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At first glance, insurance-linked securities (ILS), such as collateralized reinsurance or catastrophe bonds, might appear to have little in common with credit investments. The use of insurance-specific language, such as expected loss and attachment points, can present a significant barrier in assessing opportunities in the space.
Credit funds are increasingly exploring ILS markets due to its low correlation with other assets and its performance as one of the best asset classes in 2023 (for an in-depth discussion on ILS performance and benefits please see our previous blog post). We want to give credit investors a practical guide to understand and invest in ILS. We will draw parallels between insurance-linked securities and credit, highlighting their similarities and providing insights into how credit investors can approach ILS with a familiar mindset.
Insurance-Linked Securities (ILS): ILS are financial instruments linked to insurance risks. They allow investors to gain exposure to insurance-related risks—like natural disasters—by providing capital to insurers and reinsurers in exchange for a return. The most common forms of ILS include catastrophe bonds and collateralized reinsurance.
Credit Investments: Credit investments involve lending money to corporations or governments in exchange for interest payments and the return of principal. The primary risk is the borrower’s potential to default on its obligations. The most common forms of credit instruments are bonds and loans.
Both ILS and credit investments have a similar structure. Investors in both asset classes put capital at risk—whether as principal or collateral—and are compensated through coupons. In credit markets, this compensation is for assuming the risk of a borrower default, while in ILS, it compensates for the risk of an insurance payout.
In reinsurance, an insurance company may seek coverage for specific risks, such as natural disasters, by structuring its reinsurance needs into layers — each layer represents a different level of risk. These layers, or "towers," dictate how much of a loss is covered by each reinsurer, with higher layers taking on risks only after lower layers are exhausted.
This structuring is akin to the capital structure in debt markets, where a company's liabilities are segmented into different levels of seniority, from senior secured debt to subordinated debt. Investors in senior debt are the first to be repaid in the event of default, while subordinated debt holders bear a higher risk for a potentially higher return. Similarly, in a reinsurance tower, the higher layers (akin to senior debt) bear less risk but offer lower returns, while lower layers (akin to subordinated debt) bear more risk for higher potential returns. In both worlds holds, the higher up in layer/priority, the lower the risk.
Consider the example below that compares a reinsurance tower with a standard capital structure side by side. The first $100 million of losses are retained by the insurance company and are not reinsured. Similar to equity, it acts as a loss buffer for investors as it is depleted first before obtaining reinsurance covers or financing via debt. If losses exceed $100 million, the next $100 million are covered by a the next risk layer (”Layer 1”). Just as investors choose where to invest based on their risk tolerance in credit markets, they decide which layers of the tower to cover based on their risk appetite.
In both the insurance-linked securities (ILS) and credit markets, risk assessment plays a crucial role in evaluating potential investments. Despite the different underlying assets, the principles of risk assessment are quite similar. Both industries rely on specialized agencies to gain a better understanding of the inherent risks. One of the leading insurance risk modelling companies, RMS, was in fact acquired by Moody’s in 2021.
Credit Markets: Rating agencies such as Moody’s, S&P, and Fitch provide assessments of creditworthiness, offering investors insights into the risks associated with different debt instruments. These agencies use extensive data and proprietary methodologies to assign credit ratings, which help investors understand the relative risk of different securities.
ILS Markets: In the ILS market, risk modeling companies like RMS and AIR Worldwide provide risk models that estimate the likelihood and impact of various insurance-related events, such as natural disasters. Their analyses help determine the probability of various scenarios, such as hurricanes or earthquakes, and their potential impact on the securities.
To illustrate the risk assessment in both markets, we will discuss key metrics on a real world example, comparing the catastrophe risk bond Marlon Ltd. (Series 2024-1) Class A, which was issued in May 2024 and provides protection against named storms in Florida and the Canadian 5 year government bond with a rating of AAA.
Probability of Attachment vs. Probability of Default
In credit investing, the probability of default (PD) represents the likelihood that a borrower will fail to meet its debt obligations. In the world of ILS, a similar concept exists: the probability of attachment (PA). PA refers to the likelihood that an insurance loss event will exceed a certain threshold (remember the layer structure in the reinsurance tower), triggering the reinsurance coverage. For example, the Marlon Ltd. (Series 2024-1) Class A catastrophe bond has a PA of 0.75%, as determined by AIR Worldwide, who was the risk modeler for this transaction. For the Canadian government bond, the implied probability of default is 0.66%, based on the market pricing of credit default swaps and assuming a 40% recovery rate.
Loss Given Attachment vs. Loss Given Default
Another key similarity is the concept of loss given attachment (LGA) in ILS and loss given default (LGD) in credit. Both metrics represent the amount that is expected to be paid out when a loss event triggered a payout.
A notable difference in credit investing is the recovery process following a default, where recovery rates can influence LGD calculations. Recovery rates vary across debt instrument and industry. Median recovery rates for senior unsecured bonds were 41.9% while senior secured bonds had a rate of 58.7% from 1987 - 2023 (see S&P’s Default, Transition, and Recovery Study for more insights). Typically, a recovery rate of 40% is assumed for simplicity, resulting in an LGD of 60%. We will do the same for the Canadian government bond.
Expected (Credit) Loss
Putting all of the above together, we can calculate the expected loss per invested dollar. The meaning and calculation are the same for credit and (re)insurance investing. This metric represents the expected loss in principal over a certain time horizon. For credit, we multiply PD with LGD while we use PA and LGA for ILS.
In our example, we obtain an expected loss for our cat bond of 0.65% and 0.40% for the government bond, respectively (see Figure 3).
While insurance-linked securities and credit investments may operate in different domains, the underlying principles of risk assessment and return profiles are similar. By drawing these parallels, credit investors can approach the ILS market with a more familiar perspective. ILS can improve investment portfolios by opening up new opportunities for diversification and attractive returns. We hope that we brought ILS closer to traditional investors and bridge the gap between insurance and capital markets.
CatX offers direct access to the ILS market for institutional investors and provides all relevant risk models and analytics for transactions, allowing new participants to fully understand the underlying risks.
Feel free to reach out to the team to discuss all our available investment opportunities in more detail.
Sources: World Government Bonds, Artemis.bm
