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How to Build a Covenant Tracking System for Private Credit in 2026

9 min read

Muhammad AliMuhammad AliFounder, consultance.ai
How to Build a Covenant Tracking System for Private Credit in 2026

Build a covenant tracker by turning each credit agreement into a versioned register of definitions, thresholds, add-back caps and deadlines, then recompute every test from cited source figures rather than trusting the borrower's certificate. Route each exception to a named reviewer with its clause and page, and prove the system on past quarters with known outcomes before using it live.

What this covers

  • Proskauer's index put the US private credit default rate at 2.51% in Q2 2026, down from 2.73% in Q1.
  • Lincoln reported a 2.7% covenant default rate in Q2 2026 and bad PIK on 6.2% of all loans, which it says may be viewed as a shadow default rate.
  • A real October 2025 credit agreement defines Consolidated Adjusted EBITDA in more than 3,000 words, with add-backs numbered (i) through (xxxi) and a 30% cap on some of them.
  • The core of the system is a versioned covenant register per facility, not a dashboard.
  • Recompute every ratio from cited source figures and treat any gap with the borrower's certified number as an exception.
  • Lumonic and Cascade sell covenant monitoring platforms; neither publishes list pricing.

To build a covenant tracking system for private credit, turn each credit agreement into a structured register of definitions, thresholds and deadlines, collect borrower reporting against that register, recompute every test from source figures, and send exceptions to a named reviewer with a link to the page each number came from. The alerting is the easy part. The hard part is converting a negotiated EBITDA definition into a calculation a credit officer will put their name to.

This guide walks through the build in the order we would do it. It uses a real credit agreement filed with the SEC as the worked example, and it ends with when buying a vendor platform makes more sense than building.

Why covenant tracking matters in 2026

Headline default rates in direct lending are moderate. Proskauer's Private Credit Default Index, which tracks US senior secured and unitranche loans, put the default rate at 2.51% for the second quarter of 2026, down from 2.73% in the first quarter. The sample covered 716 loans with $195.6 billion of original principal. Borrowers with EBITDA of $25 million to $49.9 million moved the other way, rising from 3.1% to 3.4%.

Lincoln International's Private Market Index tells a similar story with a warning attached. Its size-weighted covenant default rate fell to 2.7% in the second quarter of 2026 from 3.1% in the first, below a six-year average of 3.9%, across roughly 1,800 private companies. In the same release, Lincoln reported that 6.2% of all loans carried what it calls bad PIK, meaning PIK interest today on a loan that had none at close, and said that figure may be viewed as a shadow default rate. It was 5.9% in the first quarter.

The practical point for anyone building a tracker: the covenant test result is only one signal. Amendments, waivers and PIK elections carry information too. A system that only records pass or fail will miss the loans that are being managed quietly.

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What you are actually tracking

Most of the work concerns maintenance covenants. Golub Capital's white paper on direct lending covenants, presented as of January 2026, describes maintenance covenants as requiring borrowers to report key financial metrics on a regular schedule. Incurrence covenants are tested only when a borrower takes a restricted action, such as adding debt or paying cash to equity holders. A cov-lite loan generally has incurrence covenants and no maintenance covenants. Golub notes that borrowers with EBITDA under $50 million are typically subject to a maintenance requirement.

The same paper describes the outcomes your workflow has to handle. A maintenance breach is an event of default, distinct from a payment default. Lenders can waive it, agree a forbearance, or amend the agreement to a different level, and these steps typically involve fees paid by the borrower. A sponsor can also inject cash as an equity cure in exchange for more room on the tests. Revolvers often carry springing covenants that switch on at a drawdown level, which Golub puts at around 35%, and then require quarterly testing like a maintenance covenant.

Reporting covenants sit underneath all of this. A test cannot run until the financials arrive, so the deadlines matter as much as the thresholds.

A real agreement shows the scale of the problem

A useful specimen is the credit agreement dated October 31, 2025, with Monarch Finco, LLC as borrower, Lincoln International CentCo, LLC as holdings, Antares Capital as administrative agent, and Antares Capital and Bain Capital Credit as joint lead arrangers. It was filed publicly as Exhibit 10.8 to Lincoln International's Form S-1, so anyone can read it.

The defined terms section runs from page 1 to page 87. The definition of Consolidated Adjusted EBITDA alone is more than 3,000 words, and its first clause lists items added back to net income, numbered (i) through (xxxi). Clause (xxxi) allows run rate cost savings from acquisitions, projected by the borrower in good faith from actions taken within 18 months and calculated as though realized on the first day of the test period. A proviso caps those savings, together with two categories of charges from another clause, at 30% of Consolidated Adjusted EBITDA for the test period. The definition also fixes deemed EBITDA for four historical quarters, including $39,808,069.86 for the quarter ended June 30, 2025.

The reporting terms are just as specific. Annual audited financials are due within 120 days of fiscal year end, or 150 days for the first year. Quarterly financials are due within 60 days, or 75 days for the first four quarters and after a material accounting change, and the agent can extend both at its discretion. A compliance certificate is due on the date those financials are delivered or required. The commitment fee also steps with the First Lien Net Leverage Ratio shown on the most recent compliance certificate, so the same number drives pricing as well as risk.

Golub makes the general version of this point: add-backs such as projected cost savings can distort EBITDA and have to be assessed and, in some cases, restricted. A tracker that stores one EBITDA field per borrower cannot represent any of it.

Step 1: Build a covenant register from each agreement

Start with the data model, not the dashboard. Every facility gets a register that a reviewer can check line by line against the executed agreement and every amendment.

Register fieldWhat it holdsWhy it matters
CovenantName and type: maintenance, incurrence, springing or reportingDecides when and whether the test runs
Definition clausesSection references for every defined term the test usesLets a reviewer check the math against the document
Threshold scheduleLevels by test date, including step-downsThresholds often change over the life of the loan
Test periodThe measurement window, such as the trailing four quartersRatios are tested over a period, not at a point
Add-back rulesPermitted adjustments, caps and look-forward windowsA cap like the 30% limit above changes the answer
Deemed valuesFigures the agreement fixes for historical periodsThey override what the financials would produce
Cure rightsEquity cure terms and how many have been usedDetermines whether a breach can still be cured
Amendment logEach change with effective date and feeKeeps every test on the terms in force at that date

Language models are good at the first draft of this register. They read a long agreement quickly and pull candidate definitions and thresholds with clause references. They are not the final word. A credit analyst reviews each entry against the document before the register goes live, and the register is versioned so an amendment never overwrites history.

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Step 2: Generate the reporting calendar from the register

Deadlines come from each agreement, not from a house template. The example above has different windows for the first year, for the first four quarters and after an accounting change, plus agent extensions. Store each rule, compute the due date per borrower per period, and record every extension as an event with the party that approved it. The calendar then tells the team which packages are late before anyone has to ask.

Step 3: Extract figures with a citation for every number

Compliance packages arrive as PDFs and spreadsheets in each borrower's own format. Extraction should return every figure with the document, page and line it came from, and it should stop rather than guess when a number is missing. A figure without a source location does not enter a test. That single rule is what makes the output reviewable in minutes instead of redone from scratch.

Step 4: Recompute every test independently

Do not rely on the ratio printed on the borrower's certificate. Rebuild it from its components using the register: apply the add-back rules and caps, substitute deemed values where the agreement requires them, and measure over the correct test period. Then compare your result with the certified figure. A difference is an exception in its own right, even when both numbers pass.

Derive the key ratios a second way, for example from the source financials rather than the certificate schedule, and block the result if the two do not tie. Record headroom as the distance from the threshold and keep the quarterly history. A loan that moves from 30% headroom to 8% over three quarters deserves attention before it breaches.

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Step 5: Route exceptions to a named reviewer

Every flag should carry its clause, number, period and source page, so a reviewer can confirm or close it quickly. Give each flag one tag: changes the credit view, worth a question to the borrower, or explained by the agreement. A closed flag stays closed unless the facts change.

The workflow then follows the outcomes Golub lists: waiver, forbearance, amendment or equity cure, each logged with its fee, date and effect on the register. Track PIK elections and maturity extensions the same way. Lincoln's bad PIK figure is a reminder that some of the most useful signals never appear as a failed test.

Step 6: Prove it on history before it goes live

Run the finished system on past quarters where the outcome is known, including at least one period with a breach or an amendment. It should reach the conclusions the credit team reached at the time, and every difference should have an explanation. Only then point it at the current quarter. A named person signs off each cycle. The system prepares the work; it does not certify compliance.

Build or buy

Vendors sell this as a product. Lumonic, which Morningstar acquired in a deal that closed on March 3, 2025 and which now operates as a subsidiary of PitchBook, says its platform sets up the reporting schedule and covenants from the document, reruns leverage and borrowing base tests on every new statement, and gives borrowers a portal to upload in their own format. Morningstar did not disclose the deal terms. Lumonic does not publish list pricing; its site offers demos instead.

Cascade focuses on asset-based finance. Its site describes automated financial and affirmative covenant tests that run as new data arrives, borrowing base calculations, verification of borrower data before tests run, and waiver and forbearance workflows with an audit trail. It reports more than $25 billion of receivable balances monitored on its platform. Cascade also does not publish pricing.

A vendor seat makes sense when your agreements are fairly standard and you want a maintained product. A custom build makes sense when the definitions are heavily negotiated, the borrower data has to stay inside your environment, or the tracker needs to feed your own loan system and memo workflow. That second case is what consultance.ai does. We build custom finance AI, the first system is live in about six weeks, and the client owns the code. You can see how that applies on our private credit AI page, or run the free covenant and payment monitor prompts from our AI build library on past data first. To talk through your own agreements, book a 30-minute audit.

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