• Liquidity
  • Fixed Income
  • Insurance

Liquidity optimisation for insurers

Building a bespoke portfolio solution

9 July 2024 6 minute read
Author

In the third part of our liquidity optimisation series, we look at how bespoke liquidity portfolios that take into account the interplay between different assets can suit the needs of insurers.

Important information

Read this article to understand:

  • The key features of effective liquidity solutions for insurers
  • The importance of “the interplay effect” between assets
  • Liquidity, capital-stability, yield and capital-efficiency considerations

The topic of liquidity has come into greater focus in the wake of recent market events and regulatory changes. Regulators around the world are asking investors to hold more liquidity or placing greater emphasis on existing rules. Recent liquidity risk events have pushed many investors towards higher liquidity allocations.

The first article in our liquidity optimisation series addressed the amount of liquidity investors need to hold. You can find out more on this topic in “A bigger splash”.1 In our view the amount of liquidity any investor should hold represents a delicate balancing act between potential liquidity needs and wider allocation choices. No easy task, but one that can be approached through a combination of scenario analysis and good liquidity-risk governance. Liquidity needs to be valued appropriately in a broader strategic asset allocation.

The second article in our series addressed the characteristics of liquidity investors need to hold. You can find out more on this topic in “Finding the right blend”.2 For many investors a liquidity pool may just mean cash deposits with banks and/or government bonds. While such an allocation may be intuitive, it is not necessarily optimal. Investors need to consider whether the liquid assets they hold are the right assets for their needs.

In this the third article in the series, we provide a case study of how one of our clients worked with us to build a bespoke liquidity portfolio. The investor in question, a multi-line insurer, had complex liquidity needs and a sophisticated understanding of liquidity risk and liquidity assets. We worked with the client to design and build an optimised portfolio factoring in liquidity, capital-stability, yield and capital-efficiency considerations.

Case study: Scale liquidity optimisation

A client approached us with a request for a liquidity solution based on an extensive set of requirements.

The client profile

  • A multi-line insurer with sophisticated knowledge of investment strategies and instruments, including advanced liquidity-risk management expertise.
  • Potentially significant unpredictable cashflow needs, resulting in a high liquidity need. Or to put it another way, this client had a large operating liquidity segment. Beyond this operating segment the client needed robust liquidity laddering in the reserve and strategic liquidity segments to allow prompt replenishment of operating liquidity if there were a major liquidity call.
  • Focus on high credit quality: minimum credit rating of “A”, to minimise risk of adverse price movement at point of need.
  • Sensitive to volatility: no appetite for interest-rate risk duration and limited appetite for spread duration (maximum of 1.5 years),
  • Limited appetite for non-base currency exposure and requirement for full hedging.
  • Sensitive to insurance capital requirements – the UK Solvency II regime.
  • Need for through-the-cycle-yield exceeding cash rates.
  • >£1billion portfolio.

The process

We operate an iterative process when designing client mandates. We typically find that client requirements may evolve during the process as the client considers the interplay between the different factors relevant to liquidity portfolio design.

We maintain a set of liquidity asset class-specific risk and return assumptions

We maintain a set of liquidity asset class-specific risk and return assumptions. Unlike the conventional, index-based risk-return assumptions available in term markets, short-term markets require more work. These markets are opaquer than term markets and have fewer indices.

We therefore build and maintain bespoke datasets based on inputs from our traders and specialist portfolio managers active in each sub-asset class. We periodically test our assumptions against latest market conditions, updating as needed.

We feed these assumptions into our proprietary MATLAB-based liquidity optimisation tool. This tool provides significant input flexibility, allowing us to consider a range of parameters.

Figure 1: How we design and build bespoke liquidity portfolios

How we design and build bespoke liquidity portfolios

Source: Aviva Investors, April 2024.

The portfolios

We generated a series of ten different portfolios with differentiated profiles to share with the client.

The relationships between returns and underlying risk characteristics are not necessarily linear. Conversely, using multiple levers can offset the effects of other levers.

For example, as shown in Figure 3, portfolios seven and eight have approximately the same level of liquidity, but portfolio eight can potentially generate a higher excess return. This is an important observation. It highlights the interplay effect central to developing robust liquidity portfolios.

Figure 2: Risk-return profiles

Past performance is not a reliable indicator of future returns.

Source: Aviva Investors, April 2024.

Figure 3: Selected portfolio characteristics (per cent)

Past performance is not a reliable indicator of future returns.

Source: Aviva Investors, April 2024.

The outcome

  • Portfolio two: Like a “standard” money market fund (MMF), with very high liquidity and a lower return target.3
  • Portfolio eight: Longer spread duration and lower liquidity. Tolerates some limited exposure to “A” category assets, contributing to a higher performance target.
  • Portfolio ten: A lower liquidity solution both in terms of the level of liquidity and settlement times of the instruments held (most with settlement two days after the trade [T+2], as opposed to most same day [T0] or next day [T+1] in the prior two portfolios). Increased performance target driven by exposure to return enhancers such as AAA-rated asset backed securities (ABS). The ABS we selected were all in the simple, transparent and standardised (STS) format, therefore benefiting from low spread capital charges under Solvency II.

Conclusion

Ultimately the client selected a higher liquidity portfolio which was close to portfolio two, albeit with a higher allocation to AAA STS ABS. This decision balanced liquidity with yield enhancement from the AAA STS ABS, while delivering a high level of capital efficiency.

The key insight for the client was the interplay effect. The client well understood the asset classes involved; what was revealing was how the asset classes worked together to build a diversified, optimal portfolio. With this interplay effect in mind, the client needed an investment manager with the breadth of capability and expertise to manage exposure to these asset classes. We believe many clients could benefit from such an approach.

The information provided is for illustrative purposes only and should not be construed as an investment recommendation.

References

  1. Alastair Sewell, “A bigger splash: How much liquidity do I need?”, Aviva Investors, July 2, 2024.
  2. Alastair Sewell, “Finding the right blend: Optimising asset allocation in liquidity pools”, Aviva Investors, July 9, 2024.
  3. A “standard” MMF is one of the four MMF types available in Europe. It is subject to the full requirements of the MMF regulation. It differs from short-term MMFs in being able to assume slightly more duration.

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