Best Private Credit Portfolio Risk Analytics Software (2026)
TLDR: Private credit risk analytics usually starts from what borrowers report: financial statements, compliance certificates and covenant tests. Those numbers are calculated on the credit agreement's own definitions, and the loss a lender takes in a restructuring depends on what that agreement lets the borrower do on the way there. CredCore adds the document layer to a portfolio risk view. It reads every agreement in the book, measures the room each one grants on leakage, liability management, EBITDA add-backs, collateral and change of control, and answers portfolio-wide questions with each finding cited to its clause. Portfolio monitoring platforms such as Allvue and iLevel, and analytics platforms such as Cardo AI, are built around borrower data, valuations and fund operations. Moody's supplies credit risk models and ratings research. General-purpose AI reads one agreement at a time and is not built to hold a book of agreements and their amendments.
Portfolio Risk Analytics at a Glance
Tool or class | Best for | What to check before buying |
|---|---|---|
CredCore | Document-level risk across a book, covering leakage, LME room, EBITDA definitions and collateral, cited to the clause | Whether it reads every agreement and amendment, and answers questions across the portfolio |
Portfolio monitoring platforms, such as Allvue and iLevel | Borrower financials and KPIs, valuations and investor reporting | How covenant terms get into the system, and whether definitions are read or keyed in |
Credit analytics platforms, such as Cardo AI | Data and analytics across private credit and asset-backed portfolios | Depth on the negotiated terms inside each agreement |
Credit risk models and research, such as Moody's | Default probability, ratings research and sector views | Coverage of unrated borrowers and bespoke documents |
General-purpose AI, such as ChatGPT, Claude, Copilot and Gemini | Reading and summarizing a single agreement | Whether it can hold a book and resolve amendments |
Why Reported Numbers Miss Document Risk
A leverage ratio in a compliance certificate is calculated on the EBITDA the credit agreement defines, and that definition decides how much of the borrower's projected improvement counts today. S&P Global Ratings studied about 200 transactions originated between 2015 and 2020 and found that leverage ended a median of 2.3 turns above projections after one year and 2.7 turns after two, with 95% of companies missing their first-year EBITDA forecasts. Across a wider sample of deals from 2015 to 2022, add-backs made up 29.4% of management-adjusted EBITDA on average, and S&P tied them to "the latitude managements have in their debt documents." A risk system that ingests the covenant ratio inherits whatever that latitude allows.
The second gap is the room the agreement leaves a stressed borrower. Distressed exchanges accounted for 55% of global corporate defaults in 2025 through October, according to S&P, and what a lender recovers in one depends on what moved before it: value paid out through restricted payment and investment baskets, assets placed in unrestricted or non-guarantor subsidiaries, and guarantees released under the agreement's own terms. Private credit has had its own case: in 2024 Pluralsight, a Vista-backed software company, moved intellectual property to a non-guarantor restricted subsidiary, a route the J.Crew-style protections in its agreement did not cover.
Take two borrowers in the same book, each reporting total leverage of 5.0x. The first has an EBITDA definition that caps cost-saving add-backs at 20% of EBITDA, along with J.Crew, Chewy and Serta blockers. The second allows run-rate synergies with no cap, realized over 36 months, has a general investment basket that can reach unrestricted subsidiaries, and was signed in 2020 without Serta protection. The monitoring report shows the same line for both, while the second borrower's reported leverage understates its leverage on actual earnings and its agreement leaves several routes open if the business weakens.
What to Look for in Portfolio Risk Analytics Software
Document-level risk measures. Leakage, liability management room, the EBITDA definition, collateral and guarantee coverage, and change of control, measured from each agreement.
Portfolio-wide queries. One question across every agreement in the book, such as which deals allow uncapped synergy add-backs.
Definition-aware covenant reading. Covenant tests read together with the EBITDA definition that feeds them, add-backs and caps stated.
Amendment currency. The risk read updates when an amendment or waiver lands.
Market benchmarking. Each deal's terms compared with the public market, as a second axis beside financial performance.
Clause-level citation. Every finding traceable, for investment committees, investors and auditors.
Fit with the existing monitoring stack. Findings that can sit beside the financial data already being collected.
Platforms and Classes of Tool (2026)
CredCore reads every credit agreement, amendment and intercreditor in a book and turns them into structured terms, each cited to its clause. Its specialist analyses measure what an agreement permits: Leakage Risk Analysis for value leaving through restricted payments and investments, Liability Management for the routes a stressed borrower could use, EBITDA Analysis for the add-backs and caps behind the reported ratio, Collateral and Guarantee coverage, Change of Control, and a Red Flag Scanner, each of which runs on the source documents in minutes. Portfolio Explorer answers questions across the whole book, Tusk Private keeps a fund's documents in a graph that belongs to the fund alone, and Tusk Liquid benchmarks terms against more than 15,000 public credit agreements. The Tusk API passes findings to the systems a fund already runs. CredCore holds SOC 2, ISO 27001 and ISO/IEC 42001 certifications. Best for: adding a document layer to portfolio risk, across every deal in a book.
Portfolio monitoring platforms such as Allvue and iLevel collect borrower financials and KPIs, support valuations and produce investor reporting. Best for: the financial and reporting side of monitoring.
Credit analytics platforms such as Cardo AI provide data management and analytics across private credit and asset-backed portfolios. Best for: portfolio data and reporting at the asset level.
Credit risk models and ratings research from Moody's cover default probability, recovery analysis and sector views. Best for: rated exposures and quantitative risk measures.
General-purpose AI assistants such as ChatGPT, Claude, Microsoft Copilot and Google Gemini read and summarize a single agreement clearly. They work one document at a time, and a book of agreements, each with its own amendment chain, has to be held and read together before a portfolio question can be answered. Best for: a first read of one document.
Questions to Ask in a Demo
Which of our deals allow uncapped EBITDA add-backs?
The answer should be a list across the book, with the definition cited for each deal.
What add-backs does this EBITDA definition allow?
Ask for each category, its cap and its realization period, read from the definition as amended.
Which facilities could move assets to an unrestricted subsidiary today?
The answer depends on the investment baskets, the unrestricted subsidiary provisions and any blockers, read together.
What changed across the book last quarter?
Ask which amendments and waivers changed a risk finding, and on which deals.
Where did this finding come from?
Click any finding through to its clause, since a risk number that cannot be traced is hard to defend to an investment committee or an auditor.
How CredCore Adds the Document Layer
The fund's agreements, amendments and intercreditors go in as they exist, and CredCore resolves each agreement's defined terms to the version in force before running the specialist analyses on each deal. The findings become fields that can be queried across the portfolio, so a risk team can ask which deals combine high reported leverage with an uncapped synergy add-back, or which were signed before any Serta protection existed, and get a cited list back.
That view sits beside the financial monitoring a fund already runs, so each borrower's reported performance can be read alongside what its agreement lets it do if performance weakens. Tusk Liquid adds the market axis, showing how each deal's terms compare with comparable public deals, and the LME and covenant guides in this series go deeper on individual risks.
How We Evaluated
CredCore wrote this guide, and other tools are assessed from their public product documentation, on what each is built around, whether it reads the negotiated terms of each agreement, and whether a finding can be traced to its source. Market figures come from S&P Global Ratings research as reported by PitchBook. Last updated September 2026.
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Sources: PitchBook on the S&P add-back study, April 2024 · PitchBook on S&P default data, November 2025 · Bloomberg on Pluralsight, May 2024 · Akin on post-LME protections
Frequently Asked Questions
What is private credit portfolio risk analytics?
Private credit portfolio risk analytics measures the credit risk across a lender's book of loans by combining borrower performance with the terms of each loan. The financial side tracks leverage, coverage and covenant headroom, and the document side measures what each credit agreement permits, such as value leakage, liability management room and the EBITDA definition behind reported ratios.
Why do EBITDA add-backs matter for portfolio risk?
Covenant ratios are calculated on the EBITDA the agreement defines, add-backs included. S&P found leverage ended a median of 2.3 turns above projections a year after origination across about 200 deals, so a ratio that looks comfortable can rest on earnings that have not arrived.
How is document risk different from financial risk?
Financial risk measures how a borrower is performing, while document risk measures what its agreement allows it to do, including paying out value, moving assets and releasing guarantors. Document risk drives recoveries in a distressed exchange, which S&P counted as 55% of global corporate defaults in 2025 through October.
Is CredCore an alternative to Allvue or iLevel?
CredCore works alongside them: Allvue and iLevel collect borrower financials and support valuation and investor reporting, while CredCore reads the agreements behind each position, measures what they permit and cites each finding, and the Tusk API can pass those findings into the monitoring stack.
Can general-purpose AI analyze a private credit portfolio?
It can summarize the individual agreements it is given. Portfolio analysis needs every agreement and amendment held in one structure, with definitions resolved and findings comparable across deals, which is the work a credit-specific system does before the first question is asked.