Liability-Driven Investing

Some readers might be thinking they have heard this all before. Is goals-based investing not almost the same concept as liability-driven investment (LDI), the buzzword of the pension industry over the last five to ten years?

Broadly speaking, both processes involve the development and monitoring of an investment strategy to meet certain predefined goals. However, LDI strategies have traditionally resided in the defined benefit fund world, where employers needed to derive certainty that they could adequately fund the liability of their member’s post-retirement income requirements. This helped manage the impact on their balance sheets.

As goals-based investing has evolved, though, it has become increasingly clear that LDI investment strategies could provide a critical building block in enabling defined contribution funds to provide more targeted outcomes to individual members.

LDI unpacked LDI asset managers reduce or eliminate unrewarded inflation and interest rate risk for investors with well-defined liabilities or targets. What does this mean? Consider Thabo saving for his retirement in five years. By applying actuarial techniques, we can estimate what salary Thabo will earn across these five years and therefore estimate how much money he will save toward retirement. We also know he doesn’t want to take a large cut to his monthly income when he retires. The trustees of Thabo’s pension fund try to design an investment strategy that will generate a suitable retirement income out of these contributions. Two important risks that could derail this planning (before or after Thabo’s retirement) include:

1. Rising inflation: inflation (increases in the cost of living) could rise rapidly, outpacing investment returns and eroding the real value or purchasing power of Thabo’s income.
2. Lower returns: the return available in the market could fall. Therefore the investment return the trustees have planned on earning for Thabo could erode.

LDI asset managers address these risks for investors.

Investing in assets that guarantee actual inflation and a fixed return until the time Thabo needs each income payment would protect against these risks. An example of such an asset is an inflation-linked bond. Inflation-linked bonds pay a stream of cash flows increased by whatever inflation turns out to be. An inflation-linked annuity is a second example which would pay Thabo a constant monthly income increased by inflation. The inflation-linked annuity will not be available for purchase by Thabo until he retires. Both assets are guaranteed to keep up with inflation and to deliver a fixed real return in excess of inflation.

Critically, the trustees (or Thabo, after his retirement) need not invest all of his assets into these investments. A portion of his assets could be invested to provide some protection against inflation. Goals-based investing tells us how much Thabo should commit to LDI assets. LDI managers use these concepts to reduce the risk that investors (such as insurers or pension funds) do not keep pace with inflation or earn an adequate return. In fact, technology exists that allows LDI managers to use only a portion of Thabo’s assets to protect his entire portfolio against reductions in available returns. These technologies are not as effective as locking in the required returns with all of his assets, but protect him against most of the risk of reductions in the return available.

These risks are technical and hence many people saving for retirement don’t think about them. They can and do cause major fluctuations in the incomes that pension fund members retiring at different times receive.

We require a different mindset to get our heads around the fact that a negative investment return could still give a higher pension income in retirement if annuity prices reduce by more than that negative return.

The amount and exact type of risk control required depends on the timing and nature of each investor’s targets or liabilities. It has therefore only been economically viable to apply LDI technology to very large investors such as insurance companies promising to pay annuity payments to clients or defined benefit pension funds who have promised to pay inflation-linked pensions to their members. This is likely to change though as providers use automation to apply these technologies to individual DC fund members.

The chart below shows how various asset managers in the LDI industry have outperformed their benchmark liabilities. For each manager, we have assumed they started with a portfolio equal in size to their liability. We then plot their cumulative outperformance of liabilities. Across the industry we see that all composites have outperformed their liabilities despite this covering an incredibly volatile time for interest rate markets. We also see that LDI does not necessary preclude an investor from earning alpha (outperformance), though the primary purpose of these portfolios is to track liability movements. In general, the larger the alpha earned the greater the volatility of the outperformance observed. In all cases we see good downside protection relative to liabilities.

How is LDI being used internationally in DC schemes using goals-based investing?

Automation is allowing funds to apply goals-based investing at an individual level to their members. Instead of designing a single investment strategy that would suit the average member, funds can now set replacement ratio or retirement income targets or objectives for their individual members. Globally there is an emerging trend of funds optimising the investment strategy of each member to these targets, developing a mix of assets appropriate to their individual circumstances. For example, a member who chooses a very low contribution rate might justifiably need to take on more investment risk to stand any chance of receiving a reasonable retirement income.

Some systems allow further personalisation using member engagement through an automated online process. The member we described might be highly risk averse and may indicate they do not want an aggressive investment strategy. Instead the member might be satisfied with a limited retirement income.

LDI is used within this framework of targeting an incomerelated goal to manage risk.

LDI makes up one of the asset classes or building blocks available to these investment strategies. More specifically, it is the lowest risk asset class in the context of an income target, much like cash would be the lowest risk if your aim was not to make any capital losses.

The bulk of the value-add in these systems is likely to flow from the individualisation (consideration of each member’s financial circumstances) and the use of appropriate goals, such as retirement income. The use of LDI assets adds a further (marginal) increase in overall investment efficiency relative to the use of conventional bond portfolios

What can LDI teach us about the successful application of goals-based investing in South Africa?

Although LDI is an asset management style and goalsbased investing an investment framework, the two have a lot in common. Both are technically complex concepts that most individuals may struggle to understand or value. Both deal with an intuitive concept (investing relative to your aim or goal) but both are notoriously difficult to measure or compare in a simple way. Unfortunately, the take-up of LDI in the DB pension market in South Africa was slow, spanning a number of years. The greatest challenge was the technical complexity of the solution and the lack of complete risk elimination. However, these are two characteristics shared with goalsbased investing. LDI taught us some useful lessons that will apply to goals-based investing:

• It took time for trustees to become comfortable with LDI and it is likely that goals-based investing will be no different. A core of progressive boards with large governance budgets adopted this technology early on, but many boards preferred to wait for the technology to be perceived as more mainstream before taking it on board.
• Reliable, comparable return and risk figures were important to most trustees. Early attempts to measure performance were fraught with problems. Inappropriate performance comparisons surfaced, which many trustees used due to the apparent certainty and simplicity of these measures.
• As with any highly technical product, it was easy for managers to manipulate clients’ views of their skill and the value of this technology and the role it would play in their broader portfolio.
• Like any other investment management style, performance figures alone are not sufficient to choose a manager. An understanding of what drove that performance, an understanding of the manager’s processes, people and skills and an understanding of what the investor is truly after are required.
• Obtaining specialist advice early on in the investment process is in members’ best interests and can save a fund from misaligned expectation or poor service delivery. The ultimate provider of a product should not be entrusted with objectively evaluating their own product relative to the market.

What LDI won’t teach us

Virtually all goals-based investing relies on a process known as stochastic simulation. Stochastic simulation looks at thousands (or millions) of possible outcomes an investor can face across the rest of their life, calculating the retirement income or other objectives they could receive in each. This allows one to control risk effectively for an investor.

For example, Sarah might know that she would like to target a retirement income of R10 000 a month, but she also knows she cannot survive on less than R5 000 a month. Stochastic simulation allows a provider to develop the best strategy that meets both of these requirements. For example, the strategy might have an expected average income of R10 000 a month and a negligible probability of an income below R5 000 a month.

It is important to remember that a goals-based investment strategy is chosen in advance, based on forecasts rather than actual results. The strategy chosen is therefore the right or wrong choice on a prospective basis, not based on whether it outperforms another strategy across a specific period in hindsight. In fact, there is very little we can learn about the strategy we implemented, relative to the objective we set by monitoring performance against traditional benchmarks.

This is not to say you set the strategy and walk away. The same process needs to be repeated to tweak the direction to maintain the optimal strategy.

Monitoring performance of the underlying asset managers being relative to their benchmarks remains important though to evaluate the value these add or detract. The same principles apply as are currently applied in this regard. Within a goals-based investment framework, the principles used to choose between active and passive management or to select a style of active management would also still apply as before.

Different goals-based investing objectives exist. Some approaches aim to minimise the probability you retire with an income below a certain level. Other frameworks aim to prioritise spending objectives (such as current spending, retirement income and healthcare spending) and take on risk aligned with the value of each objective. How does one compare these frameworks and ultimately choose one? NOT by comparing historical investment performance. This would be like choosing between medical and motor insurance based on which you have successfully claimed from in the past. It would be far more useful to consider whether you can afford the premiums for each and whether you could financially tolerate the loss of your car or expensive medical procedures. Trustees should consider what objectives they believe would suit their membership. In doing so, the following will play an important role:

• The needs of their members.
• Philosophical views held by the board might inform one objective being deemed ‘more appropriate’ as a target for members’ savings. For example, should members who are deeply underfunded be directed to ‘go for broke’ or preserve the (inadequate) retirement income they can look forward to? How will global coverage by a larger state pension change this?
• The financial acumen, or otherwise, of the membership.
• Data limitations and access will become increasingly important as investment strategies become more individualised. Funds with limited access to their membership and poor existing data may want to retain an ‘average member’ approach to setting investment strategies.
• Legislation and minimum standards will also become increasingly important. We have already seen this highlighted in the US where strong recommendations in this regard have been made by the Government Accountability Office.
• Eventually it will be possible to use stochastic modelling to compare different frameworks or objectives and different solutions to these. This is currently not possible. This approach will also remain problematic for as long as these solutions and frameworks remain proprietary products.

Conclusion

Goals-based investing is not a new idea. The concept of designing investment strategies optimally around one’s liabilities or objectives is well established. The technologies available to do so have evolved over time. For example, twenty years ago the use of stochastic asset-liability modelling was not common in pension funds. Today most DC funds either use asset-liability modelling exercises themselves or use portfolio ranges that have been designed using these techniques. The next major innovation in this regard is taking this technology to the individual DC member. Through advances in technology, it will soon be possible to apply a goals-based investment framework to each individual member, accounting for their financial circumstances.

LDI will form part of this solution. LDI can remove or reduce some of the unrewarded risks DC members are exposed to. This includes protecting them against the risk that available investment returns fall in the future or that very high inflation rates erodes the purchasing power of their savings. LDI assets are therefore an effective building block within a goals-based investment framework that should not be ignored.

LDI will also play a more conceptual role in establishing goals-based investing within the minds of DC members. Thanks to the high hedging efficacy of LDI, it will be possible to offer members soft guarantees – levels of retirement income they are highly unlikely to fall below. This is simply not possible without the use of LDI and individualised investment solutions. Offering something like this is already realistic for members within the last ten years of retirement. Certainty is something members do understand. The same is not true of the more complex and technical benefits such as investment efficiency brought about by using LDI assets.

In truth, attempting to fully guarantee a retirement income would be too costly for most members. The industry will, however, be able to use this technology to limit downside, offering soft guarantees on lower limits to retirement income. This remains useful and could dramatically reduce risk and anxiety for members. It is our belief that members will better understand what level of retirement income they need and the probability associated with reaching that goal. This could be highly effective in a semi-automated, individualised advice framework.

In closing, the goals-based investing framework in our view better manages member expectations in respect of outcomes, better aligns to members’ actual needs through optimisation and contains implicit advice which is suitable and can take account of changing circumstances.