- ALM & Regulatory Capital Strategist
United Kingdom, Intermediary
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Is it time for insurers to embrace tactical credit allocation?
Against a new environment of higher inflation, greater volatility and lower liquidity, insurers may wish to consider whether their current approach to credit provides enough flexibility to capture tactical opportunities.
Our research shows that with careful guardrails and both top-down and bottom-up analyses, introducing a tactical credit approach has the potential to enhance returns without meaningfully impacting risk levels or capital requirements.
How a tactical approach to credit could benefit insurers now
Unlike the past 20 to 30 years, there is now a clear trade-off between growth and inflation. Since the global financial crisis, central banks have generally acted to suppress volatility; moving forward, they are more likely to act to generate it. This will create more volatility going into and out of market cycles and cause a greater number of dislocations within global credit markets, such as mispricings or idiosyncratic spread-widening events, which may create tactical opportunities for credit investors.
Credit plays a critical role for insurance balance sheets, especially in the investment-grade category, which has historically offered steady income with relatively low default rates. The asset class often benefits from low turnover in portfolios as well as favourable accounting treatment, both factors that limit the impact of price volatility.
Insurers typically steer their credit exposures through their strategic asset allocation. As a portfolio strategy, setting a strategic asset allocation achieves three key goals for insurers: firstly, it identifies long-term investment opportunities; secondly, it ensures that overall risk is consistent with the insurers’ risk appetites; and thirdly, it provides reassurance that capital is deployed efficiently.
However, the long-term nature of strategic asset allocations itself means portfolios are unable to accommodate swift changes that might arise from unexpected events, such as a pandemic, or from market dislocations. This makes it difficult to fine-tune credit exposure up or down promptly, which limits the amount of income that insurers can generate, which in turn can impact shareholders’ return on equity.
Assessing the opportunity: from theory to practice
Given our belief that the new macro regime calls for a greater use of tactical allocation in credit, we decided to analyse the impact of adding a tactical approach to a typical insurance credit portfolio. Our case study tested various scenarios using quantitative methods. The results: a positive impact on income of between +0.1% to +0.5% per annum and an increase on return on equity of between +0.5% and +2% per annum. Crucially, our proposal preserves the philosophy and goals underpinning insurers’ strategic asset allocations: low probability of incurring credit losses, limited profit and loss volatility, and minimal capital consumption.
Step 1: identifying a tactical opportunity
We started our analysis by creating an initial credit portfolio based on a European insurer’s typical allocation (Figure 1). The next step was to evaluate whether amending any of these characteristics could potentially improve on the return, risk profile and capital requirements of the initial portfolio. Once we identified this potential opportunity, we tested it under multiple conditions and evaluated the results.
Figure 1
Step 2: selecting an appropriate high-yield exposure
We identified credit quality as a variable that could make the credit strategy enhance returns without introducing excessive incremental risk or capital required. Based on this variable, we tested the possibility of creating a new credit strategy by tactically adding high-yield exposure when the opportunity arose. We focused on the segment of the high-yield spectrum adjacent to the initial credit portfolio: BB-rated, with maturities of between one and three years.
It was important to establish a process to determine when to introduce the tactical component (Figures 3 and 4). To do so, we relied on our quantitative assessment of relative credit valuation, meaning that the expected spread return for the new credit strategy, taking credit losses into account, had to exceed that of the initial portfolio by a certain margin, which for our example was 2%. When that hurdle was cleared, we allowed a 10% allocation of the initial portfolio to the high-yield assets identified above. These values can be customised, based on individual insurers’ risk preferences.
As Figure 2 shows, both returns and volatility from spreads in these high-yield bonds are normally above those in the initial portfolio. However, there is only a small difference in Solvency II capital requirements between the initial portfolio and the new high-yield exposure.
Figure 2
Step 3: assessing the results
To evaluate the results, we needed to answer a key question: does introducing a tactical component to the credit strategy help improve returns without adversely effecting other characteristics? We tested the tactical approach under different assumptions. By backtesting both portfolios using historical data, we evaluated the results on an absolute basis (Figure 3) and relative to their capital requirements (Figure 4).
Key conclusion 1 — The results show that based on historical data and simulated past performance over 15 years, the portfolio with the new credit strategy would have generated around 15 basis points (bps) of incremental return with comparable risk, on an absolute basis. This corresponds to an increase in income of about 7% through profit and loss.
Figure 3
Key conclusion 2 — Relative to capital requirements, the average return on equity increases by 152 bps, with volatility largely unchanged.
Figure 4
Key conclusion 3 — The turnover from introducing this kind of tactical approach was minimal; in the simulation period the average turnover was 14%, which is comfortably below the 50% specified for the initial portfolio.1
Final considerations
The case study demonstrates the potential benefits of including a tactical component within a strategic credit investment while adhering to the typical restrictions and goals of insurers. Our goal was to show that increasing credit flexibility does not necessarily entail increasing risk. In conducting our study, we prioritised risk control, focusing on lower risk segments of the credit market, such as short duration, and carefully selecting our high-yield exposure. However, starting points, new exposures and constraints all can be customised to accommodate different risk preferences and balance sheet configurations.
It is important to note that the only source of increased return in our example is asset allocation, which understates the size of the potential income enhancements. In practice, by leveraging a fundamental approach, in addition to the quantitative one employed in our example, the portfolio could generate additional income from sector, issuer and security selection.
Successfully capitalising on tactical opportunities requires rigorous and timely analysis. But insurers who look to employ a tactical allocation to credit (on top of their strategic allocation) may find their approach enhanced in an environment of higher volatility, lower liquidity and wider bid-ask spreads.
1Forward-looking statements should not be considered as guarantees or predictions of future events. Past results are not a reliable indicator of future results. Holdings vary and there is no guarantee that a portfolio has held or will continue to hold any of the securities listed.
Important information
The hypothetical performance referenced above is based upon the firm’s backtest of the model portfolio applying the following assumptions. The model was created out of the universe of US corporate credit rated BBB 3 – 5 years for investment grade and US high yield rated BB 1 – 3 years for high yield. The model was rebalanced monthly. Turnover was not constrained. The model used in the backtest is proprietary and intended to estimate expected returns from credit over a 12-month horizon. Some assumptions were made for modelling purposes and may not be repeated. Changes in assumptions may have a material impact on the simulated returns presented. The performance period for the model was chosen based on availability of data and is deemed to be long enough to reflect performance over several cycles. Other periods selected would have different results, including losses. Past performance is no guarantee of future results.
Actual performance may differ substantially from the hypothetical backtested performance presented. Live portfolios are constructed using specific securities and are subject to transaction costs. In our model, we have not considered transaction costs which might overstate the outperformance of the model over the market. We have not considered any additional returns that might arise from security selection. We believe these two effects offset each other and that the backtest is an accurate reflection of what a live strategy would have delivered.
Except where indicated, simulated performance results are gross of commissions and other direct expenses, advisory fees, custody charges, withholding taxes, and other indirect expenses. If all expenses were reflected, the performance shown would have been lower.
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