19 Best Private Credit Portfolio Analysis Tools & Data Solutions: In-depth Evaluation Guide for Asset Managers
Posted by Laura Saville on September 27, 2026
Private credit managers increasingly run sophisticated systems for portfolio administration, covenant monitoring, valuation, and reporting. The harder problem is getting an independent, external view of borrower credit quality, particularly for private and unrated names where public ratings and market signals are thin or absent.
Without that outside perspective, risk assessments rely heavily on borrower-supplied financials and internal models, which can make deteriorating credits slower to spot. Teams that track borrower financials, covenants, or loan positions in Excel can face outdated data and inconsistent calculations. And because each stage feeds the next, a weakness anywhere in the stack affects the quality of the analysis that follows.
An effective private credit portfolio analysis stack therefore needs to cover the core functions asset managers use to understand, monitor, value, and manage portfolio risk, including an independent read on borrower credit quality. Here’s what that looks like in practice:
| S/N | Category | Primary job |
|---|---|---|
| 1 | Independent credit intelligence & benchmarking | Provide an external view of borrower credit quality so asset managers can benchmark internal ratings, compare borrowers consistently, and identify changes in creditworthiness |
| 2 | Portfolio data & administration | Maintain the portfolio record, including positions, loan terms, PIK accruals, borrower data, cash flows, documents, and fund-level information |
| 3 | Portfolio monitoring & covenant management | Track borrower performance, covenant headroom, exposures, watchlists, reporting requirements, and ongoing portfolio activity |
| 4 | Valuation & fair value | Estimate the fair value of private credit positions, support periodic NAV calculations, and provide independent valuation support |
| 5 | Risk modeling & scenario analysis | Model expected losses, concentrations, correlations, stress scenarios, liquidity risk, and the effect of potential new investments on the portfolio |
A private credit fund can usually find established tools for portfolio administration, covenant monitoring, valuation, and risk modelling. Conversely, independent credit intelligence is harder to obtain because private borrowers often lack external signals the fund can use to test its internal credit view.
This is a significant gap. A fund may have excellent portfolio tool stack, covenant monitoring, valuation support, and stress-testing tools. But if none of those systems provides an external borrower-level credit view, the team must still validate its assessment with its own inputs.
Adding more data providers does not necessarily solve the problem either. Roughly two-thirds of surveyed institutions already use two to three external providers, yet respondents still identified private and unrated coverage and independent credit assessments as important gaps. More than 70% also cited visibility into private borrowers as a significant pain point, while 72% reported difficulty obtaining up-to-date information on private entities.
The missing layer, therefore, may not be another dashboard or workflow platform. It may be a timely, independent credit view on borrowers that public-market data does not cover.
So, rather than comparing platforms feature by feature, we will explore the core functions a private credit portfolio analysis tool stack should cover and the top tools for each one. We will also ensure the solutions we recommend in the first category close the unrated-entity gap in your portfolio.
Recent research shows unrated private debt impairs more often than comparable rated debt. See what the data reveals about the private market transparency gap and why independent benchmarking matters.
Best private credit portfolio analysis Data Tools at a Glance
Here’s an overview of the portfolio analysis solution categories we are going to cover later:
| Category | Tool | Best for |
|---|---|---|
| Independent credit intelligence & benchmarking | Credit Benchmark | Independent credit benchmarking for private and unrated borrowers, plus portfolio profiling and risk analysis |
| S&P Global Ratings | Recognized public ratings for borrowers or debt instruments already covered by S&P | |
| Moody’s Ratings | Recognized public ratings for borrowers or instruments already covered by Moody’s | |
| Fitch Ratings | Recognized public ratings for borrowers or debt instruments already covered by Fitch | |
| KBRA Private Ratings | Formal analyst-led ratings for specific private borrowers or transactions | |
| Morningstar DBRS Private Ratings | Confidential analyst-led ratings for specific private borrowers or debt instruments | |
| Moody’s RiskCalc and EDF | Scalable PD estimates and model-derived credit scores for unrated private companies | |
| RapidRatings | Quantitative financial-health scoring for private and unrated companies | |
| Portfolio data & administration | Allvue | Integrated private debt portfolio management, loan administration, and accounting |
| BlackRock eFront | Institutional private markets data, fund administration, monitoring, and reporting | |
| S&P Global WSO | Loan administration, position tracking, reconciliation, accounting, and reporting at scale | |
| Portfolio monitoring & covenant management | Lumonic | Automating borrower data collection, covenant monitoring, and portfolio reporting |
| Finley | Borrowing-base, collateral, and covenant monitoring for asset-backed lending | |
| Cardo AI | Covenant, collateral, and portfolio monitoring for asset-based finance and structured credit | |
| Valuation & fair value | 73 Strings | Automating and standardizing private credit valuation workflows |
| Kroll | Valuation technology and independent third-party support for illiquid or complex loans | |
| Risk modelling & scenario analysis | MSCI | Measuring private credit risk alongside the wider portfolio and testing market scenarios |
1. Independent Credit Intelligence and Benchmarking
Independent credit intelligence gives asset managers an outside reference for borrower credit quality, internal ratings, and PDs. Managers use it to test internal ratings, challenge their probability-of-default estimates, and compare borrowers consistently across the book.
They don’t replace the lender’s own analysis. The goal is to supplement its internal rating with external evidence proving the rating, credit grade, or PD is well calibrated. Four types of providers can supply an external credit view, but they rely on different sources of evidence:
- Bank-contributed credit consensus data combine the internal credit views of other financial institutions that assess the same borrower.
- Public credit ratings come from agency analysts and are published for the market.
- Private and confidential ratings also come from agency analysts, but a lender, borrower, or other party commissions the assessment, and the rating remains private.
- Model-derived credit scores use quantitative models to estimate credit risk from financial statements and other borrower data.
| Type | Independent evidence comes from | Main private credit limitation |
|---|---|---|
| Consensus assessments | Other financial institutions that assess the borrower | Coverage depends on contributor assessments |
| Public ratings | External rating agency analysts | Many private borrowers are unrated |
| Private ratings | Commissioned external analysts | Usually obtained name by name |
| Model-derived scores | Quantitative credit models | Often depend on borrower-supplied financials |
These approaches serve different purposes, as each provides a different form of independent credit assessment. Asset managers often use more than one. The right mix depends on how much of their book is already supported by external data and where the portfolio lacks a credible second opinion.
I. Consensus Credit Assessments
Consensus credit assessments combine the internal ratings or default-risk estimates of multiple financial institutions that assess the same borrower, anonymize them, map them to a common rating scale, and publish an aggregate view for each borrower. This helps asset managers compare their own view with the collective view of other lenders.
That makes it one of the more useful alternative credit data providers for private and unrated borrowers. Many of these companies have no public rating or traded market signal, but several banks may still assess them internally. A consensus view turns those separate assessments into a common external reference that the asset manager can use to test its own rating or PD.
a. Credit Benchmark
Best for: Asset managers that need an independent credit view on private or unrated borrowers and want to use it for portfolio profiling, monitoring, risk-return analysis, and pre-trade review.
Credit Benchmark gives buy-side teams a peer reference drawn from banks that have direct exposure to the same counterparties they hold. More than 40 global banks, including roughly half of the global systemically important banks (G-SIBs), contribute their internal borrower ratings and probability of default (PD) estimates. Credit Benchmark anonymises these submissions, maps them to a common scale, and produces Credit Consensus Ratings and forward-looking one-year PD estimates, refreshed weekly.
What makes this data different is where it comes from. Unlike a model-derived score based on borrower financial statements, or a single-provider rating opinion, Credit Benchmark reflects the aggregated credit judgement of institutions independently assessing the same obligor for their own risk-management purposes. Those banks have capital at stake and regulatory obligations behind their assessments, so the consensus adds genuinely new information to a manager’s analysis rather than simply providing another score.
That matters most where other signals are missing. The database covers 125,000+ legal entities across 160 countries, and more than 90% of them are unrated by the major agencies, including private companies, funds, subsidiaries, and financial counterparties. For private credit portfolios full of borrowers without public ratings or traded-market prices, this is often the only independent external view available.
Asset managers can upload a portfolio, match its borrowers to the database, and compare each internal rating with the bank consensus. Because each assessment draws on multiple contributors, the data also shows how much agreement sits behind it. A tight cluster of views signals strong consensus on a borrower’s credit quality, while a wide spread flags that contributors see the risk differently and the name may deserve a closer look.
The matched ratings can then be rolled up into a portfolio-wide credit profile, showing how much exposure sits in each rating band, where weaker credits are concentrated, and how the portfolio shifts over time. Even without full coverage, a match rate above half the portfolio can provide a representative view, and weekly updates help managers catch rating changes between scheduled reviews.
For deeper analysis, transition matrices quantify historical rating-migration patterns to support portfolio modelling and scenario analysis. Industry correlation matrices show how default risk across sectors has historically moved together, giving a credit-driven view of diversification where market-price correlations aren’t available. Consensus PDs can also be combined with spread and recovery assumptions to assess risk-adjusted returns and spot potential mispricing.
Credit Benchmark feeds into existing workflows through its web app, Excel add-in, API, flat files, Bloomberg, Snowflake, and AWS.
Keep in mind
Credit Benchmark provides credit intelligence and benchmarking. It does not replace loan administration, covenant management, valuation, or fund accounting systems.
Case study: assessing unrated loan pools before committing capital
In a significant risk transfer deal, a buy-side team may receive a loan pool with dozens or hundreds of borrowers that have no public credit rating. If the seller is the only source of credit information, the buyer has no independent way to check whether the risk has been assessed fairly.
One asset manager used Credit Benchmark to solve this problem before investing. It compared the borrowers in the loan pool with consensus ratings from more than 40 contributing banks. This gave the team an independent view of borrower credit quality before pricing or approving the deal. The manager later used the same method for structured credit, with consensus ratings mapped to individual loans inside CLOs where no external borrower-level rating was available.
This gives the investment team a second credit reference at underwriting and stronger evidence to support its decision before an investment committee. Credit Benchmark’s private credit risk management guidance explains how this external reference fits into a broader risk framework.
What to find external validation for your private credit portfolio composed of unrated entities? Book a free portfolio coverage assessment with Credit Benchmark.
II. Public Credit Ratings
Public credit ratings give asset managers an external opinion on a borrower’s creditworthiness. Rating agencies assign them after their analysts review the issuer, its financial position, and the terms of its debt. For a portfolio manager, a rating provides a recognized reference point that can sit alongside the fund’s internal credit view.
In private credit, coverage is often limited, since many private borrowers have never sought a public rating. And where a rating does exist, a further question becomes relevant. A rating can provide an external opinion, but in private markets an additional question matters: can that opinion itself be independently benchmarked? Comparing a rating, or an internal credit view, against a broader set of independent assessments helps managers see whether it sits in line with consensus or stands apart from it.
Public ratings therefore remain a useful input where available, but they work best as one reference point within a wider benchmarking approach rather than as a complete answer to it.
a. S&P Global Ratings
Best for: Managers that need a recognized public credit rating for borrowers or debt instruments already covered by S&P. 
S&P Global Ratings gives investors an external opinion on the creditworthiness of an issuer or debt instrument. Its ratings run from AAA to D and help investors compare relative credit risk across companies and securities. S&P treats BBB- and above as investment grade, while BB+ and below fall into speculative grade.
To arrive at these grades, S&P’s analysts assess factors such as leverage, cash flow, liquidity, and interest coverage, as well as competitive position, industry conditions, management quality, and the economic environment. A rating committee then decides the final rating, and S&P monitors rated issuers for material changes in credit quality.
For a private credit manager, an S&P rating can provide a recognized external reference for a borrower that already has agency coverage. The manager can compare that rating with its internal grade, use it to place the borrower on a common credit scale, and track later upgrades or downgrades as part of portfolio monitoring.
The main limitation is coverage. Many private credit borrowers have never obtained a public rating. So, S&P may provide a useful benchmark for public entities, but it does not provide an external reference across the whole portfolio.
b. Moody’s Ratings
Best for: Managers that need a widely recognized public rating for borrowers or instruments already covered by Moody’s.
Moody’s Ratings provides public credit ratings on issuers, debt instruments, and securities. These ratings give investors an external view of relative credit risk and help them compare borrowers on a common scale, at both issuer and instrument level.
Moody’s long-term scale runs from Aaa at the highest end to C at the lowest. The ratings are forward-looking opinions of relative credit risk and use published methodologies. Moody’s also separates commercial and analytical responsibilities within its ratings business to support the independence of the rating process.
The main limitation for private credit is the same one that applies to other public rating agencies: many borrowers in a private credit portfolio have never been publicly rated. A Moody’s rating can therefore provide a strong external reference where coverage exists, but it may leave much of the portfolio without a public benchmark.
c. Fitch Ratings
Best for: Managers that need a recognized public credit rating for borrowers or debt instruments already covered by Fitch.
Fitch Ratings provides public credit ratings that give asset managers an external view of an issuer’s or debt instrument’s credit quality. Its public ratings use the same rating scale and core criteria that Fitch applies across its other rating products.
Fitch has broad reach across global credit markets, with nearly 21,000 rated entities and transactions, more than 1,400 analysts, and a presence in 28 countries. It also has dedicated private credit coverage across areas such as middle-market loans, CLOs, business development companies, funds, asset managers, corporates, and infrastructure.
For portfolio analysis, the main limitation is still coverage. A public Fitch rating is useful when it exists, but many private credit borrowers do not have one. Managers may therefore need another source of external credit intelligence for the unrated portion of the book.
III. Private and Confidential Ratings
Private and confidential ratings give asset managers an external, analyst-led view of a borrower or debt instrument without publishing the rating to the wider market. They use the same type of credit analysis found in public ratings, but the result stays restricted to the borrower, lender, investor, or other permitted parties.
The main limitation is scale. These ratings are typically commissioned for specific names or transactions, so extending them across a portfolio with hundreds of borrowers may require separate engagements rather than a single portfolio-wide data feed.
a. KBRA Private Ratings
Best for: Managers that need a formal, analyst-led credit rating on specific private borrowers or transactions.
KBRA provides analyst-led private ratings for issuers and transactions that do not need a publicly distributed rating. Its private credit coverage includes more than 1,000 rated issuers and transactions, work with over 100 sponsors, and thousands of underlying credit assessments on middle-market, sponsor-backed companies.
KBRA also makes eligible private ratings available through its Ratings Feed for authorized issuers and verified investors. This can bring private rating data into existing credit, risk, reporting, and portfolio systems instead of forcing teams to track each rating manually.
The main limitation is scale. Private ratings still depend on KBRA having assessed the specific borrower or transaction, so coverage across a large private credit book will not necessarily be complete. They work best as an external opinion on selected names rather than as a universal borrower-level benchmark.
b. Morningstar DBRS Private Ratings
Best for: Managers that need a confidential, analyst-led rating on a specific private borrower or debt instrument.
Morningstar DBRS provides private credit ratings that are not published on its public ratings website. Instead, it sends the rating directly to the issuer or the party that requested it. This provides an analyst-led external opinion on a borrower or debt instrument that may have no public rating.
Morningstar DBRS also has a dedicated private credit service. Its work includes lender-initiated private credit ratings, and the firm uses financial information collected through those engagements to develop aggregated sector statistics and private credit research.
The main limitation is portfolio coverage. A private rating exists only for borrowers or transactions Morningstar DBRS has assessed, so a manager cannot assume that every name in a large private credit portfolio will have one. This makes the service more suitable for specific exposures than for a complete external credit view across the entire book.
IV. Model-Derived Credit Scores
Model-derived credit scores use quantitative models to estimate borrower risk from financial statements and other data. They can produce PDs or credit scores for unrated companies at scale.
Their main weakness is the input data. If the model relies on the same borrower financials the manager already uses, stale or incomplete inputs can weaken the result. These tools are most useful as an external quantitative check, not a substitute for the manager’s own credit analysis.
a. Moody’s RiskCalc and EDF
Best for: Managers that need scalable PD estimates and credit scores for private companies without public ratings.
Moody’s RiskCalc estimates the credit risk of private companies that may not have an agency rating. It provides a consistent way to assess many unrated borrowers, using company financial data to produce an Expected Default Frequency (EDF), which expresses the estimated probability that a borrower will default.
The models can produce EDF estimates over horizons from one to five years, map those estimates to rating scales, support stress testing, and process portfolios in batches. This makes the tool useful for comparing credit risk across a portfolio and identifying borrowers that may need closer review.
RiskCalc can also translate EDF measures into rating-like outputs. It uses an approach that combines the EDF with factors such as company size and sovereign risk to produce a rating that is more comparable with an agency rating.
The main limitation is that RiskCalc depends on borrower financial data. If those financials are outdated or incomplete, the EDF estimate may also be less reliable. Unlike a full agency rating, RiskCalc does not incorporate the same range of qualitative factors, such as external support and country-related risks.
b. RapidRatings
Best for: Managers that need a quantitative financial-health score for private or unrated companies.
RapidRatings provides quantitative credit-risk analysis for public and private companies. Its core measure is the Financial Health Rating (FHR), a 0–100 score built from a company’s financial statements and proprietary models. RapidRatings also provides reports that explain the factors behind each rating, which can help teams identify weaker credits and focus their reviews.
However, this rating depends on company financial data. If the borrower’s financial statements are old or incomplete, the assessment may not reflect its current position. RapidRatings also focuses broadly on counterparty, supplier, and credit risk rather than private credit portfolio management specifically.
2. Portfolio Data and Administration
Portfolio data and administration tools help private credit managers bring loan terms, positions, cash flows, borrower data, and accounting information into one system so teams can manage the portfolio more consistently.
These platforms support tasks such as loan administration, position tracking, payments, reporting, and fund accounting. Although they are essential for maintaining clean portfolio data, they usually do not provide an independent view of borrower credit risk.
Here are the top examples in this category:
a. Allvue
Best for: Private credit managers that want an integrated system for portfolio management, loan administration, and accounting.
Allvue provides private debt software that brings portfolio data, loan operations, and accounting into one platform. Private credit managers use it to track positions, loan terms, cash flows, accruals, transactions, and portfolio performance without relying on separate spreadsheets and systems.
For portfolio administration, Allvue’s Investment Accounting system tracks loan activity and maintains a detailed history of each position. Its portfolio management tools then bring this information into dashboards and reports, so teams can see their exposures and performance from one place.
Allvue also covers other parts of the private debt workflow, including research, covenant tracking, fund accounting, investor reporting, and deal management. This makes it useful for firms that want several front- and back-office processes connected through the same system.
b. BlackRock eFront
Best for: Institutional asset managers that want one private markets platform for portfolio data, fund administration, monitoring, and reporting.
BlackRock eFront is a private markets platform that helps asset managers manage alternative investments, including private debt, across the full investment lifecycle. It brings together portfolio data, fund operations, monitoring, reporting, and investor information in one environment.
For private credit managers, its main value is creating a more consistent source of portfolio data. eFront Portfolio Monitoring supports data collection, standardization, analysis, and investor reporting, which can reduce the need to reconcile information across spreadsheets and separate systems. eFront Invest adds fund management and operational capabilities, while eFront Provider supports data exchange between asset managers and fund administrators.
For firms with both public and private investments, eFront can connect with BlackRock’s Aladdin platform to provide a broader view of portfolio exposures and performance across asset classes.
However, eFront is primarily a portfolio management and data infrastructure platform. It can organize and analyze private credit holdings, but it does not by itself provide an independent borrower-level credit benchmark.
c. S&P Global WSO
Best for: Private credit managers that need a scalable system for loan administration, position tracking, cash reconciliation, accounting, and reporting.
S&P Global WSO is a loan portfolio administration platform built for private credit, CLOs, syndicated loans, and other credit portfolios. With it, operations teams get one system for managing loan positions, cash flows, transactions, accounting, reconciliation, and reporting across the loan lifecycle.
Specifically in private credit portfolio analysis, the software serves as the operational record of the portfolio. Items such as loan balances, interest accruals, cash and PIK interest, amendments, and cash movements are tracked within the system. That way, teams keep position and payment data accurate as the portfolio grows, instead of maintaining those records across separate spreadsheets and systems.
Keep in mind that WSO helps maintain accurate loan and portfolio records, but does not provide an independent borrower-level credit benchmark. Managers still need a separate source of credit intelligence to test their internal view of borrower risk.
3. Portfolio Monitoring and Covenant Management
Portfolio monitoring and covenant management tools help private credit managers track how borrowers are performing after a loan is made. Financial updates, covenant tests, compliance data, and other borrower information are centralized in one system, so teams can spot problems earlier.
Most importantly, they help automate covenant calculations, flag breaches, track reporting deadlines, and highlight changes in borrower performance. This reduces the need for manual spreadsheets and helps teams quickly identify and focus attention on credits that may be weakening.
The top solutions in this category include:
a. Lumonic
Best for: Private credit managers that want to automate borrower data collection, covenant monitoring, and portfolio reporting.
Lumonic is built for private credit teams that need to collect borrower data, monitor covenants, and keep portfolio reviews up to date. It brings information from financial statements, compliance certificates, borrowing-base certificates, credit agreements, and other borrower documents into one system.
The platform structures this information so teams can monitor both reporting and financial covenants without maintaining separate spreadsheets. It can handle straightforward covenant tests as well as more complex calculations, including EBITDA adjustments. Each calculation can be traced back to its source data, which helps teams check discrepancies and see how figures have changed over time.
Lumonic also helps teams combine data from different debt structures into auditable reports for investment committees, LPs, and co-lenders. Historical diligence files, borrower updates, and covenant trends can also be retained for future underwriting and portfolio comparisons.
b. Finley
Best for: Private credit managers and asset-backed lenders that need to automate borrowing-base calculations, covenant monitoring, collateral analysis, and borrower reporting.
Finley is a private credit operations and monitoring platform with a strong focus on asset-backed lending. It turns credit agreements into structured data so lenders can track the rules of each facility, including covenants, borrowing-base requirements, concentration limits, and borrower deliverables.
For portfolio monitoring, Finley keeps loan positions, collateral, covenants, and exposure data in one place. It can automatically calculate borrowing bases and covenant tests, then alert managers when limits are breached or reports are due. This helps teams track changes over time without rebuilding the same analysis each month.
Finley is especially useful for loans backed by pools of assets, where managers need to monitor the collateral closely. It can track which assets qualify as collateral, how concentrated the pool is, whether payments are becoming overdue, and how the borrowing base changes over time. Finley also keeps the source documents linked to the data, so teams can trace each calculation back to the original information.
c. Cardo AI
Best for: Managers of asset-based finance and structured credit portfolios that need automated covenant, collateral, and portfolio monitoring.
Cardo AI is a credit technology platform with a strong focus on asset-based finance and structured credit. To enable portfolio monitoring, it centralizes borrower, collateral, facility, and covenant data into one system so managers can track performance across individual deals and the wider portfolio.
The platform also automatically calculates financial metrics and covenant tests when new borrower data arrives. It then flags breaches or other changes that need attention. Teams can compare current results with earlier reporting periods and keep a record of covenant changes, waivers, and approvals.
Cardo AI supports portfolio-level monitoring too. Managers can review exposures and concentrations across borrowers, sellers, asset classes, and deal structures, which helps them see where risk is building across the book rather than looking at each facility separately.
These capabilities make it a strong fit for portfolios with detailed asset-level data and complex financing structures. Managers focused mainly on simpler cash-flow loans may not need the same level of infrastructure.
4. Valuation and Fair Value
Valuation and fair value tools help private credit managers estimate what their loans are worth when no active market price exists, based on factors such as loan terms, borrower performance, market data, and comparable transactions. This makes them especially useful for illiquid or complex loans, where managers cannot rely on a quoted price.
However, valuation shows what an investment is worth today, but it does not necessarily tell the manager how the borrower’s credit risk compares with an independent benchmark.
Here are the main solutions within this category:
a. 73 Strings
Best for: Private credit managers that want to automate and standardize valuation workflows across a large portfolio.
73 Strings provides valuation technology for private markets, including private credit. Instead of spreadsheets, 73 Value Credit module helps value portfolios in a structured system where they can manage assumptions, calculations, supporting data, and approvals in one place.
The platform supports several valuation methods, along with calibration, benchmarking, scenario analysis, and stress testing. Managers can update market inputs and borrower information, test different assumptions, and apply a more consistent valuation process across multiple investments.
A key benefit is auditability. 73 Strings keeps a record of the data, assumptions, valuation calculations, and changes behind each result. This makes it easier for valuation teams to explain and support their marks during internal reviews, LP reporting, and audits.
One point worth noting, is that 73 Strings is primarily valuation technology. It helps a manager calculate and document fair value, but human judgment is still required to choose appropriate methods and assumptions. Firms that need a separate third-party valuation opinion may also need an independent valuation adviser
b. Kroll
Best for: Private credit managers that need both valuation technology and independent third-party support for illiquid or complex loans.
Kroll combines independent valuation services with technology for valuing private and illiquid investments. This lets asset managers value individual loans or entire portfolios where there is no active market price, including senior and subordinated debt, distressed loans, structured products, and whole loan pools.
One product worth pointing out is its Private Capital Markets Platform. Teams use it to collect investment data, update valuation models, and manage valuations in one place. It can also extract information from financial statements and credit agreements, support scenario analysis across hundreds of loans, and keep a record of historical valuations and assumptions. This makes the valuation process easier to review and audit.
However, since valuation does not provide the same information as an independent borrower credit benchmark, asset managers may still need separate credit intelligence to judge how the borrower’s default risk compares with the wider market.
5. Risk Modelling and Scenario Analysis
Risk modelling and scenario analysis tools help private credit managers estimate how the portfolio could perform under stress. They can model defaults, losses, rating changes, concentrations, and correlations, revealing which borrowers or sectors drive the most risk and how the portfolio may respond to a downturn.
Their main limitation is that the results depend on the inputs. If the borrower ratings or PDs are poorly calibrated, the model can still produce misleading results.
The main solutions include:
a. MSCI
Best for: Institutional managers that want to measure private credit risk alongside the rest of their portfolio and test how exposures may behave under different market scenarios.
MSCI provides risk modelling tools designed to show how private credit affects overall portfolio risk. Specifically, the Private Credit Factor Model measures exposures using factors specific to private credit, such as lending strategy, region, capital structure, and broader market conditions.
That approach lets the model reveal which exposures drive risk, how much diversification private credit adds, and how the portfolio could respond to changes in credit markets or the economy. Teams can extract these insights during portfolio-level analysis or more detailed loan-level analysis.
MSCI also supports scenario analysis and stress testing. Managers can apply hypothetical market shocks and estimate how private credit and other asset classes may respond. The results of such tests are then used to set risk limits, construct portfolios, and report to investment committees.
MSCI’s factor model focuses on portfolio risk rather than replacing borrower-level credit underwriting. For that, you can use MSCI other separate private-credit products for borrower-level PD, LGD, and implied ratings.
b. Moody’s Credit Portfolio Management
Best for: Managers that need portfolio-level credit risk analysis, concentration analysis, stress testing, and scenario modelling.
Moody’s Credit Portfolio Management helps managers measure risk across a credit portfolio and test how that risk could change under different scenarios.
Most importantly, the platform can show where risk is concentrated by borrower, sector, geography, or other portfolio segments. Managers can then run stress tests and “what-if” scenarios to estimate potential losses and see how changes in credit conditions could affect the portfolio.
WIth the data it provides, asset managers can more accurately set risk limits, compare risk and return, and assess how a new investment or portfolio change could affect overall risk.
However, the quality of the analysis depends on the credit data and assumptions fed into the model. If borrower-level PDs or ratings are poorly calibrated, the portfolio-level results may also be less reliable.
c. Internal Risk Models
Best for: Managers who need a risk framework designed around their own portfolio, investment strategy, and internal processes.
Asset managers build internal risk models to measure credit and portfolio risk using its own data, assumptions, and methodology. They can cover borrower-level measures such as PD and LGD, as well as portfolio-level measures such as expected loss, concentration risk, correlations, and stress losses.
Their main advantage is flexibility. A manager can tailor the model to its own lending strategy, borrower mix, deal structures, collateral, covenants, and risk limits. Internal models can also support underwriting, portfolio construction, ongoing monitoring, and scenario analysis.
However, most importantly, internal models depend on the quality of the data, assumptions, and validation behind them. In private credit, where there’s usually limited default history and a lack of external market signals, it’s usually difficult to test whether the model is well calibrated.
How the Five Parts of the Stack Work Together
Each part of the software stack answers a different question about the portfolio, but the outputs from one layer often inform the next. Suppose a private credit fund makes a loan to a mid-sized company.
- Independent credit intelligence gives the manager an external view of the borrower’s credit quality and helps test its internal rating or PD.
- Portfolio data and administration software records the loan and its key terms, including the balance, interest rate, maturity, and payment structure.
- After the loan closes, monitoring and covenant management software tracks the borrower’s financial performance, reporting obligations, and covenant compliance. If earnings weaken or a covenant is breached, the team can investigate the change.
- Valuation software uses the latest available information to support an estimate of the loan’s fair value, which is especially important when there is no active market price.
- Risk modelling software then measures how the position affects the wider portfolio, including expected loss, concentration risk, and potential losses under stress.
The layers are connected. Weak borrower data can affect covenant analysis, just as poorly calibrated credit inputs can weaken stress tests and stale performance information can affect valuation. That’s because each category answers a different question.
How to Choose a Private Credit Portfolio Analysis Software Stack
The right stack depends on where the investment process has gaps and how well different tools complement one another. Key considerations include:
- Gaps in the current workflow. Heavy use of Excel, manual data entry, email, or disconnected systems can indicate operational weaknesses. Analytical gaps matter too, particularly when private borrowers have no external credit reference.
- Private and unrated borrower coverage. Database size alone says little about usefulness. What matters is how much of the actual portfolio a provider can cover, especially where borrowers lack public ratings or other market-based credit signals.
- Update frequency. Borrower financials, credit assessments, covenant data, and other risk inputs may refresh on different schedules. Less frequent updates can leave teams working with information that no longer reflects the borrower’s current position.
- Methodology. Ratings, PDs, and risk scores can come from agency analysts, private rating analysts, quantitative models, consensus assessments, or internal models. Each source provides a different type of evidence, so understanding the methodology helps clarify what role the output can play in portfolio analysis.
- Integration. APIs, data feeds, exports, common entity identifiers, and compatibility with existing systems affect how easily information moves across administration, monitoring, valuation, and risk workflows. Poor integration can reintroduce the manual reconciliation that software is meant to reduce.
- Overlap between providers. Multiple tools can end up solving the same problem while leaving another part of the workflow uncovered. A stronger stack combines complementary capabilities, with each provider serving a clear role.
Closing the Benchmarking Gap in Your Private Credit Software Stack
A complete private credit software stack should cover five core functions: independent credit intelligence, portfolio data and administration, borrower and covenant monitoring, valuation, and risk modelling. Each serves a different purpose, and gaps in one area can weaken the analysis produced elsewhere.
The independent credit intelligence layer deserves particular scrutiny because private borrowers often lack the public ratings and traded market signals available in public credit. The right solution depends on the type of external evidence a manager needs and, crucially, which borrowers its existing sources do not cover.
Credit Benchmark can help managers identify that gap by matching their portfolio against its consensus credit dataset. A coverage assessment shows which borrowers already have Credit Benchmark consensus ratings and where independent credit validation is still missing.
Book a free portfolio coverage assessment with Credit Benchmark to see how much of your private credit portfolio can be independently benchmarked.
Frequently Asked Questions
What is private credit portfolio analysis software?
Can private credit funds manage portfolios in Excel?
Does one platform cover the full private credit analysis workflow?
What should asset managers look for in private credit portfolio analysis software?
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