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Financial due diligence is a buyer-side investigation of a target company’s historical financial performance, conducted before an acquisition closes. Its purpose is to test whether reported earnings are accurate, sustainable, and supported by the underlying accounting records.

It is not an audit. An audit expresses an opinion on whether financial statements comply with an accounting framework. Financial due diligence asks a different question: what will this business actually earn under new ownership, and what is the buyer really paying for. The work typically covers earnings quality, working capital, debt and debt-like items, revenue durability, and cost structure.

Financial due diligence typically includes a Quality of Earnings analysis, a net working capital analysis, a proof of cash, a review of debt and debt-like items, and an assessment of revenue and customer concentration.

A standard lower middle market scope covers:

• Quality of Earnings. Normalizing reported EBITDA for non-recurring, non-operating, and owner-discretionary items.
• Net working capital. Monthly trending to set the working capital target written into the purchase agreement.
• Proof of cash. Tying reported revenue and expenses to actual bank activity.
• Debt and debt-like items. Deferred revenue, accrued vacation, capital leases, unpaid payroll taxes, deferred compensation.
• Revenue analysis. Customer concentration, churn, retention, pricing, and mix.
• Cost structure. Gross margin by product and customer, and fixed versus variable cost behavior.
• Balance sheet review. Receivables aging, inventory valuation, fixed assets, related-party balances.
• Forecast assessment. Whether management projections are consistent with historical performance.

Scope varies by provider. Buyers should confirm in writing which of these are included rather than assume the list is standard.

A traditional financial due diligence engagement usually takes three to six weeks from data room access to final report. Smaller transactions with clean accounting can finish in two to three weeks. Deals with multiple entities, cash-basis books, or missing periods commonly run eight weeks or longer.

The dominant variable is not deal size, it is data readiness. Most delay comes from incomplete general ledger exports, unreconciled intercompany accounts, and slow seller response to follow-up requests, not from analytical difficulty. A buyer who resolves data access before the engagement starts removes most of the calendar risk.

A Quality of Earnings analysis tests whether a company’s reported earnings reflect sustainable, recurring operating performance. It produces a normalized or adjusted EBITDA figure, supported by a bridge showing every adjustment made to the reported result.

Because purchase price in most middle-market deals is a multiple of adjusted EBITDA, each dollar of adjustment moves valuation by that dollar times the multiple. At a 5x multiple, a disputed $200,000 add-back is a $1 million argument. A QoE also examines revenue recognition policy, margin trends, and the accounting basis of the books, since a normalized figure is only as reliable as the records beneath it.

A Quality of Earnings report is one component of financial due diligence. Financial due diligence is the broader engagement, and the QoE is the earnings-focused deliverable inside it.

In practice the terms are used loosely, and many providers sell a "QoE" that also covers working capital, debt-like items, and revenue analysis. The distinction matters at scoping. A buyer who commissions only a QoE may receive a normalized EBITDA figure with no working capital target, no proof of cash, and no debt-like items schedule, all three of which change the final purchase price and the terms of the agreement.

The core request is three years of financial statements, monthly profit and loss statements, monthly balance sheets, trial balances, general ledger detail, bank statements, and receivable and payable aging reports.

A complete request list also includes:

• Tax returns covering the same three years
• Payroll registers and an employee census
• Revenue detail by customer by month
• Material customer and vendor contracts
• Debt agreements and lease schedules
• Fixed asset register with depreciation schedules
• Inventory reports and the valuation methodology used
• Related-party transaction detail
• Any add-back schedule already prepared by the seller or their advisor

The general ledger is the item most often left off and the item most necessary. Summary financial statements cannot support an EBITDA adjustment, because the adjustment lives in individual entries. Transaction-level detail can.

Buyers find problems by testing the statements against the underlying accounting records rather than reading the statements on their own. Issues surface at transaction level, in timing, classification, and breaks in pattern.

The techniques that produce the most findings:

• Trend revenue and gross margin monthly rather than annually, which exposes smoothing that annual figures hide.
• Tie reported revenue to cash receipts, which catches recognition ahead of delivery.
• Review manual journal entries posted near period ends, where discretionary classification concentrates.
• Compare each period’s expense classification against the others, since inconsistency is the most common signal.
• Search the ledger for related-party names and for round-number entries.
• Test whether items labeled non-recurring appear in more than one year.

Most material problems in this size range are not sophisticated. They are inconsistent classification and undocumented adjustments that persist because nobody read the ledger.

A Quality of Earnings analysis is used to set and defend purchase price. Because valuation is a multiple of adjusted EBITDA, the QoE determines the number that multiple applies to.

It serves three audiences with different needs. Buyers use it to test seller claims and support negotiation. Lenders and private credit funds require it to size debt against sustainable cash flow. Investment committees treat it as the analytical basis for approval. Sellers increasingly commission sell-side QoE reports before going to market, to pre-empt buyer adjustments and protect valuation.

An EBITDA add-back is an expense added back to reported earnings because it is non-recurring, non-operational, or will not continue after the transaction closes. Add-backs raise adjusted EBITDA and therefore raise valuation.

Owner compensation is the standard example. A founder paying themselves $500,000 in a business that would pay a professional manager $200,000 creates a $300,000 add-back, because that excess cost disappears under new ownership. The logic is forward-looking, which is the source of most disputes: an add-back is valid only if the buyer genuinely will not incur the cost. Add-backs are the most contested element of most lower middle market negotiations.

The most common are owner compensation normalization, personal expenses run through the business, non-recurring professional fees, one-time legal settlements, and rent adjusted to market rate on related-party property.

Others that appear regularly:

• Non-recurring severance or restructuring costs
• Discontinued product lines or closed locations
• Above or below market salaries paid to family members
• Transaction costs from the current sale process
• Accounting basis corrections, including cash to accrual conversion errors
• Deferred maintenance or capital expenditure misclassified as operating expense
• Insurance proceeds, litigation recoveries, or government subsidies
• Inventory and reserve adjustments that belonged to earlier periods

Add-backs are identified by reviewing general ledger transaction detail, not summary financial statements. Analysts examine individual entries, vendor names, account classifications, posting dates, and manual journal entries to isolate costs that are non-recurring or unrelated to ongoing operations.

The working process is: obtain the full general ledger, foot it to the trial balance, scan for unfamiliar vendors and round-number entries, test expense accounts with high period-over-period variance, review manual and reversing entries, then cross-reference candidates against bank records and invoices.

Sellers usually arrive with a prepared add-back schedule. That schedule is a hypothesis to be tested against the ledger. It is not evidence.

A legitimate add-back is traceable in the general ledger, documented, and genuinely will not recur under new ownership. All three conditions have to hold, and most disputed add-backs fail on the second.

The five tests a buyer should apply to every line:

• Traceable. The item ties to specific journal entries and a specific amount, not to a management estimate.
• Documented. An invoice, contract, settlement agreement, or payroll record supports it.
• Non-recurring in fact. The item appears in one period only, rather than reappearing in a different form every year.
• Not operationally required. The business can run without the cost after close.
• Consistently treated. The same category of expense is handled the same way across all periods presented.

An add-back that fails the documentation test is an assertion. An add-back that fails the non-recurrence test is usually a normal operating cost that has been relabeled.

An aggressive add-back adds back a cost that is actually recurring, is unsupported by documentation, or was never incurred at all. The most aggressive versions add hypothetical income rather than removing real expense.

The recurring patterns:

• The recurring one-time item. A one-time legal expense that appears in all three years presented.
• Pro forma revenue. Projected sales from a new product, or a contract signed but not yet started.
• Unrealized synergies. Cost savings or headcount reductions that have not been executed.
• Run-rating. Annualizing the strongest quarter and presenting it as the baseline.
• Undocumented owner perks. Personal expenses claimed without any transaction support.
• Capitalization shifts. Moving ordinary operating expense onto the balance sheet.
• Macro normalization. Unquantified adjustments for a bad year attributed to external conditions.

The reliable test is documentation. Legitimate add-backs come with support. Aggressive add-backs come with explanation.

Each adjustment is mapped to the specific general ledger accounts and journal entries that produced it, with amounts by period. Those account totals must foot to the trial balance, and the trial balance must tie to the financial statements.

The deliverable is a bridge. It starts from reported net income or reported EBITDA, lists each adjustment as a separate line carrying a general ledger reference, and arrives at adjusted EBITDA. Every line should be traceable in one step to the entries beneath it. An adjustment that cannot be tied to a specific account and period is an estimate, and the report should label it that way. Unreconciled adjustments are the first thing an experienced lender or investment committee challenges.

Because add-backs exist at transaction level and financial statements only show totals. A profit and loss statement showing $1.2 million in professional fees does not reveal whether that is recurring accounting work or a single litigation matter.

Only the general ledger shows individual entries, vendor detail, posting dates, manual journal entries, and account classification. That detail is what separates a supportable adjustment from an assumption. It also exposes problems invisible in summary form: entries posted after period close, reversing entries, intercompany transfers, and expenses recorded in the wrong period.

A QoE built only on financial statements can restate what management reported. It cannot independently test it.

AI-powered financial due diligence uses machine learning and language models to read accounting data at transaction level, classify entries, reconcile records, and surface candidate findings in hours rather than weeks.

The practical difference is coverage. A human team samples, because reading every line of a ledger with more than 100,000 entries is not feasible on a deal timeline. It reviews the largest accounts and the most unusual entries and accepts the rest. Software reads all of it. The role is breadth and speed at the data layer, producing a structured set of findings that a professional then reviews, tests, and signs off on.

AI can do most of the data work: ingesting general ledger and trial balance files, normalizing charts of accounts, reconciling records, detecting anomalies, and proposing EBITDA adjustments with the supporting entries attached. It cannot replace professional judgment or attestation.

What it does well is high-volume, rule-consistent analysis across a complete dataset. What it cannot do is interview management, negotiate an adjustment with a seller’s advisor, interpret contractual nuance, or take professional responsibility for a conclusion. The realistic model is sequencing rather than substitution: use software to establish the factual picture fast, then apply human judgment where judgment is what is actually needed.

AI is used for data ingestion, chart of accounts normalization, reconciliation, anomaly detection, and first-pass adjustment identification.

The concrete applications:

• Parsing general ledger, trial balance, and financial statement files across different accounting systems and formats
• Mapping inconsistent chart of accounts structures into one framework, including across mid-year system migrations
• Footing the general ledger to the trial balance, and the trial balance to the financial statements
• Flagging unusual entries: round numbers, period-end concentrations, reversing entries, unfamiliar vendors, out-of-pattern amounts
• Building monthly revenue, margin, and expense trends from transaction detail rather than from summaries
• Identifying candidate EBITDA adjustments with underlying entries attached
• Generating structured findings summaries and targeted seller information requests

The output is a starting position, not a conclusion. What it compresses is the weeks normally spent assembling the picture.

Yes. General ledger analysis is the strongest application, because the task is high-volume pattern recognition over structured data.

Software reads a full ledger regardless of size, standardizes account naming, groups transactions by vendor and category, trends accounts monthly, and identifies entries that deviate from established pattern. It handles cash-basis books and multi-entity structures where consolidation is manual. On one Quebec mandate, AddBack processed 177 documents and more than 130,000 accounting entries, and arrived at a normalized EBITDA within $2,000 of the accounting firm’s databook.

Yes. Anomaly detection is a core strength, because an unusual transaction is defined by deviation from pattern, and pattern detection across large datasets is a machine task.

Typical flags:

• Round-number entries in accounts that normally carry precise amounts
• Transactions concentrated in the final days of a period
• Manual journal entries in accounts that are usually system-generated
• Reversing entries and duplicate payments
• Vendors appearing once at a material amount
• Names suggesting related-party activity
• Expenses recorded outside their normal period
• Amounts sitting just below an approval threshold

A flag is a question, not a finding. Many anomalies have legitimate explanations. The value is that nothing material goes unexamined, not that the software is right about any single item.

Yes, and this is the cleanest use case, because reconciliation is deterministic and has a verifiable right answer.

Software foots every ledger account to its trial balance total, identifies variances by account and period, detects unbalanced journal entries, and traces the trial balance up to the financial statements. It also handles the messy version: multiple entities, account codes that changed mid-period, and accounting system migrations, all of which consume analyst days when done manually.

When the reconciliation does not tie, the variance is often the most useful early finding in a deal.

Yes. Software reviews general ledger detail and proposes candidate adjustments with supporting entries attached, across the standard categories: owner compensation, personal expenses, non-recurring professional fees, one-time settlements, related-party rent, and discontinued operations.

The distinction that matters is between identifying a candidate and concluding on it. Software can find a $340,000 legal expense, confirm it appears in one period only, and tie it to specific entries. Whether it qualifies as non-recurring depends on facts outside the ledger: the nature of the dispute, whether similar exposure remains, and how the buyer intends to treat it. That call belongs to a professional, working from a complete picture rather than a sample.

No, and buyers should be skeptical of anyone claiming otherwise.

A QoE report carries professional responsibility. Lenders, private credit funds, and investment committees rely on it because a named firm stands behind the conclusions. Software carries no such accountability, cannot conduct management interviews, and cannot exercise judgment on the negotiated questions that determine final adjustments.

The useful role is upstream. Establish the financial picture before a QoE engagement begins, so buyers know what they are buying before committing to full diligence spend, and so the QoE team starts from a reconciled base rather than a data room.

The main limitations are absence of professional accountability, dependence on data quality, inability to gather information outside the accounting records, and constrained judgment on contested items.

• No attestation. Software cannot issue an opinion a lender or investment committee can rely on.
• Data dependent. Incomplete or badly maintained ledgers limit what any analysis can conclude.
• No management access. Interviews often explain anomalies that records alone cannot.
• Limited context. Contract terms, litigation posture, and industry norms sit outside the general ledger.
• Judgment on contested items. Whether an add-back survives negotiation is a professional call.
• Verification required. Flagged items need human review, and treating output as conclusion is a real risk.

Used as a screening and preparation layer, these limitations are manageable. Used as a substitute for professional diligence, they are not.

Traditional financial due diligence is a professional service engagement delivering a signed report over three to six weeks. AI due diligence software is a tool that analyzes accounting data in hours and produces findings without professional attestation.

They are sequential rather than competing. One tells a buyer whether to proceed. The other supports closing.

AddBack analyzes complete general ledger data and returns normalized EBITDA and financial findings in hours. A traditional QoE process takes three to six weeks and delivers a report with professional sign-off.

AddBack is built for the decision that comes before that engagement: whether a target deserves full diligence spend at all. It reads every entry rather than sampling, reconciles the ledger to the trial balance, and produces an adjustment bridge with entry-level support. It does not issue an opinion a lender can rely on, and it does not negotiate adjustments with the other side.

Most buyers use both. AddBack to screen and prepare, a QoE firm to confirm and sign. Screen first. Spend second.

Indirectly, in two ways: by preventing spend on deals that should not have reached diligence, and by reducing the hours a QoE team spends on data assembly.

The larger saving is avoided cost. A buyer who commissions full diligence on five targets to close one absorbs four engagements of dead spend. Screening the ledger first means only viable targets reach that stage.

The second saving is scope. When a QoE team receives reconciled data with a mapped chart of accounts and an initial adjustment schedule, they spend their time on judgment instead of cleanup, which is where their rate is actually worth paying. Providers price partly on data condition, so arriving with clean data is a negotiating position.

Yes, mainly by compressing data preparation, which consumes most of the calendar time in a typical engagement.

Analysts routinely spend the first one to two weeks obtaining files, resolving format problems, mapping the chart of accounts, and reconciling the ledger to the statements. Automating that removes most of it. It also front-loads the information request: knowing on day one which accounts are unclear means seller follow-ups happen once rather than across three rounds, and seller response time is the delay buyers control least.

Analysis and negotiation still take professional time. The realistic gain is on assembly, not on judgment.

Nearly all of the factual groundwork. Before an engagement begins, a buyer can already have a normalized EBITDA estimate, a reconciled ledger, transaction-level trends, a flagged anomaly list, and a targeted seller information request.

• A normalized EBITDA estimate with an entry-level supporting bridge
• Confirmation that the ledger foots to the trial balance and up to the statements
• Monthly revenue and gross margin trends built from transactions rather than summaries
• A flagged list of unusual entries, vendors, and period-end activity
• Customer concentration and revenue durability detail
• A targeted seller information request list

That package changes the character of the engagement. The QoE team starts from a reconciled position instead of a data room, and the buyer walks in knowing which findings to press.

Use software early, when the question is whether a target is worth pursuing. Use a QoE provider late, when the question is whether the deal can close and be financed.

• Pre-LOI and early exclusivity. Software. Fast, complete, and cheap enough to run on every target under consideration.
• Post-LOI confirmatory diligence. QoE provider. Required by lenders, expected by investment committees, and necessary for negotiating adjustments with the seller’s advisor.
• Both, in sequence. What most disciplined buyers do. Screen every target, commission full diligence only on the ones that survive.

The failure mode is using either alone: paying for full diligence on unqualified targets, or closing on software output with no professional sign-off.

Yes, and it is the most common use case. Running an analysis on the general ledger before engaging a QoE firm lets a buyer decide whether the deal justifies the cost, and gives the firm a cleaner starting point.

There is no conflict between the two. Sequencing them means diligence dollars go only to targets that already survived a complete look at their accounting records. Buyers doing this at volume, search funds, independent sponsors, and platform acquirers running multiple add-ons, see the largest effect on total spend, because their ratio of engagements to closings was the highest to begin with.

A Quality of Earnings report for a lower middle market transaction typically costs between $30,000 and $75,000. Smaller deals with clean books can come in between $15,000 and $30,000. Larger or more complex transactions, including multi-entity structures and cross-border deals, commonly exceed $100,000.

Pricing drivers, roughly in order of impact:

• Data condition. Cash-basis books, unreconciled accounts, and missing periods add hours before analysis begins.
• Number of entities. Each legal entity multiplies reconciliation work.
• Periods covered. Three years is standard, and each additional year adds cost.
• Scope. Whether working capital, proof of cash, and debt-like items are included or priced separately.
• Provider tier. National accounting firms price above regional and boutique providers.
• Timeline. Compressed deadlines carry a premium.

Most providers quote a range rather than a fixed fee, and the range widens when they have not yet seen the data.

For a business under $5 million in EBITDA, expect $15,000 to $40,000 for a scoped Quality of Earnings, and more if the engagement includes working capital, tax, and debt-like items analysis.

The problem this creates for smaller buyers is proportion. On a $3 million purchase price, a $25,000 engagement is close to 1% of the deal, and it is spent before the buyer knows whether the deal is real. Buyers acquiring at this size usually resolve this in one of three ways: negotiate a reduced scope, use a regional provider rather than a national firm, or screen the general ledger first and commission full diligence only on targets that clear the screen.

On a deal that closes, almost always. A QoE routinely identifies adjustments that move purchase price by more than the fee, and lenders generally require one regardless.

The economics are asymmetric in the buyer’s favor on a live deal. At a 5x multiple, finding $50,000 of unsupported add-backs changes price by $250,000 against a $40,000 fee. It also supports the working capital target and surfaces debt-like items that otherwise transfer to the buyer at close.

Where the value breaks down is on deals that do not close. Commissioning full diligence on a target that fails for reasons visible in the ledger is pure loss, and for buyers evaluating many targets that loss compounds. The answer is not to skip diligence. It is to sequence it.

The buyer pays for buy-side diligence, and the seller pays for a sell-side QoE they commission before going to market. Buy-side cost is not usually recoverable if the deal falls apart.

That allocation is what makes broken-deal cost a buyer problem. Sellers increasingly commission sell-side reports to control the earnings narrative early, and buyers should treat a seller-provided QoE as a useful starting document rather than a substitute for their own work. It was prepared by a firm the seller hired, to support the seller’s number.

The largest reduction comes from spending less on deals that never close, not from negotiating a lower rate.

• Screen before you commission. Analyze the general ledger before engaging a firm, so full diligence goes only to targets that survive.
• Arrive with clean data. Providers price partly on data condition, so a reconciled ledger and mapped chart of accounts lowers the quote.
• Scope deliberately. Pay for a full QoE, working capital, and debt-like items where the deal warrants it, not by default.
• Match provider to deal size. A national firm on a $4 million acquisition is usually overpaying for brand.
• Consolidate the request list. Three rounds of seller follow-up costs more than one well-built request.
• Reuse the screen. For platform acquirers running add-ons, one repeatable screening standard beats bespoke work per target.

The cheapest reliable method is to obtain the general ledger and test the seller’s add-back schedule against it, line by line, before commissioning a professional engagement.

Every claimed adjustment gets four questions: does the entry exist, is the amount right, is there documentation, and does a similar item appear in other periods. Most unsupportable add-backs fail one of those without any professional judgment required, because they fail on the arithmetic.

What this does not produce is a report a lender will accept, and buyers should not confuse the two. It produces a decision about whether the deal is worth paying to verify properly. Screen first. Spend second.

Request general ledger and trial balance data early, and analyze it before committing to a full engagement. Transaction-level data reveals whether reported EBITDA is supportable well before a QoE firm is involved.

An effective screen answers six questions:

• Does the ledger foot to the trial balance and up to the financial statements
• Do monthly revenue and margin trends look organic, or smoothed
• Are the seller’s proposed add-backs traceable to actual entries
• Is customer concentration disqualifying on its own
• Are there related-party or unusual entries that require explanation
• Is working capital seasonality going to change the price mechanism

Sellers sometimes resist releasing ledger data this early. The resistance is itself information. Reasonable buyers make the request under NDA as a condition of proceeding, and a seller with clean books rarely objects.

Before an LOI, review three years of financial statements, monthly profit and loss detail, the general ledger if obtainable, revenue by customer, and the seller’s add-back schedule.

The goal at this stage is not certainty. It is avoiding a price commitment that diligence will unwind. In priority order:

• Whether reported EBITDA traces to the accounting records at all
• Whether the seller’s add-backs are documented or merely asserted
• Monthly revenue trend, with attention to any recent inflection
• Customer concentration and contract durability
• Gross margin stability, and whether declines are being hidden by mix
• Working capital seasonality, since this becomes a purchase price mechanism
• Obvious debt-like items: deferred revenue, accrued vacation, unpaid payroll taxes

A price set on unverified EBITDA is a renegotiation scheduled for later, and renegotiating from an executed LOI is a materially worse position than pricing correctly at the start.

As early as you can get data, and again at each stage where new records arrive. The cost of finding a problem rises through the deal, from free before an LOI to expensive after exclusivity and reputational after close.

A workable sequence:

• Before the LOI. Ledger-level screen on earnings quality, concentration, and add-back support. Findings here cost nothing but time and can be priced into the offer or used to walk.
• During exclusivity. Confirmatory work on working capital, debt-like items, proof of cash, and tax exposure. Findings here are negotiable but you have already committed time and legal spend.
• Before close. Verification that nothing changed and that the working capital target still holds. Findings here are disruptive and often unrecoverable.

The highest-value red flags are revenue recognized ahead of delivery, non-recurring expenses that recur every year, gross margin decline masked by product mix, deteriorating receivable aging, and undocumented owner add-backs.

The working list:

• Revenue spikes concentrated in the final month or quarter before sale
• Add-backs presented without invoices, contracts, or payroll support
• Related-party transactions on non-market terms
• Unrecorded liabilities: accrued vacation, deferred revenue, unpaid payroll taxes
• Ledger totals that do not foot to the financial statements as presented
• Deferred maintenance or capital expenditure suppressing current-period cost
• Inventory or reserve levels inconsistent with historical practice
• Customer concentration paired with expiring or unwritten contracts
• Accounting system changes mid-period, or missing months
• Prior periods restated without clear explanation

Individually most of these have innocent explanations. Clustered, they usually mean reported EBITDA will not survive scrutiny.

Rebuild it from the general ledger rather than accepting the seller’s schedule. Start from reported net income, trace each claimed adjustment to specific entries, confirm the accounts foot to the trial balance, and test whether each item is genuinely non-recurring.

Sellers and their advisors almost always present adjusted EBITDA with an add-back schedule attached. That schedule is an argument, prepared by someone paid to maximize the number. Verification means checking each line against four questions: does the entry exist, is the amount accurate, is there documentation, and does a similar item appear in other periods.

This exercise moves price more reliably than any other single piece of pre-LOI work.

Sustainability is tested by separating recurring operating performance from one-time and owner-specific effects, then asking whether the drivers of that performance survive the sale.

The questions that decide it:

• Revenue durability. Is revenue contracted or recurring, or does it depend on relationships held by the departing owner.
• Concentration. What happens to earnings if the largest customer leaves within a year of close.
• Margin trend. Is gross margin stable, and if it is declining, is the cause pricing, cost, or mix.
• Cost normalization. Does the business carry costs it will need after close but is not currently paying, such as market-rate management compensation.
• Deferred spending. Has maintenance, capital expenditure, or headcount been suppressed to improve the trailing twelve months.
• Working capital. Does growth require cash the buyer will have to fund.

Adjusted EBITDA answers what the business earned. Sustainability answers what it will keep earning, and that is what the buyer is actually purchasing.

Review the general ledger, trial balances, three years of monthly financial statements, tax returns, bank statements, revenue by customer, payroll registers, and receivable and payable aging.

Search funds face a structural problem that shapes the answer: they evaluate many targets to close one, and they cannot fund professional diligence on every candidate. That makes early access to transaction-level data disproportionately valuable, because the screen has to be cheap enough to run repeatedly.

The workable approach is one consistent screening standard applied to every target using ledger data, with paid diligence reserved for the few that clear it. Owner-operated businesses in this size range also carry heavy commingling of personal and business expense, so add-back analysis is usually where the real valuation question sits, not in revenue.

Start by footing the ledger to the trial balance and the financial statements, then move to account-level trending, vendor grouping, and a review of manual and period-end entries.

1. 1Reconcile. Confirm the ledger ties to the trial balance and up to the statements, and investigate every variance before going further.
2. 2Standardize. Map the chart of accounts into consistent categories across all periods, including any mid-year system change.
3. 3Trend. Review revenue, gross margin, and major expense accounts monthly rather than annually.
4. 4Scan. Flag round numbers, period-end concentrations, reversing entries, unfamiliar vendors, and related-party names.
5. 5Test add-backs. Trace each proposed adjustment to specific entries and confirm it appears only in the periods claimed.
6. 6Cross-reference. Verify material items against bank records, invoices, and contracts.

Manual review of a large ledger forces sampling, which is why steps 3 and 4 are usually where things get missed. Software makes complete coverage feasible inside a deal timeline.