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In any private equity debt financing, term sheet stage is one of the most consequential parts of the process. By the time five, ten, or even twenty lenders return their bids, the deal team faces a flood of structures, pricing assumptions, and conditions, each written in slightly different language. The pressure is to compare them quickly and accurately, then drive the best outcome for the sponsor.
Most teams still do this in a master Excel sheet. Someone copies pricing from each lender’s Word document, lines up covenants, and tries to keep the columns straight. The problem is well known. Side-by-side lender bid comparison done manually in spreadsheets leads to errors and delays, and even small mistakes can cost real money on a large facility.
This guide explains how PE sponsors and debt advisors can compare lender term sheets efficiently. It covers what to evaluate, where manual comparisons break down, and how a structured approach to lender term sheet comparison in private equity removes errors and accelerates close.
Lender term sheet comparison is the structured process of evaluating competing debt bids during a private equity financing. After the lenders return their proposed commercial terms, the deal team puts each term sheet side by side. It analyzes them on a consistent set of variables, including pricing, leverage, covenants, fees, and conditions.
In leveraged finance, this comparison is also known as the gridding process. The name comes from the practice of arranging each lender’s terms into a grid format so that any column can be compared at a glance.
Done well, gridding gives the sponsor or debt advisor a clear view of where each lender is competitive and where they are not, which is what powers the next round of negotiation. For a wider primer, see A Primer on Capital Markets in Private Equity.
On most PE deals, side-by-side lender bid comparison is still done manually in Excel. A junior team member copies pricing, leverage, and covenants from each lender’s Word term sheet into a master tab. The deal partner reviews the result. The team negotiates from there.
The friction shows up in five places, every time.
These are not theoretical issues. The article Term Sheets in Word: The Drawbacks walks through how document-based term sheets compound this problem on every refinancing and add-on financing.
Before any comparison can be efficient, the deal team needs a fixed set of variables to score each lender against. The variables below are the standard for leveraged finance term sheets in PE.
Pricing
Compare margin (basis points over base rate), original issue discount, upfront fees, ticking fees, and call protection. Look at headline pricing and effective all-in pricing across the expected hold period.
Leverage and structure
Compare total leverage on a net and gross basis, senior leverage, and the split between term loan, revolver, and any second lien or unitranche components. Different lenders price the same risk at different leverage levels.
Covenants
Compare maintenance covenants, incurrence covenants, cushions to base case, and any springing or holdco-level structures. Covenant flexibility often matters more than headline margin over the life of the loan.
Fees and economics
Capture upfront fees, commitment fees, agency fees, and any underwriting or arrangement fees. Fee economics often look small per item but add up fast.
Call protection and prepayment
Compare non-call periods, soft and hard call premiums, and make-whole provisions. This shapes optionality on refinancing during the hold period.
Conditions and certain funds
Compare conditionality on closing, MAC clauses, and any market flex provisions. On larger UK deals, certain funds protections matter as much as pricing for execution risk.
Hold size and distribution
Compare each lender’s intended hold versus distribute, plus any club requirements. A lender that intends to syndicate post-close behaves differently to one that intends to hold to maturity.
The process below replaces the master Excel sheet with a structured workflow. It is the same six-step sequence that high-performing UK sponsors and debt advisors run on every leveraged finance bid.
Set the variables you will compare on before any lender returns a term sheet. This includes pricing, leverage, covenant headers, fees, and conditions. A pre-built template prevents the team from rebuilding the comparison logic each time bids land.
When a bid lands as a Word term sheet, the next move is critical. Either translate it into structured fields right away, or accept that you will spend hours later fighting against unstructured data. A digital term sheet on Termgrid lets lenders submit bids directly into a structured grid, which removes the manual translation step.
Different lenders use different language for similar concepts. Map each bid against a single dictionary of terms. This sounds basic but it is the single highest-leverage step. Once every lender’s covenant, fee, or call protection sits under the same standardized header, real comparison becomes possible.
With normalized data in hand, build the grid. Each lender is a column. Each variable is a row. The team should be able to read across any row and instantly see who is best, who is in the middle, and who is off-market. This is the heart of the gridding process. Grids: The Telltale Sign of Growing Competition in Private Credit Markets covers how grids surface competitive dynamics that a flat list cannot.
A bid does not exist in isolation. Compare each lender’s current position to what they have agreed in past deals using Precedent Search, and to your relationship history with them via Relationship Insights. A lender holding back today on margin may have stretched on a similar deal six months ago, which is useful negotiation leverage.
Final negotiations should happen against the grid, not against multiple Word documents. Work down the rows, push tighter pricing where the bid is off-market, push softer covenants where there is room, and confirm conditions in writing as you go. The grid becomes the single source of truth for the entire team and for the eventual lawyers.
If your team is still running the comparison in Excel, the table below shows where mistakes typically creep in and what each one actually costs.
|
Common Error |
Where It Happens |
Real-World Cost |
|
Margin typo |
Pricing row, copy-paste from Word |
Misallocated bid, lost basis points |
|
Mismatched leverage definition |
Net vs gross leverage row |
Wrong lender selected on leverage |
|
Buried covenant |
Footnote in source document |
Late-cycle covenant breach risk |
|
Stale version |
Multiple copies of master sheet |
Decisions made on yesterday’s data |
|
Missing fee item |
Fee schedule appendix |
All-in pricing understated |
|
Inconsistent call protection format |
Soft call vs hard call rows |
Refinancing optionality miscalculated |
The difference between running term sheet comparison in Excel and running it on a structured platform is not a feature comparison. It is a workflow shift. Here is what changes.
|
Dimension |
Manual Spreadsheet |
Structured Grid Platform |
|
Bid capture |
Manual copy-paste from Word |
Lenders submit into structured fields |
|
Terminology |
Inconsistent across bids |
Normalized against a single dictionary |
|
Comparison view |
Static, hand-built |
Live grid, refreshes in real time |
|
Error rate |
High, no source-of-truth check |
Low, structured validation |
|
Negotiation cycle |
Slow, document-based |
Fast, grid-based |
|
Audit trail |
Scattered emails |
Centralized history per bid |
|
Post-close reuse |
Manual handover |
Auto-flow into Portfolio Management |
Five practical habits separate the deal teams that close cleanly from the ones that lose days to spreadsheet errors.
For a wider view of the surrounding workflow, the article Top Five Tips for Managing a Debt Process is a useful companion read.
Termgrid is a purpose-built SaaS platform for private capital markets, created by industry professionals to digitize the manual, document-driven process of arranging institutional debt. The term sheet module sits at the heart of the bid comparison workflow.
For sponsors and debt advisors comparing lender bids, Termgrid centralizes the workflow:
As of May 2026, more than 30,000 active users across 1,600 institutions, including KKR, Bridgepoint, EQT, Permira, Apax, and Charlesbank, run their debt financings on Termgrid. Combined client AUM exceeds $4.8tn, and the platform has supported debt financings worth more than $1tn. Users save roughly one day a week on debt workflows. To see how this plays out in practice, see the Sponsor Deal Execution case study.
The most efficient method is a structured side-by-side grid, with every lender bid mapped to a single set of standardized variables. Pricing, leverage, covenants, fees, call protection, and conditions should sit under fixed headers, with normalized terminology across every bid. This avoids the version control and copy-paste errors that plague spreadsheet-based comparisons.
Prioritize the variables that have the largest economic impact across the hold period. These are pricing, total and senior leverage, covenant package, fee structure, and call protection. Then evaluate certain funds language, hold versus distribute intent, and any conditionality that could affect execution. Headline margin alone is a poor proxy for the full economics of a debt facility.
Excel was not built for term sheet comparison. There is no validation against the source document, terminology varies across lenders, multiple versions of the master sheet circulate at once, and conditions buried in footnotes rarely make it into the spreadsheet. The article Term Sheets in Word: The Drawbacks covers how document-based workflows compound the problem.
On a structured workflow, A clean side-by-side comparison of eight to fifteen lender bids can typically be ready within a day of the final bid landing. Manual workflows can often take three to five days or more, with continued reconciliation through the negotiation phase. The difference shows up in close timeline and in negotiating leverage.
Yes, on the comparison itself. Platforms like Termgrid let lenders submit bids directly into a structured grid, normalize terminology automatically, and surface a live side-by-side view across every variable. Excel still has a place for ad-hoc modelling, but the central comparison workflow benefits from a purpose-built tool. Schedule a call to see this in practice.
Lender term sheet comparison in private equity is too expensive to run on a master Excel sheet. The errors are real, the delays are measurable, and the negotiating leverage you lose is hard to win back.
Move the comparison onto a structured grid, normalize terminology before the bids land, and bring precedent and relationship data into the same view. The deal teams that adopt this approach close faster, with sharper terms and far fewer late surprises.
Schedule a call with Termgrid to see how the digital term sheet, gridding workflow, and Demand Tracker turn lender bid comparison into a controlled, error-free process.
Termgrid
Termgrid connects deal execution data to ongoing debt portfolio monitoring. Track covenants, capital structures, amortisation, maturities, and hedging positions in one place.
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