Barrie & Hibbert Blog

Solvency II on pensions – a necessary evil?

2012-04-30T08:27:32Z

In February 2012, the European Insurance and Occupational Pensions Authority (EIOPA) published its final response to the European Commission’s Call for Advice on the review of the IORP Directive 2003//41/EC, now commonly known as ‘Solvency II on pensions’.

Much of the subsequent debate revolves around a possible increase in pensions funding and compliance costs - for defined benefit pension schemes in particular. In the UK, various anti-SII lobbying groups argue that the UK already has strong governance structure in place such as the sponsor’s covenant to protect its final salary pensions, and that further protection from Europe is unecessary. So while many DB schemes in the UK are underfunded, much of the gap between the scheme’s existing ring-fenced assets and the amount needed to pay full benefits is safeguarded by the sponsor’s future contributions.

Funding costs aside, very few can really disagree with the concept of a Holistic Balance Sheet (HBS), first introduced in the EIOPA Call for Advice consultation. An HBS approach would potentially require, at least, the quantification and disclosure of the size of the sponsor’s covenant which is currently ‘off balance sheet’ against the full cost of funding a pension scheme, on a long-term economic basis. This would bring transparency to stakeholders regarding the security of the pension benefits. An illustration of a possible HBS is set out in figure 1.

One of the challenges of adopting a Holistic Balance Sheet approach is in being able to quantify the sponsor’s covenant in a market-consistent manner. It is undoubtedly an interesting problem, but one that need not be so complex that it defeats us. (The main focus of this article is not about capital requirement, but it is worth mentioning that as the Solvency Capital Requirement is defined using a Value-at-Risk (VaR) for the market-consistent balance sheet, once we have a way of calculating the market-consistent balance sheet, we can then build a VaR estimate by re-valuing that balance sheet in tail scenarios).

Techniques already employed in insurance solvency assessment have direct relevance to solving the problem of valuing the sponsor covenant. Not only do these mechanisms give an objective method of quantifying the employer covenant, they could also provide an improved governance structure in which trustees and sponsors have a clear strategy on if and when employer contributions will be paid as market conditions change. The credit-riskiness of contributions, if deferred, can also be quantified.

Market-consistent valuation of the sponsor covenant – a possible approach

Another method of putting a market-consistent valuation on the sponsor covenant is to examine the contribution strategy in order to identify how the full range of possible future financial and economic paths, as well as how the credit-riskiness of the sponsor will behave over time. The approach suggested below has parallels with how insurers incorporate future management actions into the valuation of market-consistent balance sheet in Solvency II.

Firstly trustee and sponsor need to agree a contribution strategy. This sits well with flight path discussions which are already in place with many trustee boards. The HBS approach will simply formalise what is already in place. A very simple example of a possible contribution strategy might target, say, 80% funding level on an economic basis and spread any deficit over a five-year period.

Next, we use a set of risk-neutral economic scenarios to produce the joint behaviour of the paths of market returns and sponsor defaults. These scenarios are then used to produce the cash flows in accordance with the contribution strategy, derived from the flight path discussion, to produce a market-consistent valuation of the sponsor’s covenant.

By way of an example, figure 2 shows the results of the sponsor’s covenant by looking at sponsors with a range of credit-worthiness. To test the extreme, funding strategy 1 assumes that the sponsor delays contributions until all assets are fully exhausted, and funding strategy 2 assumes that the sponsor will pay the full buyout cost every year should a deficit arise.

Based on figure 2 above, we can make a number of observations:

The larger the contribution payments are assumed to be, the larger the value of the sponsor covenant will be. (Where contributions are paid at the end of every year to fund to full buyout (blue line), the overall value of covenant is higher especially for a risk-free employer.
The more credit-risky the sponsor is, the smaller the value of the sponsor’s covenant will be.

The two observations might be obvious but they demonstrate that this technique is useful in terms of quantification of the sponsor’s covenant. The conclusions are also in line with what logic tells us should be true.

Key benefits of this approach in quantifying the sponsor’s covenant within the holistic balance sheet framework

A Holistic Balance Sheet approach is indeed more transparent but also brings with it interesting challenges from a financial modelling point of view. In addition, our suggested approach, set out above, on the quantification of sponsor’s covenant has additional benefits which extend beyond the HBS framework of:

Clarity of value when contributions are deferred – this method allows both the quantification of time value of money as well as the credit-riskiness of delaying contributions.
Lends itself to having a governance structure whereby trustees and sponsors are clear about their contribution strategy – when contributions are expected to be paid under different financial outcomes, both the movements as a result of the scheme’s funding position as well as changes to the sponsor’s financial circumstance.

Both of the above seem to me to have the benefit of killing two birds with one stone. More importantly, it honours the true spirit behind Solvency II for putting in place an HBS– better financial management of the pension scheme and ultimately more controlled decision-making.

Alternative views on extrapolated yield curves: a fundamental question remains unanswered

2012-03-05T15:01:28Z

The valuation of ultra long-term cash flows is surely one of the most basic challenges faced by accountants and actuaries. Yet the resulting debate grinds on about how to extrapolate observable yield curves. At its heart is an absolutely fundamental choice. On the one hand, extrapolated prices could represent where we might truly expect to trade a promised cash flow. These prices will be uncomfortably volatile and will imply relatively high levels of solvency capital for insurance firms. Alternatively, extrapolated prices can be stabilized for the purposes of avoiding this variability. Unfortunately, prices produced by the two methods are quite different.

The estimation and extrapolation of market yield curves has gained the attention of insurance firms, accountants and regulators over the past few years as a consequence of a move towards a market-based approach to valuation. This basic valuation principle is embedded in IFRS/FASB rules for fair valuation (including insurance contracts) and a worldwide move by insurance regulators towards risk-based capital to support an economic balance sheet. Here we will discuss one fundamental question – the basic purpose of any extrapolation. There are two separate ways of thinking about extrapolation which turn out to be quite different.

View #1: Accountants and traders – the Traders’ yield curve

Consider the perspective of accountants and dealers. The FASB definition of fair value says:

“Fair value is the price that would be received to sell an asset or paid to transfer a liability in an orderly transaction ... between market participants ... under current market conditions.”

IASB/FASB anticipates using a range of market information and judgement to arrive at a valuation. Where prices are unavailable, valuations are to be based on expected values with risk adjustments. In order to give insight into these risk adjustments, consider the question of where a transaction would take place and ask yourself what factors would determine where you would be prepared to trade? The trader’s approach is to ask: firstly, how much of the resulting risk in my position can be hedged? Secondly, what is the cost of the hedge over the possible life of the position (itself often highly uncertain – especially if the hedge requires dynamic action)? Thirdly, how to adjust a price for the unhedgeable risk for which additional trading risk capital is required i.e. what is the necessary amount and required return on the trader’s risk capital. For a cash flow falling beyond the traded market, we could say:

The cost of the hedge will be closely linked to the availability of similar tradable bonds.
The risk charge is likely to be unstable. In stressed market conditions, the risk charge will probably rise in line with other risk capital costs.

This line of argument suggests that a fair value approach will produce volatile extrapolated prices. For anyone who must trade an asset or liability, these are the values that really matter and pretending otherwise could be costly. Let’s call the results produced by hedging and taking account of capital costs the traders’ yield curve. You might expect the extrapolated curves produced to contain flat forward curves where variability in traded rates is transferred to extrapolated maturities.

As an aside, you should note EIOPA’s view is that risk adjustments for unhedgeable market risk can be ignored – either because they are immaterial or just too difficult to calculate.

View #2: Actuaries and insurance regulators – the Stabilized yield curve

Volatile market-based yield curves result in volatile insurance balance sheets and, given a short-term VaR capital measure, relatively high and volatile capital requirements. This volatility is seen as unhelpful by many in a long-term business where extrapolated cash flows are rarely traded. A consensus has emerged to stabilize the curve and methods essentially attempt to answer three questions:

What is the limiting (“ultimate”) forward interest rate (UFR)?
Which observable market prices should be fitted?
What is the appropriate speed of convergence between observed rates and the ultimate rate?

The way these questions are answered could deliver curves that are indistinguishable from the trader’s curve. Alternatively, highly stable rates could be generated that bear little resemblance to the trader’s curve. For all three questions, there are quite different views. The discarding of market prices – due to their lack of liquidity – runs the risk of disconnecting liability values from markets and creating a disincentive to hedge – probably not the regulators’ intention nor in the long-term interests of shareholders and policyholders.

Where next?

So, is it possible to simultaneously stabilize the extrapolated curve whilst respecting market prices and the trader’s pricing models? I doubt it. The stability that regulators and firms seek simply is not consistent with a trader’s view of pricing dynamics.
Does this matter? In Europe at least, it seems a simple fact of life that the answers to these questions will now be determined by political compromise rather than cold, objective economic analysis. However, there is a fine balance here which now risks the creation of two sets of yield curves – one for accountants’ fair valuation which makes use of all reliable market information and an alternative which stabilizes for the purposes of regulatory valuation. That would be a disappointing outcome for the architects of Solvency II.

Jumbo jets and fighter planes: exploring the Point-In-Time approach

2012-01-13T14:36:21Z

In previous articles, we have discussed the relative merits of the Point-in-Time (PIT) and the Through-the-Cycle (TTC) views of risk and capital; in a new research report, we analyse these approaches from the perspective of policyholder protection. This entry summarises the main findings, namely that PIT capital regimes can in principle simultaneously provide a higher degree of policyholder protection and a lower long-run average capital requirements than the TTC approach, although there are practical difficulties which must be considered.

Figure 1: Comparison of TTC and PIT Value-at-Risk at 99.5% over one day for the S&P 500

PIT capital takes account of all available current information to assess capital requirements for the current period. By contrast, TTC capital aims to set capital requirements for a typical year. These two approaches turn out to deliver both different levels of average capital and potentially different levels of protection for policyholders. In our report we develop and illustrate three key results as follows.

Result 1: The long-term average capital requirement using the PIT approach is typically lower than the capital requirement using a TTC approach.

We know that the average of a function of a random variable is not the same as the function of the average of that random variable. In a similar manner, the capital required for average risk is not the same as the average capital for time-varying risk. In fact, we have observed that long-term average PIT capital requirements are typically lower than TTC capital requirements. This is not always the case but in all the realistic examples we have investigated we have found this result to hold.

To illustrate this we can use real data on equity returns. Figure 1 shows daily S&P 500 losses (negative returns) from 1990 to 2011, along with TTC and PIT “capital requirements” of 99.5% Value-at-Risk over a one-day horizon. The frequency of losses exceeding available capital is 0.5% per day in both cases. The TTC case holds a constant level of capital, while the PIT case dynamically adjusts capital requirements according to forecasts of volatility. The average PIT capital requirement is 2.94%, significantly lower than the TTC capital requirement of 4.17%.

Intuitively this can be thought about using the following analogy: if you were flying a jumbo jet through a mountain range, how low would you dare fly? The chances are you’d want to fly at, or about, the height of the highest mountain in the range. How about if you were flying in a nimble fighter jet? You could fly lower through most of the range, and pull up over the high peaks whennecessary (Figure 2). Your average height would be lower in the second case than the first (although the ride might be more nail-biting!).

Figure 2: TTC is like a jumbo jet, PIT is like a fighter jet. You can fly lower on average with PIT, although at times you may fly higher.

Result 2: The PIT approach using Value-at-Risk provides the optimum protection to policyholders, in terms of the Expected Policyholder Deficit, for a given average level of capital support over time.

The Expected Policyholder Deficit (EPD) is the expected value of policyholders’ losses through insolvency. The EPD is often used as a measure of policyholder protection, as it considers both the severity and the frequency of insolvency. It turns out that, for any given long-term average level of capital support, the policyholders’ total expected deficit is minimised if this capital is held on a PIT basis, using Value-at-Risk as a risk measure.

This says that if an insurance company wishes to maintain a long-term average level of capital support of $100 million, say, then it is much more beneficial to policyholders for the insurer to hold more capital when riskiness is high, and less when riskiness is low, such that the average level of capital is $100 million, than to hold $100 million at all times. This is a very general result which does not make strong assumptions about the particular distributional form of the model.

In the example of equity returns above, if we scaled up the PIT capital requirement so that the average PIT capital is the same as the TTC capital requirement of 4.17%, the Expected Policyholder Deficit in the PIT case is 0.0011% per day while in the TTC case it is over 7 times higher at 0.0078% per day.

Result 3: The PIT approach can simultaneously give a higher degree of policyholder protection and lower long-run average capital requirements compared to the TTC approach.

What is the outcome of combining Result 1 and Result 2? Do the costs and benefits associated with the different approaches to capital just cancel out? If TTC capital requirements are higher than average PIT capital, does this offset the lower Expected Policyholder Deficit for PIT for the same average level of capital? The answer is no, not in general. Even when TTC capital requirements are higher than average PIT capital requirements, the Expected Policyholder Deficit tends to be lower in the PIT case than the TTC case.

To achieve the same degree of policyholder protection, in terms of Expected Policyholder Deficit, TTC capital requirements may have to be substantially higher than long-run average PIT capital requirements.

Table 1 summarises the average capital requirement, probability of insolvency and EPD for the following four cases in our S&P 500 example:

TTC(I): Through-the-Cycle VaR at the 99.5% level
PIT(I): Point-in-Time, scaled to match the same average capital requirement as TTC(I)
PIT(II): Point-in-Time VaR at the 99.5% level
TTC(II): Through-the-Cycle, scaled to match the same EPD as PIT(II)

	TTC(I)	PIT (I)	PIT (II)	TTC (II)
Average Capital Requirement	4.17%	4.17%	2.94%	5.05%
Probability of Insolvency	0.49%	0.12%	0.49%	0.26%
Expected Policyholder Deficit	0.0078%	0.0011%	0.0044%	0.0044%

Table 1: Comparison of results of different capital approachesapplied to daily S&P 500 returns

Summary

Our analysis and investigations suggests that, in principle, the PIT approach to capital requirements provides a higher level of policyholder protection than the TTC approach. To put it simply, with TTC, when policyholders lose, they tend to lose big. Further, PIT capital requirements tend to be lower in the long-run average sense than TTC capital requirements – capital is committed when it is needed most. Capital has an opportunity cost and so shareholders will prefer a company to operate at lower capital levels if they can achieve the same objectives. In practice, however, we do acknowledge that there are a number of operational difficulties in carrying out the PIT approach. In particular, PIT capital requirements can be very volatile, and a company could find itself having to raise significant levels of capital at certain points in the “cycle”. Thought needs to be given to how a company could manage these variations in capital requirements i.e. how the costs of raising and distributing capital influence the optimal strategy and how the volatility in capital requirements may enforce cyclicality.

Finally, these results do not incorporate the impact of model risk (i.e. the possibility of mis-forecasting risk) which would both tend to dampen the movements in PIT capital. In terms of our airplane analogy, if it is foggy, or if the instruments in the cockpit of the plane are faulty, the PIT pilot may be wise to fly higher to give themselves more of a buffer should a mountain suddenly appear.

Contrasting the differing requirements of the various stakeholders in an insurance company, there turns out to be a direct conflict between policyholder protection and the commercial difficulties of implementing a PIT capital management strategy in practice. We believe that the framework summarised here and presented in detail in our research note provides an important reference point for firms and policymakers in respect of a fundamental question in the capital management debate.

Solvency II for pensions - an unwelcome intrusion, or an inspiration?

2011-12-06T15:44:34Z

The 2010 EU Green paper on the future of pensions sparked many debates in the industry about the pros and cons of applying Solvency II to pensions. Following this publication, the European Commission asked EIOPA for advice on an EU-wide legislative framework for IORPs (Institutions for Occupational Retirement Provisions) in April 2011. EIOPA has since published a second consultation on ‘draft responses to Call for Advice’ currently expected to close on 2 January 2012.

Many have expressed concern regarding possible implementation of the draft proposals contained in these documents. Speaking in his capacity as chair of the NAPF, Lindsay Tomlinson voiced concerns that a Solvency II regime applied to pension schemes will have the effect of restricting pension schemes’ freedom to invest, suggesting that pension schemes should be growth investors. Many have interpreted this ‘restriction’ as having the effect of prompting an exodus from equities to bonds. Another concern is the burden of potentially yet another funding basis – no doubt prompted by the reports of spiralling Solvency II costs in the life sector - allegedly some companies have already spent over £150 million on Solvency II implementation.

While this debate continues, we should perhaps pause and ask ourselves -- are we already approaching a theoretical Solvency II regime on pensions?

Mapping Solvency II onto the existing pensions framework

In order to understand how far we are currently from a possible Solvency II regime, let’s summarise what Solvency II for insurers looks like, and how that potentially maps onto the pensions world.

A high level summary comparing an insurance regime and a pension regime are set out in the diagram below:

Pillar I – covers the quantitative requirements – in essence, what is the value of your pension liabilities and how much risk is there in the scheme?
Pillar II – covers the qualitative requirements which will require a clear robust governance structure as well as a risk management process in place. In pensions language, this translates into pension scheme trustee governance, trustee knowledge and understanding and the risk register, to name a few.
Pillar III – covers disclosure requirements to regulators and members. This translates into disclosure of pension scheme’s annual Trustee Report & Accounts and Annual Summary Funding Statement to all members.

Comparing the current DB pension system in the UK with the insurance sector, one may even be convinced that the two sectors are not really under a very different regime. Most of the contentious points about applying a Solvency II type regime on DB pensions are about Pillar I and not about Pillars II and III.

The devil is in the detail

Pillar I has caused most controversy as on the face of it, a Solvency II approach will require pension schemes to operate on a much stronger funding basis as well as holding additional capital against investment risks and other unhedgeable risks. However, this scenario might not arise as the Call for Advice has made a clear distinction between the schemes which are underwritten by a sponsoring employer and those which are not. The implication is that schemes with a sponsoring employer (which apply to almost all schemes in the UK) will be able to allow for the recourse to the employer as a backing asset. In addition, it may be possible for credit to be taken for the presence of the PPF in some form. We are of course far from getting the details on paper, but for the sponsors who are worried about the funding implications of Solvency II on pensions, the reality of the situation might not be as grim as it sounds.

What’s changing: the wider implications

Apart from the IORP directive, other regulatory bodies continue to move forward in the area of deriving a platform which better reflects risks taken by pension schemes.

One such change is the PPF levy framework for 2012/2013. Within this framework, part of the PPF’s main objectives in respect of measuring investment risk is as follows:

to reflect the potential volatility of a scheme’s investment strategy in thelevel of risk-based levy charged; and
to give schemes that have adopted de-risking strategies the opportunity to obtain appropriate credit for these risk reduction measures.

Practically, this means that for the 2012/2013 levy year, schemes with liabilities above £1.5 billion will have to carry out a Bespoke Stress Calculation on a mandatory basis. But adopting a more risk-based approach is very much in line with the principles of Solvency II and the PPF’s levy framework will hopefully act as a catalyst to better risk management practice for pension schemes without the bureaucratic burden of onerous legislation.

Conclusion

With the other changes, driven by different authorities coupled with the review of the IORP directive, it is not a matter of lobbying against whether Solvency II should be applied to pensions; one would argue, it is already in place, simply badged up under a different name.

A constructive way to deal with the possibility of applying Solvency II to pensions is to learn our lessons from how Solvency II implementation on insurance is working and select the elements which have worked well and avoid the pitfalls for pensions.

Different parties within the pensions industry are currently lobbying about (mostly against) Solvency II on pensions. If we are not careful, some of the strong messages may get lost in politics as a result of highly negative voices about the IORP directive. Initiatives such as the PPF levy framework to include investment risks are good practice to ensure that schemes are rewarded for managing risks. As we see from the current financial crisis, a system whereby institutions are treated equally regardless of the level of risks they run means that the good ones will forever have to bail out the bad ones.

A signal from the Fed?

2011-08-18T13:15:08Z

In the midst of global financial market turmoil and following the downgrade of its government’s credit rating in the previous week, the US Federal Reserve Bank announced on August 9^th that it anticipated that the dismal state of the domestic economy and developed world growth prospects would “warrant exceptionally low levels for the federal funds rate at least through mid 2013”. What does this mean for projection of US interest rates? In particular, is there a case for narrowing the distribution of projected possibilities for US short rates over the next two years in line with the Fed’s anticipated path?

When thinking about the probability that should be attached to the Fed’s scenario, it is worth saying that there are many other scenarios that could play out over the coming years. Whilst central bankers are clearly smart people, even they would not claim to have perfect foresight. Past attempts by economists to forecast financial and economic circumstances have been fairly unsuccessful and are naturally constrained by the practical challenge of forecasting the behavior of a complex, dynamic social system which we do not (and probably never will) fully understand. In other words, I think we should be sceptical of any forecast. Uncertainty about what will and can happen to asset prices is one of the reasons that stochastic models can offer significant insights. There is little doubt that, with S&P’s credit downgrade of the US and the intensification of the Euro area debt crisis, the future of the global economy is especially uncertain and investor confidence is unusually fragile. This leaves policymakers in a weak position when it comes to making rhetorical guarantees or promises.

The announcement by the Fed is best interpreted – by the sceptic – as a fairly clear (and worryingly impotent) attempt to calm the markets as opposed to an unshakeable commitment to a certain monetary policy stance. The clear internal wrangling that was behind the decision (signalled by the split in the vote 7-3) and the fairly slippery language used to make the announcement (“[The Federal Open Market Committee] will continue to assess the economic outlook in the light of incoming information and is prepared to employ these tools as appropriate.”) doesn’t really inspire belief that a low rate environment is something that policymakers will enforce ‘come hell or high water’. If, for example, inflation rates continue to tick up and expectations lose anchor there will be pressure to respond. The question we need to ask is how much attention should we pay to this announcement when thinking about yield curve projections for the coming years? As is so often the case, market instruments offer an important source of information.

How have participants in the market for US treasuries reacted to the announcement?

Source: http://www.treasury.gov/resource-center/data-chart-center/interest-rates/Pages/TextView.aspx?data=yield

The falling prices of risky assets and the corresponding flight to safety depressed yields between August 1^st and 8^th across all maturities. Subsequently, as might be expected, longer yields have not reacted (much) to the Fed statement, although at shorter maturities curves appear to have become slightly more depressed. Whether this will persist remains to be seen.

So, how does the Fed signal feed through to our views on the potential outcomes for yield curves over the coming two years? To the extent that the market would be calmed by the news and to the extent that the market believes the announced rate paths, our calibrations and views should naturally adjust to reflect this (whilst also weighting some longer term fundamental views). From the market reaction so far the implication is that the Fed announcement is being treated with an understandable degree of scepticism by investors.

Stochastic projection methods are implicitly sceptical but don’t provide explicit explanations for the scenarios generated. We can tell stories around some of these scenarios and debate probabilities – Rumsfeld’s known unknowns – for example, the inflation surprise that triggers a response from the Fed. Other scenarios – the unknown unknowns – are more elusive and therefore can, ultimately have a bigger impact on future prices. It is easy to forget this important source of risk.

Barrie & Hibbert in the press: ifaonline, Risk.net, and the Actuary

2011-07-08T09:48:15Z

How to use Barrie & Hibbert's retirement tool

ifaonline.co.uk

"John Higgins and David Campbell believe the at- retirement space is currently underserved by financial planning tools. Advisers are provided with plenty of options for which tools to use in the accumulation of their pension funds but have little to help decide the most effective approach to managing the transition to retirement and how to optimise their income in retirement."

Comment: Practical considerations are compromising Solvency II methodology

Risk.net, login required

"A number of politically-inspired compromises have led the Solvency II directive away from its market-consistent routes – so much so that according to Barrie & Hibbert’s Craig Turnbull and John Hibbert, the final confidence level for some liabilities is not one in 200, but one in 12."

Pensions: Value at Risk

The Actuary

"Celene Lee looks at the implications of new reporting standards for the measurement of risk in pension schemes and asks if there is a better means of communicating VaR."

Yield Curve Extrapolation: Longest reliable point

2011-04-19T12:33:59Z

It is profoundly worrying that the most basic valuation question we might ask of an insurer -- what is the value today of a fixed liability cash flow at some future date?-- is still unanswered less than two years ahead of Solvency II implementation.

Policymakers, regulators, firms, actuaries and accountants have belatedly focussed on a number of difficult questions including the choice of risk-free asset, the method for extending valuation beyond traded maturities and the possible impact of market liquidity premia on the way the valuation question is answered. This comment focuses on one specific aspect of the extrapolation – the reliability of forward rate estimates and whether we should switch focus from the liquidity of assets to the reliability of forward rates derived from market prices.

It’s apparent that there is considerable discomfort with potential variation in yield curves and their impact on the balance sheet where firms are exposed to large duration mismatches. Putting aside the rights and wrongs of exposing the economic mismatch between assets and liabilities (and I’m in the accounting camp here), I think there is a lack of appreciation of the difficulty and estimation error in establishing a reliable forward interest rate curve even where markets are Active and meet the ‘Deep/Liquid/Transparent’ (DLT) requirement (if we could decide what ‘DLT’ really means). This is important because I think the preference for a reduced longest liquid point (‘LLP’) is driven by the desire to stabilise the forward curve between valuation dates rather than any objective view on liquidity. This objective is not unreasonable given that, in practice, for durations beyond 15-years there can be a reasonably wide range of credible forward rates that will closely fit market prices. So, if your objective is not simply to produce the best fit to market prices at a single point in time but to produce a good fit and manage changes between valuation dates in a credible fashion, it may be more useful to think in terms of a ‘longest reliable point’ (LRP). Here, we might choose to extend the curve from 15 or 20 years, not because of liquidity considerations but because we can better manage the trade-off between providing a good fit to market instruments out to – say – 30 years and, additionally, ensuring that the behaviour of the curve beyond the LRP is credible through time.

Here’s an example. This compares the government forward curves produced by Barrie & Hibbert and the US Fed for end-December 2008:

A few points to note:

Both curves provide an extremely close fit to bond prices
The Fed (in common with other central banks) use methods which focus only on the traded part of the curve (why would they do otherwise?)
Generally, the spline approach allows for a richer description of the market and provides a marginally better fit
However, the B&H curve is additionally influenced by what we want to happen in the extrapolated part of the curve (which is not shown) and so the terminal gradient is managed, but this does not have a material impact on the overall fit to observed prices.

My conclusion is that we may want to think about shifting the discussion from a narrow focus on liquidity (which could be argued is a ‘red herring’) to a longest reliable observation on forward rates and management of the trade-off between fitting instruments beyond this LRP with stability of the curve over time.

The path really matters - Part III: A de-accumulation example

2011-03-11T14:58:32Z

Previous entries have highlighted the sensitivity of savings accumulation to the path or order of a set of investment returns. We concluded that – for accumulation – savers benefit from avoiding poor returns late in the accumulation period and that these returns will do less damage early in a savings plan because the invested fund is small. The analysis presented below demonstrates that the reverse is true for de-accumulation. In the example we analyse the same set of returns (mean 7% and standard deviation / volatility of 16.5%) over a 30-year horizon where the initial fund is €100,000 and an annual withdrawal of €6,000 is made. As before we now experiment only with the order in which the returns are delivered but leave the magnitude of returns unchanged. What difference does this make to results? Let us examine the terminal fund and the probability and timing of fund exhaustion i.e. where the fund is wiped out before year 30.

The chart below plots some possibilities for the growth in the underlying investment asset price. As before, you can see that all paths start and finish in the same place for a unit investment. The top (green) profile shows the path where we place returns in order from best to worst. The bottom (red) profile shows the reverse with returns ordered from worst to best. In contrast to accumulation strategies, de-accumulation will benefit from ‘early returns’ as under the green path. In this case, for the same set of returns, the ‘early return’ green path delivers a final fund of €+389K whilst the worst ordered outcome (‘early damage’) produces €-1.3M (although this result rather unrealistically assumes we ‘borrow’ at the unit rate of return). These differences are the exact opposite of what we saw for accumulation. Two additional random-ordered paths are also plotted on the chart.

Now consider two more obvious questions: firstly, what is the probability of the fund being exhausted before year 30?; secondly, what is the chance of the fund being wiped out in any particular year? The chart below helps to answer the question by analysing 10,000 possible (randomized) orderings of the returns. You can see that the assumptions suggest that the strategy delivers the €6,000 withdrawal over the full 30 years in approximately 70% of simulations. In the 30% of simulations where the fund is wiped out prematurely, there is a very high probability of the fund surviving beyond year 10 but around a 10% chance it is exhausted by year 20.

In these past three articles, I’ve highlighted some of the problems faced by savers. In future articles, we’ll take a look at some of the strategies used by product designers to help tackle the questions raised.

A comparison of alternative risk capital definitions

2011-03-07T10:09:02Z

There is no universal definition for risk capital. European early adopters of risk-based capital methods (including Solvency II) have adopted a measure which requires sufficient capital to remain solvent (on a market-consistent basis) with 99.5% confidence at a 1-year horizon. In the US, firms and regulators have leaned towards a quite different measure which depends on the behaviour of the balance sheet over its lifetime ‘run-off’. These alternative definitions are difficult to compare directly. Indeed, the theory behind these measures is not well developed. However, we can say some things about the different measures – their sensitivities and how they will behave relative to each other.

Consider a very basic example. Suppose an insurer holds a single unhedged position in a written 10-year put option with a strike at 90% of the current (total return) index level. We assume that the only source of uncertainty is equity risk and calculate some alternate measures of capital as follows:

VAR measures at 1, 2 and 3 year horizons
A run-off capital requirement (the PV of the shortfall at the specified confidence level)
A conditional tail expectation (CTE)

All measures are calculated at various confidence levels between 90% and 99.9%. The results plotted below are for the PV of capital in excess of the basic value of the option. I have highlighted 3 points which represent measures commonly used in different parts of the world:

1-year 99.5% VAR measure (14.9%)
95% run-off measure (15.9%)
98% CTE measure (17.6%)

You can see that, for this example, the capital requirements are broadly similar. Now, the quantity of capital required to support a risk exposure of this type will be critically dependent on the assumptions made about equity risk. For the 1-year VAR measure, the tail of the distribution of equity returns at the end of the first year of projection will be important. For the two alternative measures, the tail of the terminal 10-year distribution will be of most importance. For the analysis below we have assumed that equity returns follow a process where volatility is stochastic (i.e. it varies through time) but it is initialised at a neutral level. However, there are other assumptions we might make which, as you will see, have a material impact on absolute and relative capital requirements.

Consider the following alternatives:

Volatility is stochastic but its initial value is set to be LOW
Volatility is stochastic but its initial value is set to be HIGH
Equity returns are assumed to incorporate some ‘mean reversion’ which will limit the tails of long-horizon equity distributions.

The chart below plots the results from the first chart in the first column. You can see that the capital requirements are pretty consistent assuming constant equity volatility. Now consider the additional columns. When initial volatility is reduced (year 1 volatility falls from 20.5% to 17.6%) the 1-year VAR capital is reduced by nearly 20% to 12.3%. The run-off measure is very slightly affected by the lower year-1 volatility. In much the same way, an elevation in initial volatility lifts the 1-year VAR measure to around 25% and modestly raises the run-off measures. Finally, the ‘bubble’ plot assumes mean reversion so that the annualised volatility of the 10-year return falls to 16.4% and the 95^th percentile total return is moved from -42% (under the base case) to -26%. Unsurprisingly, this has a material impact on the run-off capital measures reducing them both to 3.9% (95% run-off) and 6.6% (98% CTE).

The story is a familiar one. 1-year VAR capital is very sensitive to initial market conditions. ‘Point-In-Time’ (i.e. conditional) estimates for the returns distribution will deliver far more variable (and pro-cyclical) capital requirements than ‘Through-The-Cycle’ (i.e. unconditional) measures. VAR capital will be sensitive to short-term movements in asset prices driven by changing risk and liquidity premia. By contrast, run-off capital measures will tend to be less sensitive to initial market conditions but very sensitive to the sources to which the modeller attributes volatility. If short-term price changes are attributed to transitory changes in risk and liquidity premia these assumptions will have a material impact on the run-off measures of capital requirements.

The path really matters – Part II

2011-03-02T15:29:51Z

This is a continuation of Part I

Consider (again) savings accumulation over a long horizon – 30 years – where we assume an individual saves €1000 each month. Now, let’s assume that we have a fixed set of returns available for the 30 years. The returns have an (arithmetic) average of 7% pa and a volatility of 16.5% so they are in line with the sort of assumptions that practitioners might make for a financial planning exercise. Suppose we now experiment with the order in which the returns are delivered but leave the magnitude of returns unchanged. What difference does this make to results – to the sum accumulated at the end of the 30-year period?

The chart below plots some possibilities for the growth in the underlying investment asset price. You can see that all paths start and finish in the same place for a unit investment. The top (green) profile shows the path where we place returns in order from best to worst. The bottom (red) profile shows the reverse with returns ordered from worst to best. As we have already seen (see blog part I) accumulation strategies benefit from ‘late returns’ as under the red path. In this case, for the same set of returns, the ‘late return’ red path delivers a final fund of €3.7M (IRR of 12.7% pa) whilst the worst ordered outcome (‘late damage’) produces €0.3M (IRR of -1.4% pa). These striking differences are exactly reversed for de-accumulation problems.

Two additional random-ordered paths are also plotted on the chart. In the chart below the full distribution of possibilities is shown for the accumulated fund where we randomise the order of the same fixed set of 30 returns and simulate a large number of possibilities. There turns out to be a 1-in-5 probability of achieving either more than €1280K or less than €680K. Given how much investors focus on both returns and measures of asset volatility it is striking how, when we nail down both these properties for a fixed set of returns, the outcomes for accumulated fund fall over such a wide range.

The lesson is that the path really matters and so advisers and savers need tools and strategies in order to understand and control these risks.

On Active Markets & the Solvency II ‘DLT’ definition

2011-02-28T03:37:03Z

In recent years market prices have taken on far greater prominence in insurance valuation and capital management as a new paradigm has been adopted by insurance regulators and accountants. This central role of market prices is recognised and, as a result, Solvency II regulators and international accountants (IASB/FASB) have drafted rules and guidance with the aim of defining which prices should be used and in what circumstances unreliable prices may be replaced with other valuation measures. However, the current rules and guidance are not well aligned (between SII and IASB/FASB) and there is a dearth of detailed thinking on how to turn aspirational regulation into practical reality.

Choices over which prices may be used (and why) will have a material impact on valuation and risk management actions. A topical example is the choice of ‘longest liquid point’ in the extrapolation of swap curves for SII valuations. The value of long-term cash flows and the connection between balance sheet assets and liabilities will depend on how the quality of individual instrument markets is judged.

The diagram provides a crude comparison of the terminology in use among European insurance regulators, accountants and European firms (CRO forum). The CRO forum and accountants’ definitions of Active markets and Hedgeable market risks look aligned.

..quoted prices are readily and regularly available from an exchange, dealer, broker, industry group, pricing service or regulatory agency, and those prices represent actual and regularly occurring market transactions on an arm's length basis.

For non-hedgeable risk (no Active markets), accountants make a distinction between model-based valuations based on the observability of the model’s inputs. Although this is a useful distinction, in practice its application will be rather grey. I would view the extrapolated price of a cash flow falling only 1 year beyond the liquid market as qualifying for level-2 whereas a 50-year extrapolation clearly falls under the level-3 definition. Most of us would struggle to say where the cut-off lies. More problematic is the additional layer of analysis applied by European regulators in defining reliable prices which additionally must trade in ‘deep’, ‘liquid’ and ‘transparent’ markets. Taking these definitions at face value suggests only a small set of instruments may pass the ‘DLT’ test. Where market prices are observable, but fail the DLT requirement, it is not clear how much weight should be placed on them in valuations. Strictly speaking, any non-DLT price will require the addition of a risk margin under Solvency II. The QIS 5 technical specification suggests that it is possible that non-DLT prices could be completely ignored (which creates a worrying potential disconnect between non-DLT assets on the balance sheet and liability valuations). A further requirement for ‘permanence’ which appeared in early versions of technical guidance has been removed (for the time being at any rate). Whilst the DLT definitions could be clarified further, the basic properties of an instrument market they seek to measure are:

Depth. The ‘normal market size’ (NMS) of trades. You might easily ask whether qualification as ‘deep’ require an absolute or relative amount?
Liquidity. This can be interpreted as a measure of the impact of abnormal trade sizes i.e. if an insurer aims to trade 10 x NMS, what impact on the price is expected.
Transparency. What information makes a market transparent? When must it be disclosed and how?

These words are somewhat different to the SII definitions but aim to convey the intention of the regulator. To help understanding of these properties of a market price, consider the chart below. It shows offers to buy and sell in a market where the amounts offered (or bid) are indicated by the size of the circles. It happens to be a market for bets on a tennis tournament. It is interesting because this ‘public order book’ provides a clear view of dealing intentions in a market so that a trader can understand the likely impact of a trade of a specific size. You can see that for Federer, it is possible to buy or sell relatively large amounts (of the bet) across a narrow price range. The market for Federer is both deep (large size) and liquid (low impact). Markets for Nadal and Djokovic are less liquid and, although there are bids and offers for Murray, only small trades are feasible and they will suffer a large impact cost.

In their report on the ‘Flash Crash’ of May 6 2010, the US CFTC provide a useful description of ‘depth’ as follows:

We use the term market depth.. to refer to resting orders that market participants place to express their willingness to buy or sell at prices equal to, or outside of .. current market levels. These orders are referred to as “buy interest” and “sell interest”, and the number of shares of each type of order interest represent “buy-side market depth” and “sell-side market depth.” Collectively, buy-side and sell-side resting orders form a “liquidity pool” against which incoming sell or buy orders can be executed.

Of course, you need to remember that this picture excludes the hidden intentions of dealers or investors who would offer liquidity but either do not bother to advertise through the order book or prefer to keep their dealing intentions secret. Dealers are notoriously cagey about revealing information to other market participants. The picture above gives an ideal view of what a market – where dealing intentions are publicly available – could look like. In practice, few markets offer this level of transparency. However, this view is useful because it can help us understand what we would like to measure.

So where are we now? To summarise:

Some clarification of language would be helpful.
The divergence between accounting and insurance terminology and emerging practice is worrying and has the potential to create an inconsistency between accountants’ fair vales and Solvency II technical provisions.
Whatever the result, firms will need to gather evidence on the reliability of the prices used in their valuations.
An informed discussion requires the development of objective, operationally-feasible measures of the various characteristics discussed in this article.

It’s a big job. We should start soon.

The path really matters – Part I

2011-02-18T14:55:48Z

Suppose you set out to accumulate savings over a long horizon – 30 years – and set aside €1000 each month. Now take a look at the two return paths shown in the chart below for a unit of investment over such a period. The upper (green) path generates a cumulative return of just over 6% per annum while the lower (red) path delivers a little less than 4%. Which would you prefer?

The obvious answer (to many of us at least) turns out to be a poor choice. For the profiles illustrated below, the particular paths shown would produce final accumulated sums of €758,000 for the green (6.1%) path and €1,016,000 for the red (3.7%) path. Of course, when you think about the timing of the cash flows, it’s no real surprise. For the red path, many of the poor returns fall in the early years when there is little contributed to the fund so they do little damage. By contrast, on the green profile the early strong returns are wasted since only a few contributions have been committed to the fund. Notice that for de-accumulation problems these effects would be exactly reversed so the poor early returns along the red path would be hugely damaging to a withdrawal strategy.

The lesson is pretty clear – for the purposes of understanding financial goals, the path really matters. It isn’t enough simply to focus on returns and their volatility. The sequence of returns will have quite different implications for different savers depending on their own pattern of contributions and withdrawals.

Finally, investment analysts often quote a ‘money-weighted’ or internal rate of return. This is the fixed return over the entire period that would produce the same cash flows. Of course, this depends on the returns and the timing, size and sign of cash flows. In this case the IRR is 4.5% for the upper path and 6.1% for the lower path.

A Comment on the Solvency II equity dampener: more change to come?

2011-02-16T15:20:43Z

In the Solvency II standard formula for an insurer’s Solvency Capital requirement (SCR), the standard stress adopted for equity risk for the purpose of the 5^th Quantitative Impact Study (QIS5) was 39%. This was somewhat less severe than what had previously been proposed by CEIOPS in its level-2 advice where a majority of regulators proposed a standard equity stress of 45%.

Under the proposed Solvency II framework this standard assumption is adjusted using a ‘dampener’ in order to avoid procyclicality. The stress test may be modified up or down depending on the where global equity prices are trading relative to their recent average. For QIS5, the dampener was calculated based on market prices relative to their 3-year moving average. At end-2009, equity prices were 9% below their 3-year moving average and so the equity stress was reduced by 9% to 30% for QIS5. At end-2010, equity prices were 11% above the 3-year moving average (MA) and so the equity stress would be adjusted up (by a capped 10%) to 49% on the same basis. The chart below plots the differences of the MSCI World Index used in CEIOPS’ studies to its 3-year MA and the resulting modified stress on the right-hand scale.

So, capital requirements to support equity risk would have been raised substantially over the year for those using a standard formula approach modified using the dampener. It is worth noting the contrast with market-based measures of equity risk. During the year, option implied volatilities (for a broad range of maturities) were broadly unchanged. Of course, we have argued in the past that a truly objective stress test following a stress test would be more severe not less severe as under the dampener. This is because – following equity stress – although risk premia tend to rise, this effect is offset by the typical increase in uncertainty and volatility (see link). In practice, it seems considerations of procyclicality outweigh cold analysis.

It is also worth noting another property of the dampener. The adjustment to the equity capital charge is described in both the Solvency II directive and guidance as being ‘symmetric’. Of course, it is symmetric in the sense that it can raise or reduce the capital charge by equal amounts. However, you can see from the chart that it certainly is not symmetric in the frequency of adjustment i.e. the adjustment upwards is applied far more frequently than the downward adjustment because equity markets tend to rise over the long term. The table below shows the proportion of time at the floor and ceiling for the equity capital charge and compares results with the CEIOPS ‘majority’ view where the dampener is based on 1-year MA and centred on a basic charge of 45%.

This is no mere accident of history. A very simple simulation of price paths shows virtually identical results:

I have no fundamental difficulty with the notion of procyclicality or the desire of regulators to limit its damaging impact. However, in an environment where equity values are reduced, it seems we are unable to face the economic reality and say the words: “policyholder security is reduced to x%; firms will rebuild their capital base to meet the 99.5% requirement over the next N years”.

If as for end-2009, the averaging period is to be selected to produce the answer firms can live with, perhaps regulators should just say so. Pretending the averaging is the result of objective analysis won’t help improve transparency or build faith in the insurance industry’s emerging capital measures.

Barrie & Hibbert in the press

2010-09-24T15:08:36Z

In the past few months, many Barrie & Hibbert experts have published articles in key trade publications. Here is a summary of our writings around the industry:

Insurance ERM

Calculating the Solvency Capital Requirement

Senior consultant Adam Koursaris authors a three-part series for Insurance ERM on the topic of calculating capital for solvency and regulatory purposes.

Related resarch: Solvency II Internal Models, Solvency II

The Actuary

Don't be Afraid... it's only Solvency II for Pensions

In this article, co-founder Andrew Barrie considers what a Solvency II approach might hold for pension schemes.

Related resarch: Solvency II

Life & Pensions

Understanding the Liquidity Premium

Craig Turnbull investigates liquidity premium in this article.

Related resarch: Liquidity Premium

Confessions of an investment banker

2010-07-06T08:27:53Z

I was an investment banker.

There we have it. Outed. Confessed. General applause please – it’s all part of my rehabilitation.

I will always be an ex-investment banker. I may choose to omit it from my CV, but it will be there: part of me, hidden, shameful.

Of course, I didn’t think of myself as one. I’ve never ever called myself one. Nobody who really knows me would recognise the label. My wife never knew....“Oh Andrew, he does sales or something”. Now she understands. Conversations with new acquaintances are gently steered away from Andrew’s career history.

I wasn’t a particularly successful investment banker. Not where it really counts for a capitalist – moolah, readies, spondoolies. I know that’s not an excuse, but it plays to my Scottish Presbyterian guilt. Perhaps I wasn’t clever enough or too lazy. My ego blames luck.

Back in 1986 when the job cards were being dealt out I picked the wrong one. I could have chosen proprietary trading or Japanese warrant sales or synthetic CDO structuring or securitisation analysis or a dozen others that have been spectacularly, if briefly, successful at some time over the past 24 years.

But no. For me it was ten years of institutional risk management. Sounded good – basically developing risk management solutions for the pensions and insurance industries. At my fingertips were a whole new array of instruments and techniques with which to revolutionise the market. Armed with some wizzy analysis by Mr H, my Global Megabank business card and a knowledge that only comes with the ignorance of youth, how could I fail? But I did.

The main problem was that the actuarial profession (let’s call it Actuaryland) and investment banking (Global Megabank) had entirely different philosophies about the nature of risk, how to manage it and, ultimately, its price. In Actuaryland equities returned 12% pa, every annum, interest rates were always going to be 8%. Even if this went a bit awry in the short term, the joys of mean reversion would eventually sort it out. The crash in 1987 followed by the unseemly rebound six months later only served to reinforce this thinking. Why would any actuary in their right mind pay the price of hedging demanded by Global Megabank and their Black & Scholes models and risk neutral pricing and no risk premium? If lunch wasn’t quite free in Actuaryland, it was pretty well subsidised. It’ll be OK: equities will deliver over 20 years.

Don’t get me wrong, there were some high points. Insurers were always up for a bit of regulatory arbitrage fun. For a few halcyon months the spectre of Minimum Funding Requirement (MFR) beat a few nervous pension managers to my door – before compromise put paid to the concept. But ultimately the gap between Actuaryland and Global Megabank was too great, so Mr B and Mr H left the big City for an Edinburgh bunker.

However, all was not well in Actuaryland. By the end of the 90’s the insurance sector was starting to uncover some unwanted consequences of their risk philosophy. A decade of falling interest rates begged serious questions about core products in the sector. Guaranteed annuity options and then with-profits failures led many to challenge their approach to pricing and managing risk. Could Global Megabank be right after all?

A new order

Then something bizarre happened. The UK’s insurance regulator took control, ordered their oversights to adopt a financial economic approach to risk and forced them to implement new processes over an incredibly short period. Solvency II extended these principles in scope and geography. Now Actuaryland has some of the smartest, most sophisticated risk managers in the financial services sector. Even more surprising is the accord amongst the different stakeholders and the convergence of approaches and philosophies deployed by regulators, rating agencies and accountants. However, is it not interesting that such a diverse group of professionals with different perspectives and objectives should embrace remarkably common valuation and risk measurement techniques?

Under strong regulatory pressure and deadlines even the more difficult issues such as liquidity premium (an important component of liability discount rate), where practice for the past 20 years has been diverse, have been debated and a common, pragmatic approach agreed by the industry.

But what about pensions?

Contrast this with the pensions sector. The approach here has been to develop a different lens through which each stakeholder views the world. Each lens has varying levels of clarity, going from a buy-out basis which shows the pension scheme in all its glory or pain through to accounting and technical provisions basis typically hazes the lens a bit.

Further, the standards applied to each of these approaches can vary significantly from scheme to scheme, actuary to actuary and accountant to accountant. Add this to the fact that we now have different advisers to sponsors and trustees and it is no wonder that many schemes struggle to get common agreement on management strategy . Unlike the insurance sector, there has been no regulatory driver for change and hence little incentive towards adopting a common approach to valuation and risk management.

However, we are now seeing clear signs that there are a number of influences coming to bear which will bring sharper focus and greater consistency in pensions-related modelling and risk management:

Technical Actuarial Standards (TAS). The Board for Actuarial Standards are currently in consultation and delivering a series of standards with the aim of independently setting these for actuarial work. This will ensure appropriate transparency that I believe will improve consistency and generally raise the standards and debate within the actuarial profession.
Solvency II. Many insurers, who are obliged to measure their core business risks are now turning their attention to other risks such as their DB pension fund and active investment risk. With a need for consistency, insurers are now starting to adopt Solvency II valuation and projection standards for these other risks.
EC regulations. By the time you read this, the EC may have published a much anticipated green paper on Occupational Pension Schemes. This paper is expected to have a Solvency II spin on it, but until it is published we can only speculate as to its content.
The questions being asked of pension funds are quite different now than a few years ago. Many relate to short-term balance sheet risk and cash flow requirements rather than long- term funding. Answering these questions creates new challenges for modellers — the calibration, time horizon, granularity of analysis, capturing existing market conditions, pricing banking and insurance solutions, etc.
Run-off. With an increasing number of DB schemes now closed to new business, they find themselves in a maturing and run-off position. This is similar to insurance products such as with-profits (which are also essentially closed to new premiums), in that the challenges are different from growing funds where significant future contributions or premiums can afford management a more liberal investment approach.
Technology. A significant barrier to more funds getting better, timelier analysis at a price they can afford is the labour-intensive administrative, valuation and modelling environment. This has meant that only the largest of schemes can afford anything more than an infrequent valuation. However, we are now seeing a growing number of platforms and techniques that will change this. Real time valuations will allow stakeholders see the impact of market risk drivers on their assets and liabilities.

The consequence of the developments outlined above will be a growing convergence between the valuation and risk management philosophies of insurers, pension funds and banks. Of course, these are all very different industries, with their own specific risks and needs. Adopted practice will be tempered and shaped by these differences. But we can expect that there will be large areas of commonality in approach and standards.

A brave new world

The pensions industry is already rising to these challenges and opportunities. Consultants are now building teams with some of their smartest resources, learning from their insurance and banking cousins and re-using much of the architecture already developed there.

I am looking forward to welcoming a new era in pension scheme risk management. This time assuming that the world is always changing and won’t always look great over the long term. Hopefully this will ensure we are prepared to deal with the issues that may be thrown our way.

At Barrie & Hibbert we are playing our own part in these developments, sharing the knowledge we have gained in life insurance risk management to promote the same high standards in the pensions industry. Together with our pensions clients – consultants, sponsors, trustees and asset managers – who are already sophisticated and demanding users of our pensions risk management solutions, we will work to support the sector to meet the challenges ahead.

If you are interested in finding out more about our services then please contact us at info@barrhibb.com.