Space Operators Are Paying an Equity Premium for Debt-Compatible Assets

In 2023, space insurers collected $557 million in premiums and paid out $995 million in claims. The net loss was $438 million, a record. The two largest claims were $420 million for the Viasat-3 Americas satellite and $348 million for the Inmarsat 6-F2 communications satellite following a power subsystem failure. 2024 losses are projected to be similarly severe.

Those numbers contain a credit signal that the lending market has not yet read.

Equity Dominates Where Debt Should Compete

Venture capital accounts for 71% of total NewSpace investment. Debt financing grew its share from 0.4% in 2019 to 7% in 2023. Seven percent is growth from a very low base.

The underlying assets are structurally compatible with debt. Orbital operators generate long-duration contracted cash flows from sovereign and enterprise customers. Those are the characteristics of financeable infrastructure. Debt sits senior in the capital structure, receives contractual repayment priority, and requires a lower return than equity. The spread between the two represents the financing premium orbital operators are currently paying unnecessarily.

The collateral problem is well documented. Once deployed, a satellite cannot be recovered or repossessed. That limits its utility as primary security. But collateral is not the binding constraint. The deeper issue is that lenders have no standardized framework for assessing the probability that a given orbital operator defaults on its obligations. Without that, they cannot set terms. Many decline the transaction entirely.

What the Insurance Data Reveals

The insurance market is the most transparent proxy available for how space risk is currently being priced, and the 2023 data exposes the structural problem clearly.

At the start of 2023, insuring a typical GEO satellite aboard a Falcon 9 for launch plus one year cost less than 6% of the insured value. By year-end, that rate had risen to around 10%.

Annual in-orbit insurance rates nearly doubled, from 0.6% to 1.2%. Of approximately 10,000 satellites in orbit, only around 300 carry in-orbit insurance, almost all in geostationary orbit.

The market is pricing a narrow slice of the orbital asset base, using engineering-based loss models calibrated to physical failure modes. Those models capture antenna deployment anomalies and power subsystem failures. They do not capture operator-level credit risk: the probability that a given operator's capital structure fails before the asset generates sufficient cash flow to service its obligations.

Every policy is essentially bespoke. There is no standardized framework because every satellite and every operator is assessed individually from scratch. That absence of standardization keeps pricing elevated and capacity constrained. The same absence applies to lending. No standardized operator-level credit framework means no basis for setting terms. The market prices its own uncertainty instead of the underlying risk.

The WACC Problem

When lenders cannot quantify risk with precision, they price their own uncertainty rather than the underlying asset risk. Those are different numbers, and orbital operators carry the difference as excess financing cost.

The financing cost for any infrastructure project is determined by its WACC. Higher uncertainty produces a higher WACC. In space finance, WACC cannot be correctly calibrated when operator-level credit risk has not been quantified. The result is a blanket risk premium applied across the sector, penalising creditworthy operators alongside weak ones.

In project finance, an investment-grade offtake counterparty reduces the required discount rate. Orbital operators with multi-year sovereign agency contracts structurally satisfy those criteria. The majority are not accessing correspondingly lower financing terms, because no framework exists to establish their creditworthiness at the asset level and translate it into outputs a lender can act on.

In offshore wind, reducing WACC from 10% to 5% drops the levelized cost of energy by over 30%, assuming a 25-year asset life and flat real cash flows. The arithmetic is the same for orbital infrastructure. A sustained compression in space finance cost of capital expands the pool of financeable operators, reduces the equity burden on existing ones, and pulls in institutional capital that is currently constrained by analytical barriers rather than risk appetite.

The Inputs Exist

The data required to build orbital credit frameworks is available. Orbital regime, conjunction event frequency, debris density, spectrum license tenure, revenue contract duration, counterparty credit quality, historical operator anomaly rates, and DSCR dynamics under revenue compression: these are measurable variables, tracked across orbital data providers, regulators, and engineering databases.

The missing component is a credit intelligence layer that takes those inputs, produces probability of default outputs at one-, three-, and five-year horizons, and formats them for investment committee and credit committee review. When that layer exists, lenders can set terms on space assets. Insurance underwriters can price operations rather than missions. Cost of capital compresses toward fundamentals.

The problem is well defined. The inputs are available. The solution is an analytical build. That layer is what SarynSpace is building.

SarynSpace produces orbital credit risk intelligence for institutional lenders, insurers, and infrastructure investors. This article is not investment advice and does not constitute a credit rating.