Private Credit’s Reality Check: Portfolio Health, Valuations, and Emerging Risk Signals
From software valuations to non-accruals and PIK, our recent webinar highlighted how investors can separate temporary dislocation from deeper credit stress.
As moderator, I had the opportunity to guide a timely conversation on where private credit stands today and which signals investors should be watching most closely. The market continues to evolve rapidly, shaped by several forces moving at once: macroeconomic uncertainty, AI and technology disruption, shifting deal dynamics, portfolio health, valuation pressure, and evolving lending standards.
In SOLVE’s recent webinar, hosted in partnership with DealCatalyst, we brought together leading experts from reputable financial institutions, to discuss how these dynamics are showing up in BDC-held portfolios, how risk is being evaluated, and where investors may need to look more closely in the months ahead.
Credit Losses Are Part of the Cycle
One of the questions I raised during the discussion was how investors should interpret the increase in non-accruals and credit losses across BDC portfolios, and whether current stress should be viewed as idiosyncratic or a sign of broader deterioration.
The response was clear: credit losses should not come as a surprise. After a long period of benign conditions, investors became accustomed to unusually low loss levels. While losses have increased and dispersion across BDCs has become more visible, the broader sector continues to show attractive performance overall. From a ratings perspective, the focus remains on asset quality, earnings durability, liquidity, and the ability of BDCs to manage through elevated redemption activity.
Software Risk Requires a More Nuanced View
Given the level of attention around AI disruption, one of the questions I raised was how valuation professionals are separating software businesses that may benefit from AI from those at greater risk of commoditization.
The discussion made clear that software risk cannot be evaluated with a broad brush. Software valuations became more challenging as public market multiples moved lower, even when many underlying businesses continued to show revenue and earnings growth. Valuation work now requires a more nuanced view across loan-to-value, horizontal versus vertical software models, retention rates, and manager assessments of AI-related disruption. The result is a more differentiated approach to understanding where risk is truly concentrated and which businesses may be more resilient.
Underwriting Is Adjusting to New Risks
From there, I wanted to understand whether lenders are changing their diligence requirements when underwriting new technology businesses, particularly as AI risk becomes a more active part of the conversation.
The response was that the core diligence categories have not necessarily changed, but the way lenders evaluate them is evolving. Areas such as revenue durability, margin pressure, customer concentration, IP ownership, cybersecurity, data risk, and regulatory exposure are receiving closer attention. While explicit AI-related provisions are not yet standard in credit agreements, AI-related risk is increasingly influencing diligence, documentation, and the decision of whether certain deals should move forward at all.
Stress Signals Are Becoming More Important
Portfolio health indicators drew particular attention. Non-accruals, PIK usage, assets trading below par, valuation marks, and delayed financial reporting can each provide insight into underlying stress. Kahn highlighted the distinction between PIK structured at origination and PIK added later as part of an amendment, with the latter potentially serving as a more meaningful stress signal.
The conversation closed with a reminder that private credit will likely remain a market of dispersion. Some borrowers and managers will be well positioned, while others may face more pressure from amendments, documentation leakage, restructurings, or sponsor decisions to hand assets back to lenders. For investors, the challenge is not simply finding more data, but identifying the signals that reveal whether portfolio movement reflects temporary dislocation or deeper credit deterioration.
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About SOLVE
SOLVE is the leading market data platform provider for fixed-income securities, trusted by sophisticated buy-side and sell-side firms worldwide. Founded in 2011, SOLVE leverages its AI-driven technology and deep industry expertise to offer unparalleled transparency into markets, reduce risk, and save hundreds of hours across front-office workflows. With the largest real-time datasets for Securitized Products, Municipal Bonds, Corporate Bonds, Syndicated Bank Loans, Convertible Bonds, CDS, and Private Credit, SOLVE empowers clients to transform the way they bring new securities to market, trade on secondary markets, and value highly illiquid securities. Headquartered in Connecticut, with offices across the globe, SOLVE is the definitive source for market pricing in fixed-income markets.
