Solution

Financial Statement Normalization & Quality of Earnings Support

For transaction advisory, quality-of-earnings, and deal teams at accounting firms and private equity funds: target financials normalized and a cited adjustment schedule drafted before the first workpaper review.

Audited financialsTrial balancesManagement accountsTax returnsGL exports
5× faster financial spreading100% of numbers cited to sourceEvery adjustment human-approved

The problem

Why this exists

4 formats

Nothing in the data room matches

Audited statements disagree with management accounts, and the trial balance uses a chart of accounts nobody on the deal team has seen. Normalization eats the first weeks of every engagement.

Senior hours

Your best analyst is rekeying

The person most qualified to judge earnings quality spends the engagement mapping line items into the databook by hand.

One challenge

Untraceable adjustments collapse

An add-back that cannot be traced to a source page dies in partner review — or survives it and gets picked apart by the other side's advisors.

The product, not a promise

A databook you can defend

Financial Statement Normalization & Quality of Earnings Support — workspace
Statements mapped to standard chart of accountsFY22–FY24 · reconciledcited
Owner compensation add-backApproved · source citedcited
Related-party rent adjustmentAccepted · source citedcited
Q3 working-capital swing outside trendCandidate adjustment for reviewverify
Adjusted-EBITDA bridgeEvery figure linked to its pagecited
HUMAN-APPROVED BEFORE IT POSTS

How it works

File in. Answer out.

  1. 1

    Intake

    Pull audited statements, management accounts and trial balances from the data room, in any format.

  2. 2

    Normalize

    Map every line item to a standard chart of accounts, reconciling periods, entities and currencies.

  3. 3

    Adjust

    Flag one-off items, owner add-backs and working-capital swings as candidate QoE adjustments.

  4. 4

    Review

    An analyst approves or rejects each adjustment against the cited source page.

  5. 5

    Deliver

    Export a normalized databook and adjustment schedule the deal team can defend.

Who it's for

Built for the people who own the outcome

Diligence analyst

You review candidate adjustments instead of building the databook by hand.

  • Normalized statements arrive reconciled across periods and entities
  • Each candidate adjustment comes with its source page attached
  • Accept, reject, or edit — your call is the one that counts

Engagement partner

Findings reach partner review already traceable.

  • Every figure in the databook links to the document it came from
  • The adjustment schedule carries approvals, so review is judgment work
  • Compressed normalization time means earlier, deeper earnings analysis

Firm risk & IT

Deal data stays governed from data room to deliverable.

  • Deploys in private cloud or on-premises, ISO 27001 and SOC 2 certified
  • Full audit trail: source, adjustment, approver, timestamp
  • Engagement data stays segregated, per your confidentiality obligations
Transaction advisoryPrivate equityCorporate developmentInvestment bankingRestructuringLender diligence
faster financial spreading
100%numbers cited to source
Every adjustmenthuman-approved
Any formatPDF, scan or Excel

From four formats to one databook

Every diligence engagement starts the same way: three years of target financials in four formats, none of which match. Audited statements disagree with management accounts; the trial balance uses a chart of accounts nobody on the deal team has seen. Before anyone can discuss earnings quality, someone has to normalize all of it by hand — usually your most senior analyst.

Botminds does the normalization. It reads audited financials, management accounts, trial balances, GL exports, and tax returns in whatever shape they arrive — scanned PDF, digital PDF, Excel — and maps every line item to a standard chart of accounts, reconciled across periods, entities, and currencies. Five times faster than manual spreading, with every number cited to the page it came from.

Adjustments that survive partner review

Normalization is the floor. On top of the standardized statements, the platform surfaces the items a QoE reviewer hunts for: one-off revenue and expense items, owner compensation add-backs, related-party transactions, working-capital swings, and period-over-period movements that break the trend. Each is presented as a candidate adjustment with the exact source page attached; an analyst accepts, rejects, or edits it. Nothing enters the adjustment schedule without a named sign-off.

The result is a databook the deal team can stand behind: normalized statements, an adjusted-EBITDA bridge, and a working-capital analysis where every figure links back to its document. When a number is challenged six weeks later — by the partner or by the other side’s advisors — the answer is one click: which document, what was adjusted, who approved it, and when.

Objections, answered

What teams ask us first

How do I trust a machine-drafted adjustment?

Check it. Every candidate adjustment arrives with the exact source page attached, and an analyst accepts, rejects, or edits it. Nothing enters the adjustment schedule without a named sign-off, and the trail records who approved what and when.

We have our own databook format and adjustment conventions.

The mapping target is yours: your chart of accounts, your databook structure, your adjustment categories. The platform normalizes into that shape, so the deliverable looks like your firm's work — because it is.

Target data is under NDA. Where does it run?

In your private cloud or on-premises, certified to ISO 27001 and SOC 2, with engagement data segregated. The audit trail — source document, extraction, adjustment, approver — stays with the databook for as long as you retain it.

Can we start mid-engagement?

Yes. Intake is the data room as it stands — audited statements, management accounts, trial balances, GL exports, in any format. Normalization runs from there, and your team reviews the output the same way it would review a first-year associate's, only sooner.

Bring your messiest data room.

Watch three years of mismatched target financials normalize into a cited databook with candidate adjustments attached.

Request a demo