears to the mean. The following graph is an example of the coefficient of variation and scatter-plot of reserving ratios for the motor class. Note that the coefficient of variation is not a curve of best fit in the graph below, but a separate ratio determined from the underlying data. As with ultimate loss ratios the ratio above is measured on net data. It must also be noted that only net data was available at this level of detail Earnings patterns For the purpose of running the simulation model for each of the notional companies it is necessary to have an estimate of the premium earning pattern for each class of business. The premium earning pattern is the percentage of premium written that is earned in the same financial year in which it is written. This earning pattern is used primarily in two places: It is applied to projected gross written premium to arrive at an estimate of gross earned premium in the year after the valuation date Unearned premium in the most recent year is grossed up by it to estimate written premium in the previous financial year. As explained above, both gross earned premium in the year after the valuation date and written premium in the year prior to the valuation date are used for the calibration. Financial Services Board - Page 25

29 While the earning pattern within a class of business may vary from company to company depending on the nature of the business written, the aim of this investigation is to estimate an industry average for each class. The STAR returns contained information regarding the term of business written for each company where premium is allocated to the following broad categories: Monthly Annual Term (greater than annual) The distribution between these three categories, by class of business, is shown in the graph below: We assigned the following earning patterns to each of these three categories: The weighted average earnings pattern used was obtained by multiplying these earning patterns by the average amounts of business in each category (in each class of business), as obtained from the data. Financial Services Board - Page 26

30 For STAR returns 2005 and earlier the premium data was sufficiently detailed to distinguish between monthly, annual and term (longer than annual) business. For returns from 2006 onwards, it was not possible to separate the annual and term premiums. As a result, an alternative method of splitting the premiums was required. We tested two alternative approaches and explain both below: Initial Method Where the detailed splits were not possible, we assumed the same splits as was derived from data from earlier years. This method is valid to the extent that the distribution between monthly, annual and term business remained stable over time. We had reason to suspect that companies were writing more monthly business and less annual and term business. For this reason, we also derived splits under an alternative method New Method Our departure point was the ratio of unearned premiums to written premiums. This is a high level approximation of the proportion of premiums earned in the year(s) following the underwriting year. One minus this ratio is therefore an approximation of the proportion of premium written which is earned in the year. However, where business is longer than 1 year in duration, one might find that the unearned premium at the end of a year does not stem from the most recent underwriting year, but rather from earlier years. To this extent, one would expect this method to potentially overstate the proportion of unearned premium, and hence understate the earning pattern. This discrepancy should be most pronounced for the longer tailed classes such as guarantee and liability. This can be seen in the graph below. For these classes we used the patterns determined under the initial method. Figure 13: Comparison of methods The resulting earning patterns and a comparison to the previous calibration results are given in the table below: Financial Services Board - Page 27

31 In order to allow for the types of business accurately in future, it will be necessary to collect information on the types of business in more detail going forward. This will allow the correct application of the initial method Claims payment patterns A claims payment pattern for each class of business was derived indirectly through our investigation into ultimate loss ratios (discussed more fully earlier in the Data section). Where company data was not sparse, we used the chain ladder factors derived to augment our industry analysis for that class of business. As discussed earlier, where the data was sparse we used these industry averages to give estimated ultimate loss ratios from claims paid to date, effectively using the Bornhuetter-Ferguson method. The following tables and graphs show the calibration of cumulative as well as incremental claims by development year for each class of business. Financial Services Board - Page 28

32 The factors above were also applied in the calibration of the size of the notional companies. We have already discussed in previous sections how the notional companies are chiefly parameterised by gross written premium and gross unearned premium. Each notional company also needs to have a value for its outstanding claims reserves (outstanding reported and incurred but not reported reserves). In our framework the OCR is a function of the gross unearned premium. Therefore, for each notional company, we determine outstanding claims values through the application of the calibrated earning patterns and claims development patterns. This is done separately for each class of business. Financial Services Board - Page 29

33 8 Maximum Event Retention 22. Introduction In its previously existing form, the FCR prescribed model made appropriate allowance for the effect of proportional reinsurance on solvency capital requirements. However, the allowance for non-proportional reinsurance was not accurate. The effect of non-proportional reinsurance was only seen to the extent that non-proportional reinsurance premiums are a proportion of gross premiums. However, in the event of a catastrophic claim, such as catered for under a 99.5% scenario, the reinsurance recovery proportion is likely to far exceed this. In light of the fact that more explicit allowance for non-proportional reinsurance is being investigated, the approximate allowance therefore has therefore been removed from the calculation framework, leaving only allowance for proportional reinsurance. For this reason, a review of the allowance made for non-proportional reinsurance is required. A number of insurers have commented that, in their opinion, the previously-calibrated overall solvency capital requirement may be too penal for them, since it does not give them credit for significant levels of nonproportional cover. From this, it would appear that some sort of capital relief should be provided to reflect the extent of recovery/protection received from non-proportional reinsurance on a 99.5% claims scenario. In order to consider making such an allowance, the FSB has requested companies to provide MER information. This included maximum event losses as well as the associated proportional and non-proportional reinsurance recoveries. 23. Data received Summarised information regarding Maximum Event Retention (MER) was obtained from 33 insurers to investigate alternative ways to allow for non-proportional reinsurance. By requesting this information, the FSB aimed to get a better understanding of the likely maximum claims events to which each insurer is exposed, taking into account concentration of risk and a return period of 1 in 200 years. In addition the mitigating effects of non-proportional reinsurance on such catastrophic claims events is to be considered in making allowance for the impact of non-proportional reinsurance on the solvency capital requirements of the insurer. 24. Framework Two initial approaches were identified to allow for non-proportional reinsurance using the MER information, each with its own strengths and weaknesses: Approach A The non-proportional claims recovery, as submitted by the company, for a 99.5% type event should be a deduction from the insurer s prescribed overall solvency capital required. It is assumed that the FCR framework includes the solvency capital required for such a claims event, and therefore that the recovery should simply be an offset to the solvency capital required. From the data provided, it is clear that this method will not work as proposed. In some cases the recovery specified by the insurer exceeds the overall prescribed FCR solvency capital required and hence Financial Services Board - Page 30

34 produces anomalous results. The limiting feature here is that the FCR capital is an industry measure and there is not likely to be effective for companies with unique profiles. Alternatively, one may look at the retention proportion in such a claims event, and apply this proportional saving to the solvency capital requirement. This may be more valid, but may still cause massive reductions in capital, where the recovery proportions are almost 100%. It would probably be appropriate to apply the proportion of saving to the net stand-alone capital, and then follow the calculation process through as normal. A key assumption for this method is that the model projects capital which provides against attritional, large and catastrophic claims experience. This is only possible if it has been calibrated on data which includes such claims. It is unlikely that the data is fully representative of catastrophic 1 in 200 year type claims, and this may explain why the capital relief appears overly generous Approach B An alternative approach, similar to that used by APRA in Australia, is to add the MER to the solvency capital requirement. This assumes that the calibration has only been based on attritional claims data and excludes catastrophes. Hence solvency capital does not include an amount for catastrophic claims. The additional amount to be held should the claim net of reinsurance recoveries. This method results in a net increase in the capital a result counter-intuitive to those insurers who had felt that the capital was high since it didn t allow for non-proportional reinsurance appropriately. This is because the data did not explicitly exclude large or catastrophic claims experience Suggested approach After discussions with the FSB and its FCR sub-committee, a simple alternative was suggested to combine the effects of Approach A and Approach B. As, the data used for the calibration process was not modified to strip out catastrophe claims, it would not be appropriate to simply add the MER. However, it is not possible to determine to what extent catastrophic events are actually captured in the data. To artificially remove catastrophe events from the calibration the tail of the distribution could be shortened. This can be achieved by reducing the standard deviations of the ultimate loss ratios. Although this method is approximate and unlikely to be very accurate, it does set the foundation for a possible approach, and allows the FSB to roll out and test a possible solution. Financial Services Board - Page 31

35 9 Asset capital charge Investment risk is confined to the market risk aspect, i.e. the risk that market movements cause a loss in value of the assets held to back liabilities and solvency capital requirements to such an extent that solvency is threatened. Solvency Capital Required Figure 14: Overview of model - Asset Charge The calibrated capital adjustment factors for each asset class should provide protection up to a specified level of confidence but not necessarily against all possible eventualities. The capital adjustment factor is applied to the value of the assets held in that class to arrive at an amount of capital to be held as a charge for investment risk. The aim of the capital adjustment factor is to provide the specified level of protection against loss in market value on only the assets backing the liabilities and other capital elements. The intention is not to protect the free assets that do not cover capital requirements. Therefore the capital adjustment factor only needs to be applied in relation to the assets backing the liabilities and regulatory capital elements. This implies that the assets would have to be allocated to the liabilities and capital elements to decide what assets the capital adjustment factors needs to be applied to. To minimise capital requirements, it is likely that the approach would be to first allocate the asset classes with the lowest capital adjustment factor. A more desirable approach would be to first allocate the assets that match the liabilities by nature, term and currency, but this is likely to produce much the same result given the types of business generally considered here. The capital adjustment factors were not recalibrated. The factors calibrated using The Smith model during the initial calibration are shown below. In our report on the initial calibration, in Appendix G, we include a more detailed description of The Smith Model, and Appendix H shows the allocation of the FSB s asset categories to the modelled asset categories. Financial Services Board - Page 32

36 The calculation of the capital charge on investments is a multi-step process: 1. First, assets have to be matched or allocated to liabilities, starting with current and other liabilities and ending in the assets remaining being allocated to insurance liabilities (claims and premium reserves). 2. Thereafter, the relevant asset charges (as discussed in this section) are applied to the split of assets backing the insurance liabilities. 3. Finally, this asset capital charge is combined with the insurance capital charge of the previous section to allow for covariance effects. This is explained in the following section and involves another set of asset allocations in this instance to match the asset capital charge and insurance capital charge with appropriate assets. As discussed, in order to calculate the investment risk capital charge, assets have to be allocated to back the liabilities. The assets allocated should be the actual assets held by the company and not notional assets as per an investment mandate or other method. When sufficient assets have been allocated to back the full amount of the liabilities, the investment capital charge for each asset class and currency can be calculated by applying the capital factor to the amount of assets. The capital charges for each class of assets are as follows: Financial Services Board - Page 33

37 10 Credit risk capital charge In this section we set out the way in which credit risk is allowed for. The credit risk component takes into account the credit risk (the inability or unwillingness of a counterparty to fully meet its own contractual financial obligations) inherent in various assets held by the insurer. This includes both investment assets and reinsurer assets. Institutions/instruments obtain credit ratings from various professional credit rating agencies. The various agencies do not always use consistent rating categories and the default probability for an international rating is not the same as for a national rating. The table below gives the credit ratings based on the Standard and Poor s equivilent National rating to the Standard and Poor s International, local currency rating. To accommodate different rating categories the categories of three agencies were mapped to ensure they relate to the same level of default risk and hence capital charge. The mapping the rating agencies and are shown below: These credit risk charges are broadly consistent with the charges in the Actuarial Society of South Africa s Professional Guidance Notes 104 (PGN104) for long-term insurers. Where other rating agencies have been used (i.e. not listed above), a factor should be used which corresponds to those listed above. Where there is no rating for an instrument, or the credit counterparty has not been rated, the minimum factor that can be used for unrated exposures is that as for a BB rated instrument (13.6%). This is a minimum, and the credit quality of the counterparty should be considered before applying this minimum. For government debt and debt instruments carrying an explicit South African government guarantee and issued in South African Rand, a charge of 0% is used. For assets with a duration of shorter than 1 year, the charge used is 25% of the charge in the table. This method is consistent with PGN104. Financial Services Board - Page 34

38 The credit risk component is calculated for assets backing technical reserves. The reduction in the reserves due to approved reinsurance must be included as a notional asset in the calculation. The assets to be included are assets held where credit risk is assumed and include, but are not limited to: Bonds and short-term deposits (promissory notes, letters of credit, convertibles, etc) OTC derivative positions (looking at the counterparty of the derivative and the market value of the derivative). This will include swaps, options, forwards, etc. Preference shares (if not allowed for as an equity investment in determining investment capital charge) Policies of insurance and reinsurance Debtors Intermediary balances Credit derivatives Collective investment schemes should be considered on a look through basis to take into account the underlying holdings of each collective investment scheme in which they have invested in order to calculate the credit risk on the underlying instruments. Approximate methods that give reasonable answers may be used where the calculations are too complex. For each credit rating category an associated Probability of Default (PD) is available. If the credit risk factors are to be based only on the PD, this may fail to take into account security measures (i.e. collateral) underlying the assets or potential salvages or recoveries in the event of default. This may be achieved by the application of a Loss Given Default (LGD) factor. However, the LGD will be unique to each insurer s asset portfolio and is virtually impossible to determine accurately at an industry level. The importance or otherwise of the LGD may well depend on the typical nature of assets for Short Term insurers. By ignoring the LGD, one is effectively setting LGD = 100%, thus obtaining a more prudent result. PGN104 does allow the insurer to take credit for collateral that has been posted. Currently the FCR prescribed model does not make allowance for this. Financial Services Board - Page 35

39 11 Operational risk Operational risk is defined as the risk of loss resulting from inadequate or failed internal processes, people and systems, or from external events. The results contain no allowance for operational risk. This will be investigated further by the FSB to ensure that operational risk will be allowed for in a way that is consistent with how long-term insurers allows for it. Financial Services Board - Page 36

40 12 Solvency Capital Required 25. Combine capital charges The credit risk charge is split between the credit risk component for assets backing technical liabilities and the reinsurance assets (i.e. notional assets relating to approved reinsurance used to reduce the liabilities). The credit risk charge component relating to assets backing technical liabilities is combined with the Asset Capital Charge using the heuristic rule of summing the squares of the two capital charges and taking the square root. ACC* = Asset Capital Charge (before allowing for credit risk) ACRC = Asset Credit Risk Charge ACC 2 2 ACC * ACRC The credit risk component relating to the reinsurance assets is combined with the Net Stand-alone Capital, for each class of business, and the MER using the heuristic rule of summing the squares of the two capital charges and taking the square root. ICC* = Insurance Capital Charge (before allowing for MER and credit risk) RCRC = Reinsurance Credit Risk Charge NSC i = Net Stand-alone Capital for business class i ICC* i 2 NSCi ICC ICC * MER RCRC 26. Covariance effects and Grossing-up This section details how the two capital charges are combined. This involves combining the insurance capital charge and the asset capital charge. In combining the capital charges we have allowed for the following: A fall in the value of assets backing the capital requirements The covariance effects (diversification and correlation) between the asset capital charge and the insurance capital charge The former is allowed for by grossing-up both charges by appropriate amounts to allow for a fall in the value of the capital charges. The latter is allowed for using the heuristic rule of summing the squares of the two capital charges and taking the square root (this is less than the sum of the charges and allows for the fact that companies are not likely to experience a worst-case asset event and worst-case insurance event at the same time). The following formulas set out how we envisage all of the above will be achieved in practice: ACC = Asset Capital Charge (includes Asset Credit Risk Charge) ICC = Insurance Capital Charge Financial Services Board - Page 37

41 g1= Grossing-up factor on asset charge g2= Grossing-up factor on insurance charge TCR = Total Capital Required OR = Operational Risk TCR ACC g 1 2 ICC g 2 2 OR The grossing-up factors are calculated via an intermediate calculation described below. This step involves the performance of an asset allocation (after the allocation of assets to current liabilities and reserves) to adjusted values for the asset capital charge and the insurance capital charge. These adjustments are given below and are performed so as not to penalise companies for the composition of elements of their shareholders funds not being used to back their capital requirements: TCR_ADJ = Intermediate total capital required (before grossing-up) ACC_ADJ = Adjusted Asset Capital Charge ICC_ADJ = Adjusted Insurance Capital Charge TCR _ ADJ ACC 2 ICC 2 ACC _ ADJ TCR _ ADJ ACC ACC ICC ICC _ ADJ TCR _ ADJ ICC ACC ICC An asset charge (calculated on the same basis as ACC) is calculated for the allocation of assets to ACC_ADJ and ICC_ADJ. These two charges are the weighted average fall in assets that could result for an appropriate level of sufficiency. c1= asset charge on ACC_ADJ where 0 < c1 < 1 c2= asset charge on ICC_ADJ where 0 < c2 < 1 The resulting grossing-up factors are calculated as follows: g1= 1- c1 where 0 < g1 < 1 g2= 1-0.5*c2 where 0 < g2 < 1 The rationale for the above is that for the asset capital charge, full grossing-up should be allowed for as you will need a grossed-up asset charge in precisely the situation that you need the asset charge itself. The grossing-up of the insurance capital charge only takes half of the appropriate asset charge into account since a worst case insurance event will not always happen at the same time as a worst case asset event. The use of a factor of a half can be seen to be allowing for a 50% correlation between insurance catastrophes and investment market crashes, which is in line with the intended practice in European markets. It is important to note that we envisage that companies will receive a credit towards their total capital requirement equal to their overall prescribed margins (from claim reserves and premium reserves). We expand more on this in the following section. Financial Services Board - Page 38

42 SCR TCR Financial Condition Reporting Recalibration Project PM PM = total prescribed margins SCR = solvency capital requirement Financial Services Board - Page 39

43 13 Worked example In this section the FCR calculation is illustrated by way of a hypothetical example. To simplify the illustration we assume the insurer only writes motor and property business. 27. Reserves The best estimate IBNR reserves, both gross and net, for the motor business are calculated by multiplying the relevant earned premium with the calibrated IBNR percentage. See the table below. The IBNR for the property business is calculated in the same way. The best estimate of OCR is taken as the current outstanding reported claims. These two components make up the claims reserve. The claims prescribed margin factor is calculated by applying the following parameters to the gross claims reserve. The net claims reserves are then multiplied by the factor to determine the claims reserve prescribed margin. Note, that while the margin is a function of the gross reserves, its application is to the net reserves. PrescibedMargin = a + b(grossclaimsreserves) c Financial Services Board - Page 40

44 The following parameters are applied to the gross unearned premium reserve to determine the premium prescribed margin factor. This factor is then applied to the net unearned premium reserve to determine the prescribed margin contained therein. UPR _ PM MAX (0;1 a b( GEP) c ) 28. Insurance capital charge The hypothetical written premium information below relates to the motor business. The user should read the stand-alone capital level from the appropriate capital grid (here we use 99.5% level of sufficiency), by reference to the written and unearned premium levels (the two dimensions of the grid). Because the exact premium numbers will not be reflected on the axes of the grid, the user will need to find the next closest value above and below, on each of the two axes of the grid. The combination of this will mean that 4 possible stand-alone capital levels will be produced, and the user s number will lie somewhere within the ranges denoted by these 4 values. Using the projected premiums from our example and the relevant capital grid (at 99.5% level of sufficiency) it can be seen that the gross stand-alone capital is surrounded by four points with standalone capital levels of R229.76mil, R250.20mil, R379.09mil and R390.75mil. Using bi-linear interpolation on these points the gross stand-alone capital required is determined to be R316.63mil. The bi-linear interpolation formula is technical in nature, and has been built into the FSB STAR return tool. The exact formula is not repeated here for the sake of brevity, but is specified in detail in the original FCR report. The gross stand-alone capital required for the property business is calculated in the same way, but with reference to Property capital grid. The net stand-alone capital is determined by applying the retention ratio (using only proportional reinsurance premiums) to the gross standalone capital. Financial Services Board - Page 41

45 The credit risk charge on reinsurance assets is determined by multiplying the asset with the corresponding charge. In this example we assumed that the term for all reinsurance assets are less then one year. The ICC* is then determined by taking the square root of the sum of the squared net stand-alone capital values across all classes. The insurance capital charge (before gross-up) is subsequently determined by taking the square root of the sum of the squared ICC*, MER and reinsurance credit risk charge. ICC* i 2 NSCi ICC ICC * MER RCRC In our example, we assume that the company has provided an MER value of R25m. Financial Services Board - Page 42

46 29. Asset capital charge The assumed split of the insurer s assets between the relevant asset categories is shown below. Firstly assets need to be allocated to the current liabilities, starting with near cash assets. Subsequently, the remaining assets need to be allocated to the net technical reserves. A charge will be applied to these assets to produce ACC*. The credit risk charge on investment assets is determined by multiplying the asset with the corresponding charge. The asset capital charge (before gross-up) is determined by taking the square root of the sum of the squared ACC* and the asset credit risk charge. ACC 2 ACC * ACRC 2 Financial Services Board - Page 43

47 30. Combining the insurance capital charge and the asset capital charge This section illustrates how the insurance capital charge and the asset capital charge are combined. The intermediate total capital charge (before gross-up) is determined by taking the square root of the sum of the squared insurance capital charge and asset capital charge (allowing for covariance effects but not grossing-up). TCR _ ADJ ACC 2 ICC 2 This leads to the following adjusted capital charges: ACC _ ADJ TCR _ ADJ ACC ACC ICC ICC _ ADJ TCR _ ADJ ICC ACC ICC These adjusted charges are then allocated to the assets remaining after the allocations performed for current liabilities and technical reserves. This asset allocation is performed in a similar manner to those performed for the liabilities. However, in this calculation we also need to allow for the fact that Insurance and Investment events are not always 100% correlated. To do this, we adjust the asset charge underlying the ICC downwards using an approximate correlation factor of 50%. So, we calculate a weighted average charge for each of the ACC and ICC, and convert these into grossing up factors, with the ICC grossing up factor allowing for the correlation effect. TCR ACC g 1 2 ICC g 2 2 OR No operational risk (OR) component has been allowed for in this example. Financial Services Board - Page 44

48 We are now in a position to calculate SCR from the formula in the section above since we know ACC, ICC, g 1 and g 2. The final value of R309.35mil for SCR is obtained as follows: TCR The company will receive a credit towards their total capital required equal to their overall prescribed margins, see table below: Financial Services Board - Page 45

49 14 Discussion of results The impact of the recalibration on the prescribed capital calculation model can be considered in four segments: 1. Impact due to recalibration of the capital grids used in determining the insurance capital charge 2. Impact due to recalibration of the reserving parameters 3. Impact due changes made to the framework 4. Impact of allowing for MER All the results shown below are on a 99.5% level of sufficiency. The results relating to the previous/2005 calibration refer to reserve or solvency capital requirements calculated, as at 2007, using the previous parameters or capital grid. 31. Recalibrated capital grids The capital grids are to determine the Gross Stand-alone Risk Capital and represent the underwriting results, at a specific level of sufficiency, from the DFA simulations. For all business classes the solvency capital requirement reduced, on an overall basis the reduction is roughly 16%. The reduction might be due to a combination of factors: reduced volatility due to the fact that insurers are completing STAR returns more accurately (e.g. allocating business between different classes more accurately), lower mean and/or standard deviation of ultimate loss ratios due to more stable data and/or better underwriting experience. The two classes that were influenced the most are Motor and Property that reduced by nearly 20% and 25% respectively. Figure 15: Change in Gross Stand-alone Capital Financial Services Board - Page 46

50 32. Recalibration of the reserving parameters From Figure 17 is can be seen that the required reserves did not change significantly as a result of recalibrating the parameters. The only component that changed is the prescribed margin, for the premium reserve (UPP), which increased throughout all classes of business. Figure 16: Change in reserves by class of business Figure 17: Change in reserves - Total industry Financial Services Board - Page 47

51 33. Changes made to framework Financial Condition Reporting Recalibration Project Discounted IBNR reserves It should be borne in mind that the final results shown in this report do not allow for IBNR reserves being discounted. The results below are only an indication of the impact on the reserves, should discounting be introduced (as mentioned in a previous section we assumed a discount rate of 8,58%). Figure 18: Impact of discounting IBNR reserves Financial Services Board - Page 48

52 Change diversification and correlation calculation Changing the method of allowing for diversification and correlation between classes of business, results in higher capital requirements. Figure 19: Change in capital due to removing correlation matrix Financial Services Board - Page 49

53 Removing investment and expense allowance In general the expense allowance outweighs the allowance for investment return earned on the assets backing the liabilities. Hence, removing it from the model resulted in lower required capital. Figure 20: Impact of removing investment and expense allowance Financial Services Board - Page 50

54 Adding credit risk component A number of assumptions were needed to determine the impact of allowing for asset credit risk. This is firstly because not all insurers responded to the additional data request from the FSB. Secondly, an assumption was needed to split out government debt instruments. However, the impact of allowing for asset credit risk is less than 0.15%. Figure 21: Impact of asset credit risk Financial Services Board - Page 51

55 34. Impact of allowing for MER In order to test the impact of allowing for the MER component the catastrophe events will need to be artificially removed from the calibration and the DFA model re-run. Due to the fact that a final decision on the approach to be adopted has not been reached this exercise was not done. 35. Summary of results The two graphs below show how the total reserves and solvency capital requirement changed as a result of the recalibration and the changes to the framework of the prescribed model. Figure 22: Total reserves and SCR - by insurer type Financial Services Board - Page 52

56 Figure 23: Total reserves and solvency capital required - Total industry Figure 24 shows that in general the capital adequacy requirement reduced. The graph shows the impact for each company. The solvency capital requirement only increased for five companies (indicated by the red triangles). There is no clear indication that the solvency capital requirement reduction is greater for large or small companies. Figure 24: Capital adequacy requirement Financial Services Board - Page 53

57 The graphs and table below shows that the industry as a whole is solvent under the recalibrated prescribed FCR model, with SCR Cover at 1.1. Considering the solvency position for each type of insurer category it can be seen that Cell Captives and Niche category is insolvent. Figure 25: Total Liabilities vs Total Assets by insurer type Figure 26: Total Liabilities vs Total Assets total industry Financial Services Board - Page 54

58 Table 5: Total Liabilities vs Total Assets Financial Condition Reporting Recalibration Project In general the recalibration of and the changes made to the prescribed model resulted in a reduction of the capital adequacy requirement. The table below shows a summary of the results split by the different types of insurers. Table 6: Summary of Capital Adequacy Requirement Financial Services Board - Page 55

59 15 Conclusion and recommendations The existing FCR framework has been updated to include the more recent data collected since the previous calibration, but also to incorporate specific adjustments and enhancements to the existing methodologies. The main areas of the recalibration can therefore be summarised as follows: Area of change Incorporation of recent STAR return data Exclusion of Reinsurers, Cells & Captives Discounting of reserves Simplification of diversification & correlation allowance Removal of investment return and expense allowance in NSC calculation Introduction of credit risk Overall impact Removal of approximate non-proportional reinsurance allowance through premiums Allowance for non non-proportional reinsurance through MER Operational risk A minimum level of capital based on 13 weeks of operating expenses Impact of change (where possible to tell) Reduction in reserves & capital Reduction in reserves Reduction in capital requirement Reduction in capital requirement Increase in capital requirement Reduction Not modelled explicitly. However, we expect a reduction in capital requirement for companies with sound non-proportional reinsurance protection. Not tested Not tested due to lack of useable data Financial Services Board - Page 56

60 The impact of the recalibration exercise is illustrated below: For the industry as a whole, the changes are as follows: Financial Services Board - Page 57

61 Note: Financial Condition Reporting Recalibration Project - While the recalibration exercise was performed only for typical insurers (i.e. excluding Reinsurers, Captives & Cells), the derived framework has been applied to all insurers to derive the results in this report. - The results shown do not include any allowance for the impact of an MER-based non-proportional reinsurance approach - The results do not include any allowance for Operational risk - The results do not include a minimum level of capital based on operating expenses The exact form and application of the MER allowance is yet to be decided by the FSB. This may involve a reduction in the stand-alone capital requirements, with an addition for the net effect of MER. This could be achieved by modelling stand-alone capital with various reductions in risk volatility, and then testing the impact of adding estimated levels of MER. We recommend that this be undertaken as an explicit exercise and that it be done in close consultation with the members of the Solvency Assessment Management (SAM) task groups. The FSB may wish to undertake impact studies for MER allowance in the form of industry feedback sessions, or quizzes, similar to what has been done with the development of the Solvency II framework in the EU. Certain aspects of the exercise also depend on information required directly from companies, such as reinsurer and assets credit ratings, operational expenses and MER estimates. We note that the information received in this regard was generally of a poor quality and it did not always allow the reliable testing and inference of results. The FSB may also wish to investigate whether the capital grids could be restated as percentage capital requirements based on premium, with linear curves fitted through the various points. In aggregate, the recalibration exercise has led to a reduction in the capital requirements of Short Term insurers. The final impact may well depend on the extent of further developments to the framework, as decided upon by the FSB (with input from SAM task groups). Please note that a number of limitations apply to this report. These have been set out earlier in this document and apply to all results contained within this report. It has been a pleasure working on this project and we would like to thank the FSB for the cooperation and assistance received throughout. A Rayner BSc FIA FASSA Director Actuarial & Insurance Solutions Deloitte & Touche J A van der Merwe, BComm (Hons) FFA FASSA Manager Actuarial & Insurance Solutions Deloitte & Touche February 2009 Financial Services Board - Page 58

62 16 Appendices 36. Glossary of Terms ASSA: Actuarial Society of South Africa AURR: Additional Unexpired Risk Reserve BE: Best Estimate DFA: Dynamic Financial Analysis EP: Earned Premium FCR: Financial Condition Report / Reporting FSB: Financial Services Board GIBNR: Gross IBNR GOCR: Gross OCR GWP: Gross Written Premium GUPR: Gross UPR IBNR: Incurred But Not Reported SCR: Solvency Capital Requirement MER: Maximum Event Retention NIBNR: Net IBNR NOCR: Net OCR NWP: Net Written Premium NUPR: Net UPR OCR: Outstanding Claims Reserves PGN: Professional Guidance Note (of ASSA) PM: Prescribed Method or Prescribed Margin RBC: Risk Based Capital TCR: Total Capital Requirement TSM: The Smith Model ULR: Ultimate Loss Ratio UPR: Unearned Premium Reserve URR: Unexpired Risk Reserve VAR: Value at Risk WP: Written Premium Financial Services Board - Page 59

63 37. Appendix A: ULR comparison initial calibration (2005) and the recalibration Figure 27: ULR's vs Gross Earned Premium for Different Classes of Business Financial Services Board - Page 60

64 Figure 28: ULR's vs Gross Earned Premium for Different Classes of Business Financial Services Board - Page 61

65 Figure 29: ULR's vs Gross Earned Premium for Different Classes of Business Financial Services Board - Page 62

66 Figure 30: ULR's vs Gross Earned Premium for Different Classes of Business Financial Services Board - Page 63

67 Figure 31: ULR's vs Gross Earned Premium for Different Classes of Business Financial Services Board - Page 64

68 Figure 32: ULR's vs Gross Earned Premium for Different Classes of Business Financial Services Board - Page 65

69 Figure 33: ULR's vs Gross Earned Premium for Different Classes of Business Financial Services Board - Page 66

70 Figure 34: ULR's vs Gross Earned Premium for Different Classes of Business Financial Services Board - Page 67

71 38. Appendix B: Means and Standard Deviations of ULR s Financial Condition Reporting Recalibration Project Financial Services Board - Page 68

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87 39. Appendix C: Reserving Ratios per Class of Business Financial Condition Reporting Recalibration Project Financial Services Board - Page 84

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95 40. Appendix D: CV of Reserving Ratio vs Gross Reserves Financial Condition Reporting Recalibration Project Financial Services Board - Page 92

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103 41. Appendix E: Discount factor for IBNR Undiscounted IBNR The model multiplies the earned premiums for each of the last six years by the relevant calibrated percentage (P d ) to obtain the IBNR best estimate. Where: P d = weighted average ratio of IBNR (relating to accident year (t j) and development year d) and Net Earned Premium (relating to year (t j)) W t-j = the weight contribution of Gross Earned Premium of year (t j) = IBNR (relating to accident year (t j) and development year d) as a percentage of Net Earned Premium (relating to year (t j)) Where: = Net Claims Reported as a percentage of Net Earned Premium in development year d for accident year (t j) Hence: Discounted IBNR Where: Since: Financial Services Board - Page 100

104 42. Appendix F: Gross Stand-alone Capital Grids - Graphs Financial Services Board - Page 101