Position portfolios for the unexpected

The views expressed are those of the author at the time of writing. Other teams may hold different views and make different investment decisions. The value of your investment may become worth more or less than at the time of original investment. While any third-party data used is considered reliable, its accuracy is not guaranteed. For professional, institutional, or accredited investors only.

The more things change, the more they stay the same. Last year’s Insurance Outlook highlighted slowing growth, elevated inflation and rates, policy uncertainty, and geopolitical turmoil. I expect the themes to rhyme in 2024, but it feels like the left tail continues to grow, even if a “soft landing” is still on the table. Our macro team has been steadfast in their view that we face structurally higher inflation, shorter and more volatile cycles, tight labor markets, and shifting supply chains. Central banks will contend with a wider range of circumstances and their policy responses will be more likely to diverge. In short, we appear to be in a world that’s very different from the post-GFC era, with more volatility, dispersion, and unknowns.

In response, I think insurers managing investments will need to be nimble, dynamic, and forward looking. They should rely less on history and more on what could happen. Importantly, this is not a risk-off exercise — it’s about looking for opportunities to make the most of capital while also taking steps to help protect against bubbles and shocks. Specifically, as I discuss in this year’s Outlook, I think insurers should focus on two critical themes in their 2024 investment planning:

1. Doubling down on diversification — Look across and within asset classes for diversification. Also, consider “implementation diversification” (e.g., active and passive or public and private market) and be attentive to secondary benefits (e.g., diversifying with assets that also hedge inflation risk).

2. Rethinking risk — Search out gaps in your risk assessment, including geopolitical and default risk. Artificial intelligence may also warrant special attention — from both a risk and an opportunity standpoint.

Doubling down on diversification

In the post-GFC era of easy money and relative economic prosperity, insurers, who often invest with a long-term view, were rewarded for simply holding on to their risk assets and weathering occasional bouts of market volatility. In other words, diversification didn’t matter much. But as noted, the future may hardly resemble the recent past when it comes to the directionality of market returns. Asset prices may experience swings in correlation, and insurers whose portfolios are dominated by investment-grade fixed income and equities will need to be prepared for multiple outcomes and less linearity.

For diversification, insurers tend to lean on the low or negative correlation between bonds (reserve assets) and equities (surplus assets). But recently, these exposures have moved together in a major way — beginning with the nightmare that was 2022 asset returns — and they may be more likely to do so in the new macro regime (Figure 1).

Figure 1

Moving into the new year, I challenge insurers to consider diversification in a much more methodical and intentional way, looking for opportunities across and within asset classes, as well as by implementation approach. To help, Figure 2 offers a diversification checklist. Some of the trades have become more common in recent years (e.g., securitized assets to diversify from credit) while others have faded considerably (e.g., US insurers have focused less on investing outside their domestic market).

Figure 2

Cross-asset-class diversification

For insurers, regulatory, liability, and balance sheet considerations can result in a heavy overweight to fixed income, and investment-grade fixed income in particular (which has made insurers the envy of other asset owners in the recent yield environment!). But insurers still invest in other asset classes and need to think about those choices in the context of diversification and not just return potential. These decisions can have substantial implications for portfolio liquidity, beta exposure in inflationary and stagflationary environments, and overall volatility, and should be the first step in examining a diversification strategy.

Intra-asset-class diversification

Stale allocations to a small group of sectors or styles are not a recipe for success in rapidly evolving markets. Insurers should take a more dynamic approach and start the exercise by reviewing reserve assets and surplus assets separately.

Reserve assets

For reserve assets, insurers may want to consider targeting:

A correlation of 0.35 or below between AAA rated collateral loan obligations and intermediate A or better credit
A correlation of 0.32 or below between longer-duration tax-exempt municipals and ABS/CMBS

Bear in mind that these targets don’t entail the use of exotic strategies or traditional diversifiers like commodities; these are typically high-quality assets considered appropriate for backing reserves. It’s also worth noting that the increased use of private credit (private placements in particular) as a reserve-backing asset and not a “risk on” investment can potentially enhance diversification through the valuation process and also the underlying sectors, industries, and issuers, some of which don’t utilize the public market at all.

Surplus assets

I think insurers should first ensure they are not “double dipping” equity beta by investing in high-yield bonds and public equities if they don’t have adequate risk tolerance. High current income has occasionally masked how closely related the total returns from high-yield bonds are to equity market returns; we estimate a correlation of close to 0.7 between the two (Figure 3).

Regional diversification should be another area of focus. In recent years, we have seen US insurers pull back from non-US markets, and that trend continued in 2022, with assets declining 17% or nearly US$80 billion.¹ This may reflect recent uncertainty about markets outside of the US, but I don’t think it should necessarily be the path forward for insurers looking to capture alpha. I am not advocating for substantial exposure outside of an insurer’s domestic market or the currency of liabilities, but I do think it is worth considering the risk of being totally reliant on a single economy for success (a risk that is amplified in a deglobalizing world).

To help insurers consider various diversification opportunities, Figure 3 highlights our assumed correlations for some of the major asset classes, based on our capital market assumptions (see “Important disclosures: Capital market assumptions” at the end of this paper).

Figure 3

Implementation diversification

Decisions about how to gain asset-class and intra-asset-class exposure can go a long way in creating a return profile consistent with an insurer’s risk tolerance. Market-efficiency arguments for using a portfolio’s largest active bets in areas most ripe for dispersion are by now well understood. But the capital market and portfolio strategy landscape has evolved considerably, creating new opportunities to dial up or dial down factors that can impact expected risk/return. This includes the aforementioned public versus private decision, where delayed mark-to-market valuation methods in the private markets may provide an offsetting element to an insurer’s financial statement return profile in the event of a major public market sell-off in a single period.

Insurers can also decide how much dynamism to build into individual portfolio strategies. For example, they may want to allow a portfolio manager to opportunistically incorporate equity strategies or fixed income risk assets depending on the risk/reward trade-off, potentially creating a smoother outcome compared with passively drifting with a benchmark (or holding positions and not trading tactically).

These implementation decisions may also provide significant secondary benefits beyond broadening alpha sources. They could, for example, include an explicit link to inflation — think core infrastructure assets with underlying contracts linked to inflation rates. Or perhaps a thematic implementation can help with the pursuit of secondary goals. Research by our Investment Strategy Group has found that thematic equity investments that exploit structural trends are less sensitive to the economic cycle than sectors (Figure 4), meaning that timing the cycle may be less important and that thematic investments may offer an additional level of diversification while potentially also helping to achieve organizational goals like sustainability or income equality.

Figure 4

Rethinking risk

I am often asked what keeps me up at night in terms of financial risks that could impact insurers. As with all things risk management, the answer is nuanced and depends on the underwriting of the insurer, the country of domicile, and many other factors. But the one response I offer no matter the insurer is that tomorrow’s risk won’t be the same as yesterday’s. While we can learn a lot from historical market-stress events, I think insurers need to focus more on what could be different and, heading into 2024, get creative and search for gaps in existing risk assessments. In particular, I think geopolitical risk and default risk warrant a much closer look.

Geopolitical risk: Too big to ignore

We have all seen the impact of war and geopolitical instability in recent years, and the human cost has been profound. Unfortunately, I think insurers must consider the possibility that these events will increase in frequency and severity. Geopolitical risk is often viewed as too difficult to model and account for in portfolio positioning, so asset owners simply punt on the exercise entirely. (We have seen a similar phenomenon with climate risk.) But this is short-sighted and, quite frankly, much too risky in today’s global investment landscape.

So, instead of speaking in generalities or treating the risks as unquantifiable, here are some actionable steps insurers can take:

Understand your country exposure, including by:

Country of domicile
Revenue distribution (e.g., which emerging market (EM) exposures have a significant share from a single country)
Significant concentration in particular countries

Monitor the geopolitical risk landscape

Utilize an index-based approach. For example, the Geopolitical Risk Index (GPR) tracks adverse geopolitical events and risks based on coverage across major newspapers and media (Figure 5). A higher index level tends to correlate with lower investment, a decrease in equity issuance, lower employment, and, potentially, a greater chance of economic disaster. It is possible to drill down into the data by country, event type, and period.
Track United Nations voting of the largest country exposures. Insurers can track how two countries vote to determine whether there may be material deterioration in their relations, often referred to as “Foreign Policy Distance.” This may be an early indicator of geopolitical volatility.

Figure 5

Establish an investment framework for integrating geopolitical risks

Create an exposure profile of the largest potential geopolitical risks. First, determine country pairs with the largest impact on current assets. Then consider which sectors drive those economies and how exposed they are to commodity imports/exports.
Create a geopolitical monitoring dashboard for countries that represent significant risks.
Evaluate historical asset price moves from threats and conflicts (Figure 6 offers examples).
Identify portfolio changes needed to factor in these risks, such as:
- Isolating country risk from broader exposure (e.g., EM vs. China), allowing for a greater ability to dial up or down exposure
- Adding a structural allocation to assets that may provide a cushion to offset some risk from areas of geopolitical conflict (e.g., gold, US Treasuries)
- Monitoring less-liquid assets to mitigate the risk of funds being locked up after an event
- Looking for opportunities where countries will need to spend to “onshore” industry if international tensions increase (it’s not all risk-off!)

Given the complexity that can accompany geopolitical risk and its impact on investment portfolios, insurers may want to partner with experienced asset managers and other subject matter experts when applying the ideas above.

Figure 6

It’s not your (de)fault

Years of low interest rates created challenges. With investment income so critical to profitability, insurers had to explore more creative avenues for return (hence the rise of private credit and illiquids). But it wasn’t all bad news. With low rates and relative economic prosperity came a default rate that was generally below the historical average of 4.1%, sometimes by a considerable margin.²

Will that change in this new regime? There is so much that remains uncertain for 2024, not the least of which is how long the Federal Reserve (Fed) will let rates stay above 5%. This uncertainty is amplified by recent changes in impairment guidelines that require insurers to proactively reserve for expected credit losses, instead of waiting until the losses are incurred (GAAP = CECL, IFRS = IFRS 9). Even if an insurer’s accounting regime falls outside of that guidance, it is critical to have a good assessment methodology in place — not only to model the existing risk of current investments, but also to serve as a reference point for adding to or subtracting from asset risk broadly. I am by no means suggesting that a significant jump in defaults is imminent, but any increase in defaults from historic lows could create a degree of pain for traditionally risk-averse insurers’ fixed income portfolios.

What to watch for

Here are the major factors I’m focused on when considering the default environment in 2024 and beyond:

What is the level and path of interest rates we can expect? In other words, how long will the Fed sustain elevated rates to hit its 2% inflation target?
Where will borrowing rates be when companies with substantial debt maturing in 2025 and 2026 come to market? Typically, borrowers will look to refinance 12 – 18 months ahead of maturity. However, given the limited issuance we saw in 2023, it feels like they are kicking the can down the road, hoping for lower borrowing costs.
What is the size and count of “zombie” companies whose business models relied on historically low rates? These tend to be VC companies in the tech space, which suggests a need for added scrutiny in credit assessments.
How will growth in China (whether it improves or not) spill over to companies that rely on revenue from that market?
Will non-bank lenders (shadow banks, private markets) cushion a potential default spike by offering more flexibility for borrowers? Or could this create a bubble or contagion further down the road?
Will we see an end to the positive ratio of credit upgrades to downgrades? What will this do to spreads and borrowing costs?
How will climate factors impact long-term credit ratings and the stability of the credit markets? Fitch Ratings recently reported that 160 corporates out of 715 it examined had elevated climate risks that could result in a negative rating action by 2035. Of that universe, over half are currently rated investment grade. (I am often asked by insurers with shorter duration profiles why they need to factor climate risk into their fundamental credit research, and I respond that rating agency action is front and center.)

Factoring the risk into credit assessments

In the spirit of rethinking risks, I would suggest the following for the new year:

Revisit the current impairment/credit loss process

Ensure the current screening criteria are appropriate (market value to book value, rating downgrade/watch, spread move, etc.).
Differentiate between interest-rate-related and credit-related issues. Perhaps look at the change in spread versus a benchmark or cohort of similarly rated issuers from the same industry.
Ask your fixed income portfolio managers for their views on looming risks and any issuers they are concerned about. This is where fundamental credit research should earn its keep.

Use forward-looking default assessments

Every rating agency provides base, bull, and bear default scenarios for the coming year.
Data providers develop issuer-level expected default calculations that can be used in setting forward-looking loss reserves, but these can also be used to monitor the most at-risk holdings.

AI is a game changer: What are the potential risks and rewards?

In 2023, artificial intelligence (AI) dominated market headlines and drove impressive gains in the technology sector, particularly for a small number of mega-cap US growth stocks. But how will AI impact the rest of the world, including other sectors? The answer will depend on timing, up-front costs for utilization, the rate of adoption, and other factors. In short, it’s a challenge to assess. But that doesn’t mean insurers shouldn’t be considering it through both risk and opportunity lenses. Here, I offer suggestions on where to begin that analysis.

How might AI’s influence grow over time?

First, I think it’s important to understand the transmission channels through which generative AI could potentially impact the global economy and, eventually, investment portfolios.

Near term — I expect companies that have direct revenue growth from producing the chips, processors, and semiconductors that are essential for generative AI to continue to prosper.

Medium term — Data-heavy sectors are likely to be among the earliest adopters. Moody’s estimates that areas like media, pharmaceuticals, information technology, auto production, and financials could start to see benefits in the next few years, if the market leaders in these sectors are aggressive with their AI spend (Figure 7). Other sectors may begin to experience benefits later in this decade.

Longer term — We should see increased adoption in the developed markets, potentially leading to improved productivity and output, as well as declining cap-ex from efficiencies. Early adopters may be rewarded by becoming “best in class,” forcing laggards to scramble to close the gap. This could lead to increased consolidation across sectors most likely to benefit from adoption/utilization.

Figure 7

What are the big unknowns?

Of course, nothing in life is that cut and dried. Significant questions need to be considered in the context of potential AI benefits:

How will countries regulate the use of AI and how will that impact the scale and pace of adoption? This could vary considerably by market, as regulators undoubtedly view being the world leader in this space as critical to economic growth.
How will AI impact workers? Will AI benefit employees by freeing up time for other tasks and increasing computing power at their disposal? Or will it lead to significant reductions in employment in industries where skills are not easily transferable? The outcome here could offset some (or all) medium-term economic gains and impact decisions on regulation.
Could the cost curve change for the better? Part of the hurdle in assessing the economic benefit of AI is the fact that the cost to harness the technology is prohibitively high for many companies currently. However, advances in the production of AI capabilities could make the technology more cost-effective in the medium term. This, in turn, could lead to greater adoption in developed markets, but also spill over to emerging markets.

Ideas for tapping the investment potential of AI

In the interest of capturing the potential right tail of generative AI adoption while also keeping an eye on risk, I would suggest the following:

Consider exposure to companies on the front line of generative AI adoption. The multiples can be high, but this is a structural trend that I don’t see going away any time soon. Exposure might be achieved via a thematic approach, direct investment in the first-generation companies, or passive ownership of market indices in which those companies make up a significant portion of the market cap.
Utilize private markets to find disrupters in the space. As adoption grows, those that can innovate should be poised to outperform. Technological advancements are often fertile areas for start-ups — more so than for publicly traded companies. Due to the higher risk/reward profile of these assets, it may be prudent to size an allocation on the smaller side of one’s surplus asset range or carve out a percentage of a portfolio’s private equity allocation.
Lean on fundamental research while assessing the winners and losers. There will be net winners and net losers across every sector. The businesses that invest appropriately and distinguish themselves as long-term benefactors of generative AI may be the positions to hold, while using their peers who fail to evolve or mismanage the evolution as sources of funds. The mega-cap tech example aside, this may not be the time to be passive when more disruption is on our doorstep.
Continue to monitor developments across the generative AI space. For example, new regulations could restrict near-term growth, but they could also mean more government investment in technology, which could create investment opportunities.

Closing thoughts on risk

The world seems likely to become even more complex in 2024, but insurers who take steps to identify, avoid, and even exploit risks may be better positioned for a successful year. This doesn’t require breaking down every investment decision to the most granular level possible. Instead, insurers should take the time to determine which risks are most central to their investments specifically and to their enterprise broadly. The focus should be on unintended double dipping of risks (e.g., significant overlap of the underwriting portfolio and assets within the same locations) and areas where current positioning wouldn’t allow for alpha participation in a structural game changer (e.g., beta to AI adoption). Finally, consider using the old 80/20 rule: Spend 80% of your time on the 20% of risks/opportunities that could have the greatest impact.

¹ Source: National Association of Insurance Commissioners, Capital Markets Bureau; as of 31 December 2022. | ² Source: Moody’s, 1983 – 2022.

Important disclosures: Capital market assumptions

Equities
General — Assumed market returns are based on the Investment Strategy Group’s expectations for future dividend yield, earnings growth, and valuation change. Assumed risk and correlations are based on historical analysis of the representative indices.

Indices used are as follows:

US large-cap equities S&P 500
US small-cap equities Russell 2000
Non-US equities MSCI EAFE
Developed market (DM) equities MSCI World
Emerging market (EM) equities MSCI Emerging Markets

Bonds
General – Assumed risk and correlations based on historical analysis of the representative indices.

High quality, sovereign bonds – Return assumptions are based on starting yields and the expectation that yields move towards our estimate of a terminal interest rate over the time period. Using these inputs and the duration of the respective bill, note, or bond, we then calculate the income and capital gains/losses associated with these changes. We assume zero downward adjustment for downgrades and defaults for high quality, sovereign bonds.

Credit risk premia – For non-sovereign and corporate bonds, excess return assumptions are estimated. The excess return assumption is a function of excess spread, a downward adjustment for downgrades and losses and reversion to median spread levels. The excess spread is readily observable in market pricing. The downward adjustment for downgrades and defaults is based on our proprietary research and the long-term historical experience.

Indices used are as follows:

Core bonds Bloomberg US Aggregate Bond
US long bonds Bloomberg US Long Government/Credit Bond
US high yield bonds Bloomberg US Corporate High Yield
Non-US bonds (hedged) Bloomberg Global Aggregate ex-USD Bond (hedged)
Emerging market (EM) debt JPMorgan EMBI Global (i.e., USD denominated)

Currencies
Return assumptions are shown for unhedged currency exposure, unless stated otherwise.

Hedged — Hedged currency return assumptions are based on current and forward-looking estimates for interest-rate differentials.

Unhedged — Unhedged currency return assumptions are formulated based on forward-looking estimates of real carry returns, normalization of real exchange rates, and an adjustment for productivity growth.

General
Period — Intermediate capital market assumptions reflect a long-term time period of approximately 10 years. If we developed expectations for different time periods, results shown would differ, perhaps significantly. Additionally, assumed annualized performance and results shown do not represent assumed performance for shorter periods (such as the one-year period) within the 10-year period, nor do they reflect our views of what we think may happen in other time periods besides the 10-year period. The annualized return represents our cumulative 10-year performance expectations annualized. The assumed returns shown do not reflect the potential for fluctuations and periods of negative performance.

This analysis is provided for illustrative purposes only. This material is not intended to constitute investment advice or an offer to sell, or the solicitation of an offer to purchase shares, strategies, or other securities. References to future returns are not promises or even estimates of actual returns a client may achieve. This material relies on assumptions that are based on historical performance and our expectations of the future. These return assumptions are forward-looking, hypothetical, and are not representative of any actual portfolio, or the results that an actual portfolio may achieve. Note that asset-class assumptions are market or beta only (i.e., they ignore the impact of active management, transaction costs, management fees, etc.).

The expectations of future outcomes are based on subjective inputs (i.e., strategist/analyst judgment) and are subject to change without notice. As such, this analysis is subject to numerous limitations and biases and the use of alternative assumptions would yield different results. Expected return estimates are subject to uncertainty and error. Future occurrences and results will differ, perhaps significantly, from those reflected in the assumptions. ACTUAL RESULTS MAY DIFFER SIGNIFICANTLY AND AN INVESTMENT CAN LOSE VALUE. Indices are unmanaged and used for illustrative purposes only. Investments cannot be made directly into an index.

This illustration does not consider transaction costs, management fees, or other expenses. It also does not consider liquidity (unless otherwise stated), or the impact associated with actual trading. These elements, among others, associated with actual investing would impact the assumed returns and risks, and results would likely be lower (returns) and higher (risk).

Any third-party data utilized in the analysis is believed to be reliable, but no assurance is being provided as to its accuracy or completeness.

Expert

Tim Antonelli

, CAIA, CFA, FRM, SCR

Head of Multi-Asset Strategy – Insurance

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