As the credit cycle ages, defaults are likely to remain front and center. But for investors evaluating private credit alongside public markets, measuring defaults is not as straightforward as it may seem.
The challenges lie in weighing how severely borrowers are becoming distressed and also in determining how that distress is recorded. Public debt markets rely on standardized, easily observable measures of credit deterioration, such as credit ratings from well-known rating agencies. Private markets, by contrast, often resolve stress through less visible mechanisms. Comparing default rates thoughtfully across the two requires deeper analysis of data beneath the headline statistics.
Public defaults are visible; private stress is often negotiated
In public debt markets, measuring default trends appears simple because it is easily observed. The three major rating agencies look at three events when assessing default: a missed payment beyond the grace period, a bankruptcy, or a distressed exchange in which debt terms (such as maturity, coupon, or principal) are restructured. Moody’s counts distressed exchanges directly, though it makes a distinction between distressed exchanges and hard defaults. S&P’s Selective Default and Fitch’s Restricted Default categories serve much the same purpose. Each event is anchored in observable contractual terms or publicly disclosed transactions. Distress, in other words, cannot easily be negotiated outside the empirical record.
Direct lending distress can echo that of public credit, but it’s much harder to observe. With a single lender or small club of lenders, stress can be resolved bilaterally through waivers, amend-and-extend transactions, or cash-to-payment-in-kind (PIK) conversions. These may be economically equivalent to distressed exchanges, but they are not always classified that way. Most loans are also unrated, forcing third-party trackers to rely on different methodologies and definitions. The result is a wide range of headline default estimates that can materially misstate – and usually underestimate – the underlying market stress.
Building a shadow default rate estimate for direct lending
Building a comparable default rate measure for direct lending therefore requires an event-based approach. We focus on five types of default events:
- Default payment
- Non-accrual (i.e., collection of contractual payments is deemed doubtful)
- Post-origination cash-to-PIK conversion (PIK optionality at origination is excluded)
- Material maturity extension of the original loan
- Debt-to-equity swaps
We would emphasize that we are taking the union of these events, so there is no double-counting: A borrower experiencing multiple events is counted only once in that order.
Figure 1 illustrates this “shadow default” analysis for business development companies (BDCs); BDCs are funds that invest in small and midsize private U.S. businesses. The figure shows the share of first and second lien secured loans (by issuer) in BDC portfolios that are in one or more of the five default states in any given quarter. This is explicitly a stock measure: Once flagged, an issuer remains classified as distressed while that condition persists. Conceptually, it’s similar to the 90-day-plus delinquency rate commonly reported in consumer credit.
Figure 1: Our shadow measure of the share of BDC issuers in a default state is notably greater than it was in 2022
There are two takeaways from Figure 1. The first is that the bulk of default events are soft in nature, involving debt-to-equity swaps, maturity extension, and post-origination cash-to-PIK conversion. The second is that, taken at face value, our shadow default rate measure has risen significantly since 2022 from roughly 14% to 19%, even if it has recently begun to plateau.
Measuring against other areas of leveraged finance
To compare direct lending with the 12-month default rates in the high yield (HY) bond and broadly syndicated loan (BSL) markets, we form quarterly cohorts of first and second lien secured loans, and calculate the share experiencing at least one qualifying event over the subsequent four quarters, which we call the 12-month trailing and issuer-weighted shadow default rate.
In our calculations, we deliberately use the original cohort as a fixed denominator: Loans that repay or refinance cleanly before the end of the 4-quarter window remain classified as non-defaults. This is conservative because it effectively assumes those loans would have stayed performing for the remainder of the period.
Figure 2 plots our shadow BDC measure alongside comparable public market default rates (inclusive of distressed exchanges). The comparison is necessarily imperfect. We have sought to harmonize definitions across markets, but differences in instruments, borrower populations, disclosures, and agency methodologies prevent a true apples-to-apples comparison. It is an estimate – a conservative approximation – particularly given the treatment of clean exits and the judgment required to identify distressed concessions.
Figure 2: Our estimates suggest a credit cycle may be taking shape at a faster pace in direct lending than in other segments of leveraged finance
With those caveats in mind, the message from the data is nevertheless striking: A credit cycle appears to be taking shape at a faster pace in direct lending than in other segments of leveraged finance, particularly the HY bond market.
That divergence is consistent with our discussion in the 6 July edition of The Credit Market Lens: The credit quality of today’s HY bond market is unusually high by historical standards, thanks to considerable compositional improvements in the aftermath of the global financial crisis.
Michael Puempel and Gabriel Cazaubieilh contributed to this report.
