Credit analysis: how leveraged finance bankers read a borrower

The group's version of valuation

Ask an M&A or equity research candidate how they value a company and you get a DCF, comps, and precedent transactions. Ask a leveraged finance candidate the equivalent question and the honest answer is different: leveraged finance does not primarily value a company, it sizes how much debt that company can safely carry. Credit analysis is the toolkit for answering that question, and it is worth thinking of it as this group's version of valuation, the analytical lens everything else in the job runs through, from structuring a deal in the first place to deciding whether a covenant package is appropriate.

Three families of metrics do almost all the work: leverage, which measures how large the debt load is; coverage, which measures whether cash flow is sufficient to service it; and free cash flow conversion, which measures how much of that cash flow actually survives the business's other obligations to be available for debt service or paydown. None of the three means much in isolation. A leveraged finance banker's real skill is reading them together, over time, against a downside case, not reciting any one of them as a verdict.

Leverage: how big is the debt load, relative to what

The most common leverage measure is total debt divided by EBITDA, sometimes net debt (total debt minus cash) divided by EBITDA when cash is meaningful and available to pay down debt. A business with $1.4 billion of debt and $200 million of EBITDA is levered 7.0 times. On its own, that number tells you almost nothing about whether the business is in trouble or perfectly healthy, because leverage tolerance depends entirely on the stability and growth trajectory of the earnings underneath it.

This is the single most important mindset shift credit analysis requires: leverage ratios are not graded on an absolute scale, they are graded relative to the cash flow's reliability. A stable, non-cyclical business with high recurring revenue can comfortably support leverage that would be dangerous for a cyclical, capital-intensive business with volatile earnings, because the first business is far less likely to see EBITDA fall sharply in a downturn and suddenly find its leverage ratio has spiked without the debt itself changing at all. A leveraged finance banker sizing a deal has to make exactly this judgment, which is why the same 7.0 times leverage figure that looks perfectly reasonable in a worked LBO financing example for one type of business would be recklessly aggressive for another.

Coverage: can cash flow actually service the debt

Leverage tells you how big the debt is; coverage tells you whether the company can actually make its payments. Interest coverage, EBITDA divided by interest expense, is the simplest version: how many times over can operating earnings cover the interest bill alone. A more demanding version, fixed charge coverage, also counts mandatory principal amortization and other contractual obligations in the denominator, testing whether the company can meet everything it is on the hook for, not just interest. The precise construction of fixed charge coverage, and how it differs from simple interest coverage in practice, is covered at the definitional level in the leveraged finance terms guide; what matters here is how a banker actually uses the ratio rather than how it is defined.

The practical use is trend and headroom, not the raw number in isolation. A company sitting comfortably above its coverage requirement today but trending downward over several quarters is a different credit story than one sitting at the same level but trending up, even though the current snapshot looks identical. Coverage ratios in a credit agreement are typically set with negotiated cushion against a base case forecast, meaning the actual test level sits meaningfully below where the company expects to run, so that normal variance in performance does not immediately trip a covenant. A banker sizing a new deal has to estimate that cushion explicitly: not just "does the company pass today" but "how much can performance miss the plan before this ratio becomes a real problem."

Free cash flow conversion: what actually survives to pay down debt

EBITDA is a starting point, not the finish line, because a real business has obligations between EBITDA and the cash that is actually available to service or pay down debt. Free cash flow conversion measures how much of EBITDA survives capital expenditures, changes in working capital, cash taxes, and any other recurring cash outflows to become cash genuinely available for debt service.

Two businesses with identical EBITDA and identical leverage ratios can have completely different credit profiles once you look at conversion. A software business with minimal capital expenditure needs might convert 80 percent or more of its EBITDA into free cash flow. A heavy manufacturer with constant capital reinvestment needs might convert well under half of the same EBITDA figure into cash actually available to pay lenders. The manufacturer is a meaningfully riskier credit at the same leverage multiple, purely because so much less of its earnings actually reaches the point where it could service debt, and a leveraged finance banker who sizes both businesses to the same leverage tolerance without accounting for this difference is making a real analytical mistake, not a minor oversight.

Leverage through the capital structure, not just at the total level

A single total leverage figure also hides where in the capital structure that debt actually sits, and a sophisticated credit read always breaks leverage down by layer, not just in total. A first lien lender does not really care about total leverage the way an unsecured noteholder does; they care about first lien leverage specifically, meaning how much debt sits at or above their own position in the structure covered in the leveraged debt capital structure: seniority and security, because that is what determines their own cushion in a downside. A business at 7.0 times total leverage but only 4.0 times through the first lien debt is telling secured lenders a much more comfortable story than the total figure alone suggests, since 3.0 turns of that leverage sits junior to them and would have to be wiped out before their own recovery is impaired.

This is exactly why leveraged finance analysis is usually presented as leverage "through" each layer: through the revolver, through the first lien term loan, through second lien debt, through senior unsecured notes, building up to total leverage at the bottom of the equity cushion. A candidate who can talk about leverage through a specific tranche, not just in total, is demonstrating the layered thinking that seniority and security actually demand, rather than treating the capital structure as one undifferentiated pool of debt.

Reading the trend, not just the snapshot

The credit stats above are almost always presented as a multi-year trend in real credit analysis, projected forward under both a base case and a downside case, because a lender's real exposure is to where the business is going over the life of the loan, not to where it happens to sit on the day the deal is signed. A company at 6.0 times leverage growing EBITDA steadily and generating strong free cash flow conversion is telling a completely different story from a company at the same 6.0 times leverage with flat or declining EBITDA and thin conversion, even though a single snapshot ratio would look identical for both. Building and stress-testing that forward trajectory, not just calculating the current ratios, is what most of a leveraged finance analyst's actual model work consists of.

This is also where the downside case earns its importance. A credit team does not size a deal to what the business can support if everything goes according to plan; it sizes the deal to what the business can support if performance disappoints by some meaningful margin, because the whole point of covenant cushion and conservative leverage sizing is to survive a scenario worse than the base case, not to look good in the base case alone. A candidate who only discusses the base case numbers in an interview, without volunteering how those numbers would look in a reasonable downside, is missing exactly the part of credit analysis that separates it from a simple valuation exercise.

How credit analysis shapes what a borrower can raise, and from whom

The output of all this analysis is not just a number, it is a direct input into structuring: how much total debt a deal can carry, how that debt should split across tranches, and what covenant package each tranche should reasonably carry given who will buy it. A full worked example of that translation, from purchase price through a finished sources and uses table, is in how an LBO actually gets financed, and the same credit lens applies just as directly when the question is not a new acquisition but whether a company has room to raise fresh debt for a dividend recapitalization.

How this differs from a rating agency's view

It is worth distinguishing the credit analysis described here from the formal credit rating process a bank runs in parallel on rated deals. A rating agency is producing a rating for a broad investor base using its own, somewhat standardized methodology, comparing the borrower against a wide universe of similarly rated issuers. The bank's own internal credit view, and the sponsor's, is sharper and more deal-specific, built for the narrower purpose of deciding exactly how much leverage this particular structure should carry and what covenant cushion it needs. Both processes matter, and both draw on the same underlying leverage, coverage, and conversion metrics, but a candidate should not conflate "what rating will this get" with "how much debt can this business actually support," because they are related but genuinely different questions.

Practice question

A company has $1.2 billion of debt, $200 million of EBITDA, and free cash flow conversion of 50 percent. Another company has the same debt and EBITDA but converts 80 percent of EBITDA to free cash flow. Which is the better credit, and why?

Both companies show the same 6.0 times leverage on a simple debt-to-EBITDA basis, but they are not equally good credits, because leverage only tells you the size of the obligation, not whether cash flow can actually service it. The company converting 80 percent of its EBITDA to free cash flow, roughly $160 million here, has meaningfully more cash available for debt service and paydown than the one converting 50 percent, which only generates about $100 million. That gap usually comes down to differences in capital intensity or working capital needs, a business with heavier capex or working capital swings eats into EBITDA before it ever becomes cash a lender can count on. All else equal, I'd view the higher-conversion business as the stronger credit at the same leverage multiple, because it has more real cushion to absorb a downturn or an unexpected cash need without straining its ability to make payments, and I'd want to size any new debt for the lower-conversion business more conservatively, or price it with a wider spread, to reflect that weaker underlying cash generation.

What the interviewer is listening for: whether you recognize that identical leverage ratios can mask very different credit risk, and whether you can name the specific driver, free cash flow conversion, rather than gesturing vaguely at "cash flow quality" without pinning down the mechanism.