For professional investors - November WHITE PAPER Determining a strategic asset allocation in a Solvency II framework

Transcription

1 For professional investors - November 2012 WHITE PAPER Determining a strategic asset allocation in a Solvency II framework

2 2 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November 2012 Contents Executive summary 4 1. Foreword: why is it a challenge for an insurer to determine its strategic asset allocation? 6 2. Solvency II: a much more economic approach compared to Solvency I 8 3. Asset classes attractiveness under Solvency II Framework considered for the asset allocation determination Determining an optimal strategic asset allocation (SAA) Discussing possible evolutions based on an insurer s actual situation Moving from a static framework to a dynamic one to generate returns while protecting solvency Conclusion Appendices 38

3 3 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November 2012 About the authors Thomas Heckel is Head of Financial Engineering for Solutions at BNP Paribas Investment Partners in London, UK. thomas.heckel@bnpparibas.com Anton Wouters is Head of LDI & Fiduciary Management at BNP Paribas Investment Partners in Amsterdam, Netherlands. anton.wouters@bnpparibas.com Sophie Debehogne is Investment Specialist in charge of promoting customized and LDI solutions at BNP Paribas Investment Partners in Brussels, Belgium. sophie.debehogne@bnpparibas.com Anne Poirrier-Hamon is Deputy Head of Financial Engineering for Solutions at BNP Paribas Investment Partners in Paris, France. anne.poirrier-hamon@bnpparibas.com Zine Amghar is a quantitative analyst of Financial Engineering for Solutions in Amsterdam, Netherlands. zine.amghar@bnpparibas.com Pierre Moulin is Head of Financial Engineering at BNP Paribas Investment Partners in Paris, France. pierre.moulin@bnpparibas.com

4 4 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November 2012 Executive summary By Thomas Heckel, Anton Wouters, Sophie Debehogne, Anne Poirrier-Hamon, Zine Amghar, Pierre Moulin New regulation under Solvency II is bound to trigger changes to the way insurers will determine their optimal asset allocation and will enhance the benefits brought by risk-mitigating strategies once a strategic asset allocation has been defined. Not all Solvency II parameters have yet been defined, but the preparation for tomorrow s asset allocations and investment approaches is already under way. That is why, as partners to insurance companies, we have over the past two years developed tools and a framework to accompany insurers in their preparations, which we present in this white paper. The mark-to-market approach and the direct link between asset allocation and capital requirements introduced by Solvency II will be pivotal elements in determining asset allocation in the future. We foresee a benefit from diversification and a need to analyse the attractiveness of each asset class in terms of its risk-return profile, beyond pure cost in capital, to ensure one s reasoning is sound. These elements will need to be reconciled with long-standing local accounting principles, which are far from a mark-to-market approach in numerous countries. However, even if specific local rules differ, it will remain generally possible to smooth the P&L that drives profitsharing to policyholders. When determining their asset allocation, insurers are likely to opt for allocations generating a return allowing profit sharing in line with their commercial objective (to limit commercial risk) as well as maximising the Return on Equity for shareholders. On the risk side, two types of risk need to be controlled: the economic risk and the accounting risk. For such an optimisation exercise, we consider the economic risk is best addressed via a 1-year, 99.5% Value at Risk or VaR (1Y; 99.5%) of the surplus of assets relative to liabilities. This is consistent with the market risk Solvency Capital Requirement (SCR) introduced by Solvency II, while providing more granularity in the rating of the underlying investments. Of course, a formal check with respect to the SCR generated by a selected asset allocation must ultimately be done. Indeed, the SCR remains the main risk measure from a solvency point of view. As for the accounting risk, this is well represented by the volatility of the P&L expressed in local GAAP: beyond a certain level, an insurer will encounter difficulties in maintaining a stable P&L in line with commercial objectives, despite the smoothing possibilities. In this paper, our objective is to present the robust and flexible Solvency II framework we have developed, focusing on the first order effects linked to the choice of an asset allocation. That

5 5 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November 2012 is why we here consider a stylised example for a life insurer. In doing so, we make simplified assumptions: a) on its balance sheet structure; b) on the accounting smoothing principles it benefits from; c) on Solvency II principles, bearing in mind they are not yet fully defined for example, we use the euro swap curve as the discount rate; and d) on cash-flows, where we deliberately do not take account of the inflows and outflows related to new business and lapse risk (1). We focus on allocations offering an adequate return from a commercial viewpoint. On the one hand, the analysis confirms that hedging liabilities with swaps enables the economic risk to be limited but generates significant P&L volatility. On the other hand, hedging with bonds reduces the P&L volatility thanks to the smoothing principles they benefit from, but at greater economic risk. Beyond their imperfect hedging properties, bonds can also be used to diversify the performance-seeking portfolio, which provides value both from an accounting and an economic viewpoint. In the end, an insurer will be able to choose the allocation located on the efficient frontier that best corresponds to its own economic versus accounting risk trade-off. This paper shows to what extent allocations from a period prior to Solvency II regulation can prove inefficient in a new context where Solvency II and local accounting need to be reconciled, and how insurers can benefit from re-assessing their allocations as Solvency II implementation approaches. The demonstration described here is based on a schematic framework that we have defined, but that is designed to adapt to other ad hoc studies that could and should be carried out hand-in-hand with a given insurer s relevant teams. Such studies should focus on the insurer s specific context including its commercial objectives, its solvency situation and the local accounting rules it is subject to as well as on specific asset classes proving to be valuable within the Solvency II framework. In summary, any adverse consequences for the industry may end up not so much arising from the Solvency II guidelines as such, but rather from the way insurers take these new guidelines into account when determining their future asset allocations and investment strategies. We believe those insurers who tackle these issues today will be the winners of tomorrow. Rather than reasoning from scratch, discussions can also take place to improve an existing allocation based on its ability to generate both an appropriate expected return (to limit commercial risk) and its adequacy in relation to the insurer s solvency situation. We carry out this exercise in the context of two different scenarios: one for a single asset pool structure (joined asset allocation for both policyholders and shareholders), and another for a structure wherein the policyholders asset pool is separate from the shareholders asset pool. We then measure the impact of the changes proposed for each type of stakeholder. Improvements can be achieved in both cases. The impact can be better directed in the case of two separate asset pools, although possible conflicts of interest between the stakeholders may arise. Last but not least, once an appropriate strategic asset allocation has been defined, it makes sense to implement free capital preservation strategies this time by taking into account the SCR rather than the VaR (1Y; 99.5%) so as to ensure consistency with the regulatory measure imposed in the short term. Despite its cost in terms of upside potential, we in fact show the significant benefit of an ex ante risk reversal strategy as well as an ex post flexible allocation to equities, with the most attractive solution arising from their combination. 1) The lapse risk is defined as the surrender risk linked to a sudden interest rate spike

6 6 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November Foreword: why is it a challenge for an insurer to determine its strategic asset allocation? Solvency II has been on the radar for a while now: on insurers radars of course, but also on those of asset managers who wish to work closely with insurers. Certain Solvency II parameters remain to be settled, at the forefront of which is the exact way in which liabilities will be discounted, with animated debates still going on about the matching premium, the counter-cyclical premium and the ultimate forward rate. Nevertheless, the key principles are established and already incorporated within insurance companies way of reasoning. The upcoming introduction of Solvency II is likely to trigger a revisiting of insurance companies asset allocation determination process, a complex exercise given the need to reconcile different objectives linked to stakeholders, regulation and time horizon Stakeholders An insurance company needs to take into account the interests of its two key stakeholders, policyholders and shareholders, which are by their nature somewhat different, in particular in life insurance: Policyholders are seeking additional return through profit-sharing, beyond what is due to them through the guarantees. So their interest is for the asset allocation to be risky enough to offer them profit-sharing, all the more so as the downside risk is covered by shareholders through the guarantees provided to them on their capital and in many cases through a minimum return level. Insurance companies take into account a target return to deliver to policyholders (in France, for example, the 10-year French government yield), below which they will face commercial risk. Shareholders have by definition put capital at risk to ensure the solvency of the insurance company. Due to the risk taken, they will expect sufficient Return on Equity (ROE), while also seeking control of the risk taken to avoid extreme scenarios. Their approach to judging the risk/return profile of an asset allocation will be an economic one. As we will see, Solvency II definitely makes steps towards an economic approach, the SCR of an allocation giving an idea of the economic risk at stake. Nevertheless, it makes sense to also take into account complementary economic indicators to grasp the full granularity of underlyings ratings or take into account diversification benefits thanks to a finer correlation matrix than the one used for Solvency II. Considering additional risk measures (after the SCR) is typically in the spirit of the ORSA (Own Risk & Solvency Assessment) developed internally by the insurer in the context of the second pillar of the Solvency II regulation. This registers in a more global process in terms of Enterprise Risk Management compared to the first pillar dedicated exclusively to the calculation of the SCR Regulation An insurance company faces different regulatory frameworks, in particular for local accounting and for solvency, that are likely to vary somewhat, which can explain a changing level of attractiveness of asset classes depending on the framework being considered. From an accounting viewpoint, depending on the insurer, it may face two accounting frameworks: IFRS and local GAAP. Our focus here is local GAAP, which has historically been the main driver in determining insurers asset allocation as it determines the profit-sharing. With European local GAAPs it is very often possible to smooth the financial result, typically with fixed income instruments impact on P&L being limited to their yield to maturity, while instruments such as equities or derivatives are valued with approaches closer to mark-to-market. Even though we will not focus on IFRS here, it is interesting to note that it will tend to be more close to mark-to-market. From a solvency viewpoint, Solvency II will introduce a mark-tomarket approach as well as a direct link between asset allocation and capital requirement. So, whereas the solvency viewpoint as such has not played a determining role in determining asset allocations before now, it will in the future need to be reconciled with the local accounting viewpoint. To give an example, swaps will be useful under Solvency II for hedging purposes in an asset allocation as they will mimic liability behaviour, while their valuation in mark-to-market under local GAAPs may for some insurance companies appear as a barrier to incorporating them Time horizon Additionally, insurers need to reconcile their long-term approach with the wish to take action in the shorter term, either to seize opportunities over the medium term or to protect themselves against extreme events in the short term. Insurance especially life insurance is a long-term business, so the time horizon taken into account in building an asset allocation should also be long. This is even more the case as insurance companies are unlikely to change their allocation over a short period due to accounting rules: if risky assets are sold, they will generate a P&L impact and thus a profit-sharing impact. Nevertheless, asset class attractiveness can vary significantly depending on the entry point, and an insurance company may consider it would add value to take into account the entry point when designing its asset allocation.

7 7 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November 2012 In addition, asset class behaviour in the short run can differ greatly from what may be expected over the medium or long term, and insurers are likely to want to be able to react effectively should extreme events occur. These different objectives and constraints make it a challenge for insurers to design their asset allocation, yet this exercise is critically important. As partners to insurers, we wish to understand what future challenges they face with Solvency II, and to share information and ideas in this context. We have been following this path over the past two years. Based on our understanding of Solvency II and local accounting rules on the one hand, and on our experience in asset allocation determination as an asset manager on the other hand, we have developed a framework and tools to accompany them in their reflection on asset allocation determination.

8 8 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November Solvency II: a much more economic approach compared to Solvency I The Solvency II directive will reform the European insurance sector s risk management. With its three pillars, Solvency II introduces various changes. As asset managers, we mainly focus on the following aspects: Within pillars 1 and 2: market risk. The market risk is the largest contributor to the total SCR for the life insurance industry and will thus be pursued very robustly. In such context, our objective is twofold: assisting insurers in the determination of their asset allocation (purpose of this white paper) and providing adequate solutions and products within this framework. Within pillar 3: transparency requirements. As insurers face more stringent requirements, we as asset managers need and wish to provide the appropriate level of information to ease the process for insurers, whether they are using the standard model or an internal model. We have been working on this topic closely with BNP Paribas Securities Services to develop appropriate reporting, but this will not be the focus of this document. The approach adopted by Solvency II to calculate the regulatory capital necessary to cover the market risks represents a major upheaval for the insurance industry A global mark-to-market that increases the volatility of both assets and liabilities First, it introduces a mark-to-market logic covering both assets and liabilities for all European insurers, whereas Solvency I rules were more country specific. On the asset side, the change particularly impacts players from countries where assets were previously taken into account at historical costs. On the liabilities side, the discount rate used under Solvency I to evaluate the technical provisions was, in most cases, a fixed rate: this led to a fairly stable valuation of the liabilities. This will change substantially under Solvency II, as the new regulation will impose the consistent use of a market rate based on the swap curve adjusted by a credit component; the exact detail of this remains to be settled, with discussion still ongoing as to the definition of the matching premium and the counter-cyclical premium that are likely to replace the illiquidity premium described in QIS 5. This mark-to-market approach will translate into higher volatility of assets and liabilities for insurance companies, thereby creating a need for liability-matching solutions and downside protection strategies aimed at reducing both the volatility of the surplus and the solvency ratio Direct link between portfolio composition and Solvency Capital Requirement Secondly, Solvency II introduces a direct link between portfolio composition and capital requirements, whereas under Solvency I, the capital requirement was a fixed percentage of the liabilities (technical provisions) and independent of the insurer s asset allocation. Under Solvency II, SCR calculations will be based on stress tests covering different market risks, applied to both the market value of assets and liabilities: seven under QIS 5, including an illiquidity premium risk, which most likely will evolve or disappear, as mentioned above. The difference in behaviour between assets and liabilities in reaction to these stress tests will have to be covered by regulatory capital.

9 9 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November 2012 Illustration 1: Global market SCR based on the seven market risks (QIS 5) Input for the global SCR Calculation Output Different capital charges from the different market risks: 1. Interest rate risk up shock down shock 2. Equity risk 3. Property risk 4. Currency risk up shock down shock 5. Credit spread risk up shock 6. Illiquidity premium down shock 7. Concentration risks All stress tests are applied on the Surplus = Assets Liabilities (also called NAV) For each market risk: first liabilities are shocked (or not depending on the market risk), then assets are shocked, the difference of NAV before and after shock is calculated These risks are aggregated with correlation matrix Global market SCR: capital charge resulting from the combination of the different market risks 2.3. Alternatives, equities, and low-rated corporate bonds are the most penalised assets in terms of capital requirement The capital charge linked to the different stress tests is based on a VaR (1Y; 99.5%) and will be larger or smaller depending on the risk associated with each asset class. From a pure capital requirement point of view, alternative and equity investments are the most penalised asset classes. On the fixed income side, low-quality corporate bonds and long-maturity bonds will be the most impacted, as detailed in illustration 2. Illustration 2: Capital charge per asset class based on QIS % 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Goverment Bond AAA duration 5 Goverment Bond AA duration 5 Goverment Bond A duration 5 Corporate Bond AAA duration 5 Corporate Bond AA duration 5 Corporate Bond A duration 5 Corporate Bond BBB duration 5 Goverment Bond AAA duration 8 Goverment Bond AA duration 8 Goverment Bond A duration 8 Swaps duration 8 Goverment Bond AAA duration 11 Goverment Bond AA duration 11 Goverment Bond A duration 11 Property Currency Equity OECD -Alternative Investments (HF,Private Equity, ). Long-term assumptions used for interest rate risk (see appendix 1) 2) These capital charges do not include the impact of the stress tests on the liability side.

10 10 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November Diversification adds value under Solvency II To calculate the global market SCR, the different capital requirements linked to the different shocks will then be aggregated based on the Solvency II correlation matrix defined in QIS 5. By virtue of this matrix, diversification will be rewarded under Solvency II even if not to the same extent as with an empirical correlation matrix. As a result, reporting and transparency on the holdings will become crucial in order to benefit from such diversification. Another significant consequence of this global balance sheet approach is that the industry will have to work differently. In the past, people in charge of liabilities (actuaries) worked alongside those in charge of the assets (investors, asset managers) but without necessarily interacting. In the future, they will have to work handin-hand to build the optimal allocation based on specific liabilities, and we will typically work with both sides when carrying out a study on asset allocation determination. To summarise, under Solvency II all assets and liabilities will be accounted for at market value and underlying real risks will need to be covered by regulatory capital. In contrast to Solvency I, asset allocation will influence both the regulatory capital and the free capital. It is thus essential for insurers to take into account the new Solvency II framework in determining their asset allocation. Before we illustrate our view on the overall asset allocation determination exercise, we first focus on different asset classes attractiveness under Solvency II.

11 11 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November Asset classes attractiveness under Solvency II As previously illustrated, the capital charges under Solvency II are quite different depending on the asset class, which will thus affect the attractiveness of those assets. Given this, Solvency II is likely to favour those asset classes that best represent insurers liabilities so as to minimise their capital requirement. In the same spirit, insurers seeking to reduce their SCR due to a capital shortage are likely to move away from standard equities and/or alternative products as these asset classes require significant capital Need to consider both asset classes expected return and their capital charge While the analysis of the SCR impact is necessary, it is not in itself sufficient. SCR focuses solely on risk, not on possible returns. What really matters, in our view, is to optimise a portfolio within the context of Solvency II. By that, we mean taking into account not only the SCR impact but also the expected return on each asset class, and then determining how to ensure consistent portfolio behaviour over time. In this context, how much excess return is expected will be critical when evaluating the attractiveness of various asset classes. Illustration 3 depicts the expected excess return adjusted by the SCR for each asset class based on two sets of expected excess returns. Illustration 3: Expected excess return adjusted by SCR per asset class Long term excess returns / SCR Smart Benchmark excess returns / SCR 3.2. Mitigating black and white conclusions on asset classes attractiveness under Solvency II The expected excess returns of the dark blue bars are based on historical returns, while the excess returns in the light blue bars are based on our Smart Benchmark expected returns (4), taking into account entry points, as we will detail later. Based on this chart, we believe there is no clear or systematic arbitrage, as was the case using only the capital charge criteria. For example, the chart shows that, based on historical excess returns, investment grade bonds outperform OECD equities. However, if we use our expected excess returns from the Smart Benchmark for the same two asset classes, this historical conclusion is mitigated due to the current very low interest rates. This shows that one should be cautious in coming to black and white conclusions about asset class attractiveness under Solvency II, all the more so as other factors can be influential. Indeed, running a thorough portfolio analysis that takes into account the diversification potential and the insurer s specific context (target return, max SCR, max drawdown, etc.) will trigger different asset classes arbitrage. We think that reaching rapid conclusions on the attractiveness of asset classes based exclusively on their capital requirement can be misleading. To have an accurate asset class attractiveness analysis, we consider it necessary to compare the expected return with the SCR, taking into account both the diversification effect and the specific context of each insurer as well as the hedging properties of the different asset classes ) Through our Smart Benchmark approach, we define the medium term (5-7 years) expected excess return per asset class based on current valuation and assuming a mean reversion of the valuation over the investment cycle. The numbers presented here were updated at the end of February GOVIES INV GRADE EQ OECD EQ OTHER. 3) Govies = 50% * (Government Bonds, AAA, 11y) + 25% * (Government Bonds, AA, 11y) + 25% * (Government Bonds, A, 11y) Inv Grade = 25% * (Corporate Bonds, AAA, 5y) + 50% * (Corporate Bonds, AA, 5y) + 25% * (Corporate Bonds, A, 5y) EQ OECD = 51.2% * Equities US % * Equities Europe % * Equities Japan EQ OTHER = Emerging Equities

12 12 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November Framework considered for the asset allocation determination The concept behind this paper is to present the framework put in place to define an optimal strategic asset allocation in the context of the new Solvency II regulation. Our goal is to highlight the first order effects linked to the choice of an optimal asset allocation taking into account five relevant parameters (economic risk, prudential risk, accounting risk, return on assets and return on equity) for insurers. To capture such effects and to be as didactic as possible, we have based our analysis on a stylised and simplified example. All our assumptions are detailed hereafter. This of course does not prevent us from carrying out more detailed analysis based on a more complex modelling, better reflecting the reality faced by the insurers. This would allow us to grasp the second order effects but is not likely to alter our first order messages A simplified balance sheet with a single type of life contract and a limited asset class menu - Consideration of a single type of life contract Depending on their business mix between life and non-life, and on the features of their products within each of these businesses (duration of contracts, profit sharing level applied, etc), insurers will end up with a different number of buckets or homogeneous groups of contracts as liabilities. In our analysis, we will consider a single bucket of life insurance contracts. We have chosen to focus on a life contract as life insurance primarily focuses on profit-sharing contracts, and will be most significantly concerned by market risk under Solvency II (in particular due to their longer duration). The assumptions will be the following for the features of the example life insurance bucket: A best estimate representing 80.6% of the overall assets, hence a surplus representing the remaining 19.4%. Best estimate liability duration of eight years, hence a duration of 6.5 years at the overall assets level, i.e. eight years at 80.6%; A guarantee given to policyholders on their capital; Profit-sharing comprising 85% of the P&L printed in local GAAP every year; 0.70% of management fees. Lapse risk is not modelled here. - One or two asset pools The balance sheet structure differs from one insurer to the next in terms of the number of asset pools. Some insurers tend to have quite a granular approach, with: segregated asset pools corresponding to different contract buckets - with asset pools either legally linked to contracts or designed purely for the ALM construction of the portfolio; and a separate asset pool for shareholders equity. In other cases, insurers will opt for a common asset allocation for the whole balance sheet. In our analysis, we will initially consider a structure with a single asset pool, and then discuss the differences between this and a structure that separates the assets associated with policyholders from those associated with shareholders equity. Illustration 4: Simplified balance sheet with one or two asset pools Balance sheet with one asset pool Balance sheet with separated asset pools Assets Liabilities Assets Liabilities Surplus = 19.4% of Surplus Asset pool 2 Surplus total assets Asset pool Liabilities best estimate Asset pool 1 Liabilities best estimate

13 13 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November A limited asset class menu We will consider the following asset classes eligible in our determination of the strategic asset allocation: Euro swaps; European government bonds with different ratings (AAA, AA, A); European corporate bonds with different ratings (AAA, AA, A, BBB); Developed equities. Note that we have simplified our asset class menu for the purposes of this white paper. Other investable assets (e.g. listed real estate, private equity and other diversification sources) could of course be added to further improve the allocation mix From a local accounting perspective, consideration of a simplified P&L smoothing approach Local accounting has long driven insurers asset allocation determination. The profit-sharing to policyholders is indeed based on the P&L calculated according to local GAAP. The specific guidelines on profit-sharing, as well as the accounting treatment of the different asset classes to determine the P&L, differ from one country to another. It is not our purpose to cover all the different possibilities, but rather to give an illustrative example of the typical mechanism. As far as profit-sharing guidelines are concerned, we consider the following framework, as briefly mentioned in section 4.1: there is a pre-determined level of profit-sharing stipulated in the life insurance contract: 85% of the profit. In certain countries, there is a constraint whereby the insurer s overall P&L must be positive in order for profit-sharing to take place in any given year. In our example, we do not consider this constraint strictly, yet we do measure and wish to take into account the importance for the insurer s overall P&L to be positive. As far as the accounting treatment of the different asset classes is concerned, we have considered the following approach: For fixed income instruments, the profit is equal to their yield to maturity. Compared to a mark-to-market approach, this of course introduces considerable smoothing of the profit. From one country to another, the smoothing can be more or less significant, and can take different forms. In France, for example, the capitalisation reserve is designed to avoid capital gains and losses from bonds impacting on the P&L and thus act as a cushion against interest rate changes and there is also a mechanism allowing to spread the profit due to policyholders across several years as an extra means of smoothing distributed performance; in Belgium, the fonds pour dotations futures acts as a cushion for future profit-sharing. In some countries, the approach may be closer to mark-to-market, in which case there will be less divergence between the accounting approach and the solvency one. We deliberately focus on an example were these approaches diverge, to show how they can be reconciled. For other instruments (including equities, derivatives, and in particular swaps), we consider a mark-to-market approach. In certain local GAAPs, the approach may be more of an asymmetrical mark-to-market, whereby profit is printed only once it is realised whereas unrealised losses beyond a certain level and/or period do impact on the P&L. This brings the additional possibility (not taken into account in our paper) for the insurer to smooth his P&L by deciding to print profits / losses in order to generate a P&L in line with the one targeted. The main point is that, in countries where local GAAP differs from mark-to-market, insurance companies have possible options for smoothing their P&L through different means so long as the P&L volatility remains at reasonable levels. It is thus important to contain the P&L volatility when designing an asset allocation, as will be discussed later. In our exercise, we do not consider the impact of the choice of an asset allocation under the IFRS regime. We instead deliberately focus on a stylised GAAP accounting framework, as it drives profitsharing From a Solvency II perspective, focus on the market risk Given that not all Solvency II parameters are yet fully defined, we have opted for the following approach: The discount rate considered is the euro swap curve. Given that the illiquidity premium described in QIS 5 will most likely be replaced by a matching and a countercyclical premium not yet fully specified (with an impact assessment being carried by the end 2012), we have chosen not to consider either of these premiums at this stage. We nevertheless keep in mind that some type of credit spread is likely to be taken into account in the future discount rate, making credit attractive as an asset class under Solvency II for hedging purposes. We consider a proxy for the calculation of the best estimate. To move from guaranteed liabilities to best estimate, the profitsharing effect must be added.

14 14 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November 2012 In real life, this effect will typically be calculated by the ALM teams for a given asset allocation by averaging year-on-year the liabilities calculated for thousands of asset class behaviour scenarios taking into account the likely P&L distribution through a complex modelling. Such modelling of the best estimates in particular includes the absorption effect when the yield served is below the target yield as well as the quantification of the commercial and lapse risk for each scenario of return. This can be assimilated to a multi-dimensions modelling approach. In our exercise, we consider a more simplified approach for the computing of the best estimate. We believe a good proxy for our stylised exercise is to assume that any asset allocation selected will generate a performance in line with the objective yield for distribution. Based on this, the calculation of the profit-sharing for each year is direct, as well as the discount of all the future liabilities now taking into account the profit-sharing. This approach has the advantage of taking into account the commercial risk but in a simplified way. Indeed, if the chosen asset allocation does not deliver on average the target yield, the policyholders will tend to redeem their contracts: this is what we will from this point on qualify as commercial risk. The shocks applied are those stipulated in QIS 5, except for the concentration risk (because our asset allocation determination exercise is based at the benchmark level, not at the real portfolio level) and illiquidity premium risk (due to uncertainty as to what credit component will be taken into account in the discount rate). We thus ignore both these risks. The short-term dampener effect on equities has also not been taken into account as our exercise is largely based on a long-term perspective. The framework defined to carry out the asset allocation determination exercise takes into account the insurer s balance sheet, the local accounting rules and Solvency II. Illustration 5: Calculating guaranteed liabilities and best estimate liabilities Present value of liabilities corresponding to the guarantee Present Present value value Expected Expected liability liability flows flows corresponding corresponding to to guarantee guarantee Liabilities Liabilities guarantee guarantee Years Years Best estimate: Present value of liabilities catering for participation to benefits Present Present value value Expected Expected liability liability flows flows increased increased by by average average participation participation to to benefit benefit calculated calculated by by ALM ALM (in (in this this exercise exercise by by the the objective objective yield yield for for distribution distribution as as a proxy) proxy) Liabilities best Liabilities best estimate estimate Years Years

15 15 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November Determining an optimal strategic asset allocation (SAA) In this section, we illustrate the framework developed to define an optimal strategic asset allocation under Solvency II. Such an exercise can be carried out with different sets of risk-return assumptions per asset class, which will of course affect the final result. Hereafter we propose to work with two types of risk-return assumptions: the first based on long-term historical averages and the second based on our Smart Benchmark approach integrating medium-term views on asset classes based on current market conditions. An alternative could also be to use the insurance company s own market views. Having two different approaches, one based on a long-term perspective and the other based on current market conditions, raises the inevitable question of which one to choose or how to combine them if both approaches are appropriate to a specific insurer. We address this specific point in the last part of our analysis Determining the optimal asset allocation according to a long-term approach - Methodology/Assumptions In order to determine the long-term SAA for the insurer, assumptions on the yield curves and on the risk-return profile of the different asset classes have been based on historical averages (see details in appendix 1). Our cash assumption over the long term is 3% and comprises of the historical spread between cash and inflation (1%), to which we add a 2% inflation assumption for the coming years (linked to FMI forecasts). The yield curves we consider combine this 3% cash assumption with the long-term shape of the curves. Expected returns for fixed income instruments are deduced from these curves. As for equities, we consider their historical volatility and excess return, to which the 3% cash assumption is added. These assumptions feed our proprietary simulator, of which a more detailed description is given in appendix 2. Five thousand scenarios are generated on the different asset classes, based on a semiparametric model where z-innovations are taken from the historical innovations, preserving cross relations across asset classes. Our simulation model is instrumental in our approach because it enables to calculate the VaR (1Y; 99.5%) on the surplus. - An accounting vs. economic trade-off In determining the SAA, objectives are threefold: Deliver profit-sharing to policyholders in line with the commercial target to avoid commercial risk. Indeed, if the right asset allocation has not been defined to deliver the target yield over long periods, the insurer incurs a commercial risk. In this specific case, the smoothing techniques allowing the insurer to compensate for bad years will prove insufficient to deliver the target yield in the long run. For illustration purposes, the commercial target has been set to the 10-year local government yield, as in the French case. Based on our long-term approach, the 10-year French government bond yield is 4.48%. Taking into account the 0.70% fees and the pre-determined rule of 85% of P&L distributed through profit sharing, the asset allocation needs to generate a performance of 6.1%. 6.1% = (4.48%+0.70%)/85% Limit the P&L volatility to avoid significant variation of return and be able to deliver the target return every year. The idea here is to avoid two scenarios: Having to decrease the profit-sharing served to policyholders, which is likely to lead to commercial risk; Shareholders needing to take a write-off on part of their capital to offset the underperformance, in order to maintain the yield granted to policyholders and avoid commercial risk. Limit the economic risk faced by shareholders and measured by the VaR (1Y; 99.5%). As explained earlier, we consider the VaR (1Y; 99.5%) measure rather than the SCR, even though our research shows that SCR is quite consistent with the VaR (1Y; 99.5%). We believe the VaR (1Y; 99.5%) allows several effects to be taken into account, which is necessary for the determination of an asset allocation even if the SCR remains the key solvency measure. First, it takes account of the default risk on EEA government bonds. Secondly, the VaR (1Y; 99.5%) differentiates the spread risk according to spread levels while the credit risk is not proportional to the level of the yield in the Solvency II framework. Lastly, a VaR (1Y; 99.5%) enables to further take into account diversification effect, given the limited level of granularity of the QIS 5 correlation matrix. Please note that using the VaR (1Y; 99.5%) in the determination of the SAA does not mean that the insurance company has to validate the VaR (1Y; 99.5%) as an internal model of risk with the regulator, but rather that the insurance company performs a sound and prudent business management complying with the Pillar 2 requirement of an Own Risk and Solvency Assessment (ORSA).

16 16 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November 2012 In order to take into account these different objectives, we have only focused on allocations generating a 6.1% return, and compared them according to the P&L volatility they generate (accounting risk) and their VaR (1Y; 99.5%) of the surplus (economic risk) as demonstrated in Illustration 6. Once the optimal asset allocation is selected, the SCR it generates has to be calculated so as to check whether it matches the SCR budget or the solvency target defined by the client. In the case where the solvency level is comfortable, the trade-off between VaR (1Y; 99.5%) and P&L volatility could be analysed for a higher target yield than the 6.1% (as described in section 6), using a three-dimensional approach as shown in illustration 7. Illustration 6: Economic vs. accounting trade-off Economic risk VAR 99.5% 34% 32% 30% 28% 26% 24% 22% 20% 18% 16% 14% 12% 10% 4% Allocations delivering the target return (6.1%) avoiding commercial risk 6% 8% 10% 12% 14% P&L VOL Accounting risk Illustration 7: Economic vs. accounting trade-off for different levels of return Return 10% 8% 6% 4% 2% 1: Hedging the liabilities (introduction of a Liability-Hedging Portfolio [LHP]) dramatically improves the VaR (1Y; 99.5%) of the surplus. The mark-to-market approach of Solvency II boosts interest for assets mimicking the behaviour of the liabilities and, therefore, limiting the underlying capital charge or the VaR (1Y; 99.5%) of the surplus. In this context, the main message boils down to the benefit of structuring the portfolio in two parts, the Liability-Hedging Portfolio (LHP) and the Performance-Seeking Portfolio (PSP). Illustration 8: Creation of a dual portfolio Assets facing surplus = performance-seeking portfolio Assets facing technical provisions = hedging portfolio Solvency II Free capital Regulatory capital Liabilities best estimate } Surplus Let us consider the two following allocations, both generating a return of 6.1%: A portfolio (A) exclusively composed of equities and cash, which we could qualify as a pure PSP, resulting in no hedging at all. A portfolio (B) made of: a LHP designed to perfectly hedge the best estimate and made of swaps calibrated to have the exact same duration as the overall liabilities (6.5 years) a PSP designed to generate a return in excess of the liabilities: given the asset class menu, it makes sense to invest it in equities. 0% 0% 2% 4% 6% P&L volatility 8% 10% 12% 0% 25% 20% 15% 10% 5% VaR (1Y; 99,5%) of surplus More information about the composition of these portfolios can be found in illustration 9 and in Appendix 3. Four principal findings resulted from the analysis we undertook using the previously-stated assumptions:

17 17 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November 2012 Illustration 9: Composition of portfolios A and B A B Weights relative to total assets 100% Weights relative to total assets 100% LHP PSP 81% Cash 81% Assets, Funded Liabilities Cash Assets, Funded Assets, Unfunded Liabilities Equities Liabilities Equities Swap Liabilities By comparing these two portfolios in an economic versus accounting framework (see illustration 10), it appears that introducing a perfect hedging of the liabilities reduces the economic risk as measured by the VaR (1Y; 99.5%) significantly, from 31.3% to 14%. The yield generated by the swaps allows less to be invested in equities while maintaining a similar target return. As a consequence, the volatility is also reduced from 13.2% to 8.7%. Illustration 10: from portfolio A to portfolio B in the accounting vs. economic framework VaR (1Y; 99.5%) of surplus 34% 32% 30% 28% 26% 24% 22% 20% 18% 16% 14% 12% 10% 81% Swap + 39% Equity + 61% Cash B 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% P&L volatility 69% Equity + 31% Cash A 2: Hedging through swaps limits the economic risk but leaves significant P&L volatility The previous step of the analysis has brought us to consider portfolio B as most attractive for the moment. The fact that its LHP is composed of swaps limits the economic risk, as the discount rate used is precisely the euro swap curve. But if we now focus on the P&L volatility of the portfolio, we observe that it is significant: 9%, compared to the expected return generated by such an allocation (6.1%). Such a level of volatility far from excludes the possibility of having a negative P&L. This is due to the mark-to-market accounting of the swap movements. 3: Diversifying sources of performance in the PSP, by investing in government and corporate bonds as well as in equities, limits both the economic risk and the P&L volatility. In other words, it can make sense to over-hedge the liabilities to reduce the P&L volatility. Taking into account the high level of the volatility of allocation B, let us now compare this allocation with a third allocation, C, made up of an LHP offering a perfect hedge (as with allocation B) but combined with a diversified PSP comprising equities, A-rated government bonds and BBB-rated corporate bonds (see illustration 11). The weight and the rating of the bonds of the PSP have been calibrated in a way to deliver a similar target return of 6.1%. The inclusion of bonds in the PSP results in an over-hedge at the level of the entire portfolio, with a sensitivity to interest rates of nine years on the asset side vs. 6.5 years on the liability side (see more details in Appendix 3).

18 18 - Determining a strategic asset allocation in a Solvency II framework - BNP Paribas Investment Partners - November 2012 Illustration 11: Composition of portfolios B and C B C Weights relative to total assets Weights relative to total assets LHP PSP 100% 100% 81% 81% Assets, Funded Assets, Unfunded Liabilities Assets, Funded Assets, Unfunded Liabilities Cash Equities Swap Liabilities Gov.Corp Eq. Swap Cash Liabilities As demonstrated in illustration 12, C appears more optimal than allocation B, illustrating the benefit of hedging correctly in a LHP and combining this LHP with a diversified PSP instead of a pure equity PSP. Diversification within the PSP reduces the total P&L volatility by three percentage points while reducing further the economic risk measured by the VaR (1Y; 99.5%) even if not to the same extent as between B and A. This diversification benefit would also apply to a certain extent in the Solvency II framework for the SCR calculation, thanks to the Solvency II matrix. This also tends to show that an over-hedged portfolio (C) compared to a perfectly hedged portfolio (B) reduces both the economic risk and the P&L volatility. The over-hedging allows bonds and swaps to bring a diversification benefit in addition to their hedging role. Illustration 12: from portfolio B to portfolio C in the accounting vs. economic framework VaR 9(1Y; 99.5%) of surplus 34% 32% 69% Equity + 31% Cash 30% A 28% 26% 24% 22% 81% Swap + 16% Gov Bond A 20% + 16% Corp Bond BBB 18% + 19% Equity + 49% Cash 16% 14% 12% C B 81% Swap + 39% Equity + 61% Cash 10% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% P&L volatility 4: P&L volatility can be further reduced at the cost of higher economic risk by switching to an imperfect LHP investing partly in bonds Based on finding 3, let us now consider a portfolio D (see illustration 13) with a duration of nine years (similar to C), but this time comprising an LHP combining swaps, A-rated government bonds and BBB-rated corporate bonds, and a diversified PSP (as in C). As the imperfect LHP offers a higher yield, the equity weight in the PSP is reduced to match the total target return of 6.1%. In this case, the LHP is not perfect due to the mismatch between the bond curves and the swap curves, even more so, given the VaR (1Y; 99.5%) perspective we have focused on, where European government bonds default risk is accounted for.