Five Questions Direct Lenders Are Asking About Their Borrowers in 2026

As an asset class, direct lending amassed significant AUM in a compressed period, with a substantial pool of dry powder accumulating in the late 2010s and early 2020s. Notably, the loans originated during this period were underwritten against a starkly different macroeconomic environment. Interest rates were near historic lows, PE-backed companies were benefiting from strong growth, and robust exit markets supported premium valuations and multiples. Broadly, these dynamics shaped underwriting assumptions and loan terms.

With abundant capital, lenders often faced intense competition for sponsor-backed deals. Borrowers consequently often gained greater negotiating power, with some able to secure more borrower-friendly documentation, including looser covenants and greater flexibility around EBITDA definitions and adjustments. Further, because sponsor-backed businesses account for a large share of direct lending activity, today’s portfolios reflect PE’s favored sectors in recent years.

Software is a particular focus, as AI raises questions about the durability of some of these businesses and, in turn, the credit risk embedded in lenders’ portfolios. According to LPL Financial, direct lenders funded roughly 40–70% of leveraged buyouts each quarter in 2022 and 2023, up from 15–25% before the pandemic. Today, industry estimates put direct lending’s software exposure at roughly 20–30%. As a result, lenders are increasingly focused on how AI-driven pressure could impact the credit health of their software borrowers, from EBITDA and leverage to compressed valuation multiples and higher loan-to-value ratios.

Further, software valuations have reset from pandemic-era highs, and the exit market has repeatedly opened and closed amid macroeconomic uncertainty, with buyer appetite concentrated in a narrow pool of trophy assets. As a result, holding periods have extended and more loans are approaching maturity before sponsors can exit. For these borrowers, refinancing risk becomes increasingly relevant, particularly for companies in AI-exposed sectors or with weaker underlying fundamentals. 

Against this backdrop, lenders are increasingly turning to their portfolio data to monitor their borrowers and loans in greater depth, identify emerging risks, and surface early-warning indicators for potential deterioration. Here, we examine five key questions direct lenders are asking about their borrowers and loans, and how consolidating comprehensive portfolio data in Chronograph can help answer them.

How Is EBITDA Tracking Across My Portfolio?

EBITDA is the translation layer between deteriorating borrower fundamentals and credit risk. To take software borrowers as an example, weaker-than-expected growth, accelerating customer churn, or declining gross margins can weigh on earnings, increasing debt-to-EBITDA, reducing capacity to service cash interest, and raising loan-to-value ratios.

Yet, tracking and unlocking a consolidated view of EBITDA across a direct lending portfolio is rarely straightforward. Lenders often receive multiple versions across borrower reporting. For example, a financial statement may present one EBITDA figure, while a compliance certificate uses another, reflecting its own adjustment parameters and contractually defined calculation.

Additionally, in recent years, generous add-backs and forecasts became common in covenant definitions amid intense competition for deals. As a result, “covenant EBITDA” can sometimes paint a stronger picture than the underlying business warrants. For credit managers, cross-checking the compliance certificate across reported financials, ensuring negotiated caps are respected, and validating the calculation against the underlying inputs on a compliance certificate are critical to assessing EBITDA with greater granularity.

As direct lenders look to build nuanced EBITDA views across their portfolios, Chronograph provides the flexible data architecture to capture, validate, and analyze EBITDA across multiple angles:

• Centralize EBITDA Adjustments. Firms can ingest and centralize EBITDA adjustments from borrower compliance certificates, categorizing them to match their bespoke buckets. This unlocks a portfolio-wide view of where and how adjustments are shaping reported EBITDA.
  
  
• Reported, Covenant, and Firm-Specific EBITDA Views. Teams can capture every reported version of EBITDA while maintaining firm-specific calculations and methodologies to maintain bespoke views of EBITDA alongside the reported figures in financials and compliance certificates.
  
  
• Add-Back Validations. With Chronograph, firms can automatically test covenant EBITDA against negotiated add-back caps and recalculate adjusted EBITDA from compliance certificate inputs to validate reported figures.
  
  
• Custom EBITDA Alerts. Teams can configure alerts to flag material swings in EBITDA or significant gaps between covenant and reported EBITDA.
  
  
• Fund-Level EBITDA Querying. Importantly, firms can maintain multiple EBITDA views at the borrower level while designating the preferred versions for fund-level analysis and downstream use cases. This enables firms to preserve the nuances of borrower reporting and custom methodologies while still answering portfolio-wide questions such as, “How is EBITDA tracking across my software borrowers in 2026?”

How Can I Automatically Track Covenant Breaches and Trigger Proactive Alerts of Headroom Thresholds and Potential Warning Indicators? 

As many borrowers face persistently high interest rates or potential technology disruption, covenant compliance only becomes more essential to monitor. A breach can trigger remedies, negotiations, or defaults, making it important to not only understand compliance, but also headroom and other early warning signs. However, for many firms, covenant monitoring is very manual, requiring lenders to rekey reported figures, recalculate ratios, and manage borrower-specific definitions and adjustments. Spreadsheets, email threads, and manual calculations add both friction and the risk of error.

Chronograph helps lenders centralize and automate covenant monitoring while preserving the bespoke terms negotiated in each credit agreement:

• Automate and Centralize Covenant Calculations. Chronograph extracts inputs from compliance certificates and automatically calculates and centralizes leverage ratios, fixed-charge coverage ratios, interest coverage ratios, and other covenant metrics.

• Preserve Borrower-Specific Covenants. Covenant definitions and permitted adjustments vary across credit agreements and borrowers. Chronograph does not impose a standardized definition; instead, it captures and calculates each covenant according to the terms negotiated with the borrower.

• Validate and Recalculate Covenant Ratios. With the underlying inputs centralized, lenders can independently recalculate covenant ratios and validate the figures reported on compliance certificates.

• Flag Breaches and Emerging Risks. Chronograph automatically flags covenant breaches and allows firms to configure alerts for indicators of potential credit stress, such as when headroom falls below 10% or net leverage increases by more than one turn between reporting periods.

• Capture the Context Behind Covenant Performance. With Chronograph, lenders can capture and preserve qualitative context around a breach or declining headroom, creating a centralized record of why performance is changing and what is driving the risk.

How Are Internal Risk Assessments and Watchlists Evolving Across the Portfolio? 

Risk ratings and watchlists are core tools for direct lenders looking to identify changes in credit quality across a portfolio. Firms typically use bespoke rating methodologies that combine quantitative indicators — such as leverage, EBITDA performance, covenant headroom and add-backs — with qualitative judgment from the deal team. Some ratings can be automated through Excel-based rules and thresholds, while others require deal team input of the broader circumstances of a borrower.

For lenders, centralizing these signals can provide a clearer view of how credit quality is evolving across the portfolio. With Chronograph, firms can:

• Automate and Centralize Borrower Risk Ratings. Configure proprietary rating methodologies to automatically assign a borrower risk rating each reporting period based on defined financial and credit metrics.

• Capture Qualitative Context and Overrides. Allow deal teams to override a calculated rating when circumstances warrant, while documenting the rationale and other qualitative factors informing the assessment.

• Track Rating Migrations Over Time. Monitor quarter-over-quarter changes in borrower ratings to identify deterioration or upgrades. 

• Analyze Portfolio Risk by Exposure. View the distribution of borrowers across risk categories by both borrower count and exposure to understand how portfolio value and borrower counts are concentrated by risk profile.

Which Underperforming Borrowers Have Upcoming Maturity Dates or Refinancing Risks? 

One of the biggest risks for borrowers facing more exposure or vulnerability to AI disruption or those with weaker fundamentals is how they will fare in the refinancing market. Today, lenders need to understand which underperforming borrowers have upcoming maturities and connect those exposures to the underlying financials, credit metrics, and operating KPIs to better understand risks. With Chronograph, lenders can enable this more granular view:

• Connect Maturity Dates to Borrower Risk. By storing facility maturity dates alongside internal risk ratings, lenders can assess maturity-wall exposure by borrower performance, industry, and time horizon. This helps teams identify whether upcoming maturities are concentrated among healthy borrowers or among companies showing signs of credit or performance deterioration.

• Assess Maturities Against Fundamentals. With borrower financials, credit metrics, and operating KPIs in Chronograph, teams can evaluate the underlying refinancing risk associated with each upcoming maturity. They can identify borrowers with weakening EBITDA, rising leverage, declining interest coverage, and limited covenant headroom, prioritizing those exposures for deeper review.

How Much of My Portfolio Is Paying Their Debt With PIK, and Is It Good PIK or Bad PIK?

In recent years, PIK provisions became increasingly common in direct lending, often as a borrower-friendly feature that gave high-growth companies flexibility to preserve cash and reinvest in organic growth or acquisitions. Rather than paying interest in cash, borrowers could capitalize some or all of their interest onto their loan principal, increasing debt in exchange for near-term liquidity.

Amid higher-for-longer interest rates and the prospect of AI-driven disruption, PIK usage is coming under scrutiny. Today, lenders are increasingly focused on distinguishing “good PIK” — included at origination as part of the intended capital structure —  from “bad PIK” — introduced later through an amendment —  often in response to weakening performance or a temporary cash flow shortfall.

However, even PIK negotiated at origination is not necessarily benign, as the underlying growth narrative still needs to materialize. For example, the restructuring of Medallia illustrates how a PIK toggle can be part of the original financing structure while the business ultimately fails to perform against the assumptions underpinning the underwriting case.

Ultimately, monitoring PIK alongside underlying borrower health is critical, as excessive reliance can swell debt balances while valuations and performance deteriorate, increasing the risk of default. With loan accounting data, borrower KPIs, credit metrics, and qualitative context centralized in Chronograph, firms can monitor PIK usage alongside the fundamentals driving borrower performance:

• Distinguish “Good” from “Bad” PIK. Track whether PIK was underwritten at origination or introduced through an amendment, when a PIK toggle is activated or turned off, and how much of the available PIK capacity has been used. At the portfolio level, this enables firms to identify the breakdown of good vs. bad PIK. 

• Track Cash vs. PIK interest. Analyze the mix of cash and PIK interest at both the borrower and portfolio level to understand how much interest is being paid in cash versus PIK.

• Capture the Context Behind PIK Usage. Centralize the rationale for PIK elections, such as preserving cash for an acquisition, funding growth initiatives, or navigating a temporary cash flow disruption.

• Monitor PIK Alongside Borrower Performance. View PIK usage alongside KPIs, EBITDA, and other credit metrics to assess whether the underlying thesis is playing out. Is growth materializing? Is cash flow recovering as expected? Or is PIK masking a more persistent deterioration in credit quality?

Chronograph provides an efficient, flexible data pipeline for centralizing comprehensive private credit portfolio data into a single source of truth, allowing firms to bolster portfolio management, better understand risks, and run deeper analysis. Check out our Navigating AI Disruption in Direct Lending Report, for a full look at how direct lenders can leverage Chronograph to unlock more granular portfolio monitoring of software borrowers.