Insurance Insights Q1 2026: Strategic asset allocation using updated capital market assumptions

Invesco’s Capital Market Assumptions (CMAs) are updated on a regular basis and incorporate the latest market developments. These are often primary inputs for asset allocation analyses, especially when assessing these over a longer time horizon. In this section, we outline a practical approach – comparing changes in expectations over time (whether up or down) on a portfolio level and then look at whether new asset classes can help in improving the overall risk-return profile.

For the purposes of this illustration, we have used Singapore’s Risk Based Capital 2 (RBC 2) framework for assessing the relevant capital charges as an example of a generic risk-based capital regime (and use the US dollar as the base currency). We observe the trend of convergence to similar frameworks across the APAC region and so we feel the direction of changes on allocations under one risk-based capital regime can still be meaningful and relevant for other APAC countries, at least in terms of direction of change if not absolute levels.¹

Expectations around return and yield assumptions are an important input into any asset allocation exercise. The added element is assessing how these asset class expected returns stack up against potential capital charges – the insurer may consider the relative attractiveness of various asset classes from both an absolute and an expected return-to-risk perspective. Not considering both these aspects may lead to a less efficient portfolio. Striking a balance between higher risk and higher reward asset strategies, while suitably managing the asset-liability profile is key within a portfolio setting. Therefore, insurers will assess these (often) opposing factors and construct a portfolio accordingly. These parameters, of course, are constantly changing depending on market conditions, and insurers need to continually seek out relative advantages between asset classes. Hence, it is important to assess portfolios across several dimensions and ensure that portfolios are re-assessed on a regular basis to ensure the objectives are still valid and achievable.

Updating Capital Market Assumptions (CMAs) in the analysis

In this example, we start with a generic asset allocation comprising the following asset classes (represented by the indicated indices/proxies below). This allocation is meant to broadly represent a plain vanilla portfolio: government bonds to manage duration, credit exposure for yield enhancement, and listed equities, including some real estate exposure, to provide potential upside/alpha opportunities.

The charts below (Figures 1 and 2) compare risk-return profiles of the generic portfolio above using the December 2024 CMAs and the latest December 2025 CMAs (or the September 2025 CMAs in case December 2025 are not available for some of the asset classes). This can help isolate the impact on the expected yield/return driven mainly by changing capital market assumptions.

Figure 1 (left) shows the portfolio characteristics on an economic basis and Figure 2 (right) shows the characteristics on an RBC basis. The purple lines represent the frontiers with CMAs from December 2024 and those in blue represent the CMAs as of December 2025 (or the latest available CMAs).

We observe that there is a decrease in the expected return of the portfolio over a 10-year horizon, reflecting updated capital market assumptions/yields, with some changes in expected economic volatility and RBC charges (reflecting slight drifts in the underlying representative indices). If we look into the data, we find that the decrease is due primarily to the downward move in yields from a new money perspective, while some of the growth asset assumptions have also been lowered. This reflects a constantly shifting market environment and views and expectations evolving over time, incorporating additional information from the past year as well as some forward-looking elements.

The effects of adding more asset classes to a portfolio

As part of the asset allocation analysis, the next step is to consider asset classes that may be able to improve certain parameters of the portfolio. As we highlighted earlier, while capital charges for certain asset classes might be relatively high, their correspondingly higher expected returns can still make them relevant. As part of a portfolio, the benefit of diversification may also help with generating potential efficiencies.

We continue our analysis by taking the above starting portfolio and adjusting it to include new asset classes and then re-examining the risk-return profile with our portfolio analytics tool (Invesco Vision²), based on the latest CMAs.

Having looked at the components of the existing portfolio, we have considered increasing the exposure to private markets to a limited extent – and specifically those asset types that we feel can act as potential complements to existing exposures. Accordingly, we have slightly reduced exposure to global high yield and allocated a corresponding amount to private credit, reduced exposure to public REITs and allocated to value-add real estate, and finally, reduced exposure to public global equities and allocated to large leveraged buyouts. Our updated portfolio now comprises the following exposures, represented by the indicated indices/proxies below:

We then compare the risk-return profile of this adjusted portfolio to the original portfolio (using the latest available 2025 assumptions). The charts below demonstrate changes to the efficient frontier of adding new asset classes and indicate where the original and enhanced portfolios lie.

Figure 3 (left) shows the portfolio characteristics on an economic basis and Figure 4 (right) indicates the characteristics on an RBC basis. The blue lines represent the starting portfolio and the green lines represent the adjusted enhanced portfolio – both sets using the CMAs as of December 2025 (or the latest available CMAs).

We observe that there is an improvement in the return profile of the adjusted enhanced portfolio — that is, the green dot representing this enhanced portfolio has moved upwards compared to the blue dot which represents the starting portfolio. The adjusted portfolio shows a very slight reduction in risk (economic basis), with a small increase in the RBC charge estimate – the latter driven primarily by the new exposure to private value-add real estate (which has a slightly higher charge when considering embedded leverage – to be conservative).

Overall, the enhanced portfolio looks reasonable with the higher expected return offsetting the slight increase in estimated RBC charge. We would highlight that this result has been obtained with small adjustments to the portfolio (+/- 1% to 2% across specific asset classes). Additional adjustments can be made to focus on other key parameters as required/desired. Further, we would like to highlight that even long-term return assumptions are subject to review and change (especially if there has been a significant move upwards or downwards in markets in the recent past) – therefore, any adjustments to be made should be incremental in nature, rather than a large-scale re-allocation – of course, assuming other asset-liability management metrics remain well-contained.

Through this re-allocation, we have been able to improve the portfolio’s expected return slightly by selectively adding asset classes that have relevant risk-reward characteristics, and, importantly, that are complements to existing exposures. Increasingly, we are finding that this means a reduction in exposures to public/listed assets and a corresponding increase in private/unlisted assets to generate additional pick-up. Of course, we would highlight that such sources of additional premium need to be analyzed and insurers need to ensure that key parameters (such as liquidity) remain well managed and in accordance with risk appetites. Private assets can be a good adjunct to public asset classes and can help bring about additional diversification – although these come with additional risk elements that need to be carefully assessed and understood. This type of analysis opens up the potential for further adjustments to the asset allocation – and this is designed as an iterative process.

Insurance portfolios and potential routes to implementation

This strategic asset allocation review often brings up the issue of how best to implement any such changes. While insurers may prefer segregated mandates, driven in no small measure by updated regulations/financial reporting standards, gaining access to such new asset classes (especially private assets) could be time and resource intensive. We are finding that insurers are looking towards easily tradeable investments when assessing how best to bridge the gap between gaining almost immediate exposure and developing a longer-term private asset exposure buildout (including, but not limited to, laying out a roadmap, considering specialist managers, and deploying capital over time). Exchange-traded funds (ETFs) have the potential to provide market beta access to private asset classes (such as broadly syndicated bank loans, high-grade structured credit, for example) in a low cost, liquid, and transparent manner. ETFs generally cover a wide range of passive and active strategies and can assist insurers in transitioning to their long-term asset allocation in a cost-effective, efficient manner.

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Investment risks

The value of investments and any income will fluctuate (this may partly be the result of exchange rate fluctuations) and investors may not get back the full amount invested. Diversification and asset allocation do not guarantee a profit or eliminate the risk of loss.

Invesco Investment Solutions (IIS) develops Capital Market Assumptions (CMAs) that provide long-term estimates for the behavior of major asset classes globally. The team is dedicated to designing outcome-oriented, multi-asset portfolios that meet the specific goals of investors. The assumptions, which are based on 5- and 10-year investment time horizon, are intended to guide these strategic asset class allocations. For each selected asset class, IIS develop assumptions for estimated return, estimated standard deviation of return (volatility), and estimated correlation with other asset classes. Estimated returns are subject to uncertainty and error and can be conditional on economic scenarios. In the event a particular scenario comes to pass, actual returns could be significantly higher or lower than these estimates.