Portfolio diversification and ALM techniques

7.5.1 Diversification is a core principle of insurance business. The concept is not restricted to insurance risks, but applies to all risks. Portfolio diversification and ALM techniques aim at risk reduction by pooling risks in a balanced way (portfolio diversification) or by neutralising risks through off-setting asset and liability positions (Asset Liability Management techniques).

Portfolio diversification

The diversification principle

7.5.2 Portfolio diversification is the structuring of assets or liabilities in order to reduce the overall variability of net wealth. Diversification techniques can be applied to portfolios of assets or portfolios of liabilities. The key principle of diversification is the pooling of independent risks, and this is a fundamental concept in insurance underwriting. Provided the risks are independent, simultaneous adverse development from multiple risks will not happen systematically, but only by chance.

7.5.3 Portfolio balance is further improved if the individual risks in a portfolio are homogeneous, that is, if the risk characteristics (such as likelihood of loss and potential maximum impact) are not too diverse (for example, a balanced portfolio of motor risks would consist of numerous similar policies of similar monetary limits).

7.5.4 The main obstacles to portfolio diversification are risk peaks and dependence. Risk peaks are individual acceptances or portfolio segments with an exceptionally large potential loss size compared to the rest of the portfolio. For example, the inclusion of motor fleet policies in a portfolio of motor business, or concentration of property risks in a geographical area give rise to peaks. Adverse development of just a small number of risks can cause significant variations in the portfolio results.

7.5.5 Dependence across policies can be due to accumulations of losses arising from single events such as natural perils. For example, widespread flooding or windstorms can have a major impact on a portfolio of risks, even though the component risks are largely independent of one another. In the presence of such dependence and accumulation risk,

an increased number of policies (size-effect) does not necessarily provide improved portfolio diversification⁸⁵.

7.5.6 Dependence can also arise through economic, social and technological trends. This kind of dependence arises from systematic and systemic risks, and cannot be off-set by portfolio diversification. A rise in unemployment, for example, can result in an impact across an entire portfolio. Reinsurance is a key tool in reducing the risks caused by such dependence.

7.5.7 The examples given here are related to insurance underwriting risks but apply equally in respect of other risks, and to assets as well as liabilities.

Active portfolio diversification

7.5.8 Active portfolio diversification requires that the co-variation of risks is distinguished and at least qualitatively known or ideally quantified. Active diversification decisions concentrate on the areas of investments and liabilities.

7.5.9 Investment diversification is achieved by investment in different asset classes and by spreading within individual classes (based on patterns of price movements between equities and bonds, and across different equity sectors, for example).

7.5.10 Often, the diversification of the portfolio of insurance risks is not actively managed, but the underlying diversification effect is assumed to take place, within underwriting policies and guidelines. Active diversification of liabilities is usually achieved in the following ways:

■ by number: in line with the principle of diversification the insurer seeks to increase the number of policies (size effect) in order to spread the total risk over many independent sources. In this way it achieves a reduction of result variability (relative to premium volume). Diversification by numbers cannot be blindly applied (due to the possibility of accumulation and dependence effects);

■ across classes and lines of business: the above diversification by numbers can occur across lines and insurance classes. In this case the homogeneity of risks might not be given, but an additional diversification with respect to class- or line-specific background dependence can be achieved. An example is the diversification of class specific price cycles;

■ geographically: this is most important in the case of natural perils coverage;

■ markets: dependence on economic, social and technological background variables can be diversified (to a degree) by spreading the risk acceptance across diverse markets.

Assessment of portfolio diversification effects

7.5.11 In essence, portfolio diversification through independence is a probabilistic effect and an effective measurement of diversification effects requires probabilistic methods.

85 Both peak risks and accumulation risks are managed with reinsurance protections.

7.5.12 By understanding the general approaches to diversification adopted by an insurer, it is possible to achieve at least a qualitative assessment by the examination of portfolio details such as policy numbers, spread across classes, geography and markets. Exposure control methods can be used to identify peak risks and critical accumulations. Where certain critical scenarios are known and where the impact can be assessed, scenario testing is applicable, but the significance of deterministic approaches is limited in this respect.

7.5.13 The current European solvency methodology gives little consideration to diversification.

The only diversification-related feature is the scaling of factors, which assumes that larger insurers require a smaller capital charge relative to premium. This is in line with the above described size effect. Also, with regard to assets portfolios, there are admissibility rules (which vary between Member States in their degree of complexity), which limit the extent to which exposures to certain asset types, and to certain counterparties, can be used for covering technical provisions.

7.5.14 The importance of diversification was thoroughly discussed during the implementation of the US Risk Based Capital (RBC) methodology for non-life insurance. In that process certain modifications⁸⁶ to the initial proposal were carried out in the attempt to recognise diversification effects:

■ covariance formula: this formula was introduced in order to take the independence of the various RBC risk categories into account (see Appendix 10.1 for details);

■ concentration factors for provisions and underwriting: in order to take diversification in provisions and in loss development into account, the capital charges for provisions and for underwriting are adjusted with a concentration factor. The factor varies between 70% and 100% and is the lower, the more provisions and premium are spread over many classes⁸⁷;

■ bond size adjustment factor: the factor for the capital charge for bonds decreases with an increasing number of issuers⁸⁸, thereby appreciating the diversification of (credit) risk in a large spread across issuers;

■ asset concentration factor: the investments of the company are ordered by size and the capital charge factor for the ten largest investments is doubled, thereby penalising concentration of investment.

7.5.15 The adjustments demonstrate that the US approach gives more consideration to diversification effects than the EU approach does. At the same time it also demonstrates how difficult an appropriate assessment of the diversification effect is (see Appendix 7.1 for details).

86 Reference is made to the NAIC RBC requirements as at their first introduction for non-life insurance in 1994. For a detailed discussion see ‘NAIC Property/Casualty Insurance Company Risk-Based Capital Requirements’ by Sholom Feldblum.

87 The loss concentration factor is 70% + 30% * (provisions in largest line of business) / (total provisions for all lines). The premium concentration factor is of similar design: 70% + 30% * (premium in largest line of business) / (premium from all lines of business).

88 The adjustment factor is calculated as a weighted average across numbers of issuers. The following factors are applied: 250% for issues 1 to 50, 130% for issues 51 to 100, 100% for issues 101 to 400 and 90% for issues exceeding 401. The scaled factors are not applied individually to the issues, but a weighted average over the actual number of issues is calculated and applied.

7.5.16 In summary the main point is that a proper assessment of insurance diversification effects requires a detailed portfolio analysis. Not only are probabilistic models required for the analysis, but the predominantly used premium data is not, by itself, sufficient for the task.

The insurance portfolio has to be broken down into segments and information about policy and risk counts, and exposure values and limits needs to be used.

ALM techniques

7.5.17 Asset Liability Management aims at the structuring of assets and liabilities so that the overall variability is reduced through off-setting asset and liability positions. Whereas diversification techniques aim at exploiting averaging effects (the ‘law of large numbers’), ALM techniques are concerned with creating positions between assets and liabilities which off-set each other’s development not only by chance, but by design.

Common ALM techniques

7.5.18 ALM techniques for insurance were first used in life insurance. Life insurance liabilities typically create foreseeable cash flow requirements and the dependence on economic and financial market performance is more pronounced than in non-life insurance. Prudent planning leads to asset strategies that should ensure the financing of the obligations and an immunisation of the variation of liabilities due to financial market variations.

Techniques include:

■ cash flow matching: this is the most rigid ALM technique. The cash out-flows from the liabilities are evaluated on a deterministic basis and asset positions are built that provide a secured cash in-flow that matches the out-flow one to one;

■ duration matching: instead of matching liabilities one to one, duration matching estimates the sensitivity of the liabilities to interest rate movements and builds investment portfolios of similar sensitivity in order to off-set the liability value variation caused by interest rate movements. Duration matching is much less rigid than cash flow matching. Duration measures only the local sensitivity to interest changes, and although small interest rate changes are off-set, large shifts might cause a mismatch of asset and liability variation;

■ matching the dependence on equity performance (profits): liabilities of with-profits policies are dependent on an underlying investment return, however the return to policyholders is smoothed relative to the actual underlying investment returns.

Therefore, the assets and liabilities are in general not completely matched unless financing arrangements for the smoothing functionality are put into place;

■ asset allocation rules: are related to diversification techniques. Assets and liabilities are jointly evaluated in a probabilistic model. The aim is to find an asset allocation rule that provides enough liquidity to meet the liabilities on average, but which does not have to meet them in each and every case (a certain degree of mismatching risk is accepted). The motivation for such ALM approaches is the observation that very rigid matching requires investment in low risk, low return securities. More aggressive investment might take the risk of mismatching into account, but will on average create higher returns, providing the liquidity needed to meet the liabilities without having to match the assets and the liabilities one to one. The probability of mismatching and the acceptance level have to be carefully considered;

■ derivatives: for portfolio segments, which guarantee a minimum return to the policyholder, interest rate derivatives are used to secure the guarantee and to allow for an investment policy, which would not provide an exact match without the hedge position. Currency derivatives are applied to ensure that liabilities in foreign currencies can be met at a foreseeable rate;

■ Dynamic financial analysis (DFA) based techniques: with the advent of probabilistic DFA models, ALM often covers a wider range of techniques. It encompasses the joint, model-based determination of assets, liabilities, supporting reinsurance and hedges, including the consideration of diversification effects.

7.5.19 The cash flow requirements created by non-life insurance liabilities are less foreseeable and the dependence on economic and financial market performance is less pronounced than in life insurance. The application of specific (micro) ALM techniques is therefore less common in non-life insurance.

7.5.20 Further ALM techniques deal with inflation and currency risk:

■ inflation is seen as the major link between non-life liabilities and assets. A common strategy is to off-set the inflation of liabilities with equity investments;

■ currency exposures can emanate from claims provisions or from future claims.

Provisions can be matched by investments in the respective currency. For future claims the earned premium is sometimes taken as a proxy and the premiums are invested in their respective currencies (only in the case of balanced liability portfolios will this yield a satisfactory match; in the presence of high volatility, such as that caused by catastrophe exposure, the loss to premium ratio can become very large).

Assessment of ALM effects

7.5.21 For life insurance the assessment of ALM effects can be achieved on a deterministic scenario basis. The scenarios consist of specific asset value movements (for example, interest rate, equity and property) and the corresponding liability values are then established for every scenario separately. This evaluation has to consider mortality rates and lapse rates and is ideally done on a policy by policy basis.

7.5.22 Where the liability evaluation per scenario can be automated with a model, probabilistic analysis can be applied. Probabilistic analysis of the total asset and liability portfolio is not common, but individual classes and products are analysed in this way (for example, probabilistic analysis of the funding costs for with-profit products or of the interest rate sensitivity of the annuities portfolio).

7.5.23 The assessment of asset allocation rules and DFA-based techniques in life and non-life insurance requires a probabilistic model of the total assets and liabilities. Currency exposures can be assessed (to a degree) from the values of provisions in life and non-life business, and from earned premium amounts in non-life business.

7.5.24 Assessment of inflation exposure requires a detailed analysis of provisions and loss development assumptions for new losses. The assessment of the interaction of inflation and asset values requires the application of advanced economic/asset models.

7.5.25 The degree of sophistication in ALM techniques is highly variable. As indicated, advanced techniques tend to be found mainly among the largest and more sophisticated life insurance undertakings. In general, such techniques are less well developed in the insurance industry than in the banking industry, perhaps due to the fact that the concept of

‘value at risk’ is more familiar in banking. Advanced techniques require significant investment in management information and modelling techniques, but they bring significant benefits to the businesses which invest in them.

7.5.26 It is rarely possible to achieve precise matching of assets and liabilities for several reasons. Liability duration in respect of life insurance in particular may be long, especially where a guaranteed benefit is contingent on payment of further regular premiums or where the liability is in respect of distant retirement benefits. For such long duration liabilities, there may be no replicating asset. The recent decrease in government debt as a proportion of national income in several countries also has obliged life insurers to rely on more risky corporate securities or on risky assets such as real estate to 'match' long liabilities.

7.5.27 A further difficulty is that assets and liabilities are not necessarily stable, and may behave in unexpected ways in critical situations, as was evidenced particularly in the case of Long Term Capital Management (LTCM)⁸⁹. There is the potential for liquidity to alter dramatically, or for the profile of liabilities to be changed by patterns of policyholder behaviour. There may also be scope for conflict between approaches to asset liability management in that, for example the hedging of economic value and of the disclosed balance sheet position may require different approaches. The significance of this last point would be less in a fair value accounting context which would highlight the effects of any mismatches.

Impact of ALM/portfolio diversification techniques on supervisory systems

7.5.28 Under most current supervisory regimes the effects of ALM and portfolio diversification are not explicitly recognised. As described above, diversification and asset liability management have a very significant impact on the financial position of an insurer. Most regimes do not recognise this in the capital requirements and the supervision of these aspects is generally done on a qualitative basis.

7.5.29 Portfolio diversification is not recognised in simple fixed ratio approaches such as the current EU regime. Factor-based RBC approaches try to rectify this, but such approaches are not well suited to taking diversification effects into account.

7.5.30 ALM effects are also not captured with fixed ratio or factor-based RBC. The UK and the USA apply some scenario testing for life companies. This is a suitable instrument for stress testing the asset and liability match. The calculation of the financial position under a given scenario takes the impact on assets and liabilities and the effect of derivatives into account. The effectiveness of such tests depends on the choice and definition of the scenarios, as well as on a prudent calculation of the scenario results. The calculation is not formally prescribed. This enables the companies to tailor the calculation to meet their

89 LTCM is the company that failed in 1998. See ‘Risk Management Lessons from Long Term Capital Management’ by Philippe Jorion, University of California at Irvine; National Bureau of Economic Research (NBER).

own specific risk profile, but it also raises the requirement for a supervisory assessment of such calculations.

Supervisory techniques for taking account of ALM/portfolio diversification

7.5.31 The effects of ALM and portfolio diversification can be quantified, but this requires the application of advanced models. The incorporation of internal models into a supervisory regime would allow ALM and portfolio diversification to be recognised in the capital requirements.

7.5.32 Scenario testing can be a suitable instrument for the ALM assessment. Scenario approaches are currently only applied in some countries as a supplementary technique for life insurance. Suitable tests for non-life insurance can be designed as well. The implementation of scenario tests for non-life insurance is on the agenda of the FSA in the UK. In addition to scenario tests, advanced probabilistic approaches can give further information. Whereas scenario tests are useful for the identification of asset liability mismatches, advanced probabilistic models can evaluate how this mismatch affects the aggregate position.

7.5.33 The use of scenario tests to assess portfolio diversification is not a straightforward solution. Tests that would adequately assess diversification would require a large number of scenarios and the scenarios would have to be very carefully constructed. In essence portfolio diversification is a probabilistic feature and advanced probabilistic models are required for an adequate assessment.

7.6 Conclusions

7.6.1 Insurance undertakings are increasingly using various complex products and techniques to manage and control risks. In the area of ART, there can be significant financial impacts, which can be difficult to assess unless accounting treatments are appropriate and disclosures are sufficient. In the area of ALM and portfolio diversification and derivatives, there is a need to consider these techniques in conjunction with an undertaking’s risk management approach; where techniques are properly controlled they can be valuable tools in the mitigation of the risks they are designed to address.

7.6.2 Financial reinsurance transactions represent a significant challenge to supervisors. The current European solvency system generally does not cope well with such products and techniques, which in many cases did not exist when the system was first devised.

Supervisory authorities have generally recognised that financial reinsurance transactions are capable of undermining the solvency requirements. The accounting treatment of such arrangements is important, and an assessment of the impact on the financial position of an insurer is usually possible in those states which have accounting rules in place to ensure

Supervisory authorities have generally recognised that financial reinsurance transactions are capable of undermining the solvency requirements. The accounting treatment of such arrangements is important, and an assessment of the impact on the financial position of an insurer is usually possible in those states which have accounting rules in place to ensure