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  • 1Overview
  • 2FDD engagements
  • 3Quality of earnings
  • 4Working capital & net debt
  • 5Supporting schedules
  • 6Exceptions & conflicts
  • 7Draft reports
  • 8Where Vaultrix fits

Transaction advisory

AI-assisted financial due diligence for transaction advisory teams

QoE support, working capital and net debt analysis, and source verification — with professional judgment staying where it belongs.

01How do transaction advisory teams use Vaultrix?

Transaction advisory and FDD teams use Vaultrix to accelerate the first pass through a target's financial documents: extracting figures, cross-checking them across sources, and citing every number back to where it came from — before a professional reviews and forms a conclusion.

Vaultrix does not perform professional accounting judgments autonomously. It's an AI-assisted workflow layer, not a replacement for the reviewer forming the actual opinion.

02How does Vaultrix fit into an FDD engagement?

A financial due diligence engagement typically starts with a request list issued to the target and ends with a report to the client. Vaultrix sits in the middle: it maps the request list to what the target has actually provided, answers financial questions with citations, and surfaces where documents disagree — the groundwork a reviewer needs before drafting conclusions. See financial due diligence for the full process.

03Can Vaultrix support quality of earnings analysis?

Quality of earnings (QoE) analysis normalises reported earnings by identifying one-time items, accounting adjustments, and non-recurring revenue or costs — work that depends on tracing figures across the general ledger, management accounts, and audited statements. Vaultrix can answer specific questions across those documents with citations (for example, whether a claimed add-back is actually supported by the underlying schedule), which speeds up the fact-finding a QoE review depends on. The normalisation judgment itself remains the reviewer's.

04Does Vaultrix help with working capital and net debt analysis?

Working capital and net debt figures typically depend on definitions set out in a purchase agreement or engagement letter, applied against balance-sheet and debt-schedule detail spread across the room. Vaultrix can locate and cite the relevant schedules and cross-check them against how a figure is presented elsewhere in the room, rather than a reviewer manually tracing each line.

05How does Vaultrix handle supporting schedules?

Vaultrix parses Excel files sheet by sheet, and every citation resolves to the exact sheet name and cell range — not just the filename — so a reviewer can open the specific schedule an answer came from directly, rather than searching for it.

06How are exceptions and conflicting evidence handled?

When two source documents disagree on the same figure — a management account and an audited statement showing different numbers for the same period, for instance — Vaultrix surfaces both instead of silently reconciling them for you. That disagreement is exactly the kind of exception an FDD report is meant to call out.

07Can Vaultrix help draft an FDD report?

Vaultrix can assemble cited findings — what was requested, what evidence supports it, what's missing or conflicting — into a starting structure for a report. It drafts from evidence already gathered and verified; it does not independently form or state a professional conclusion, and every draft is subject to the reviewing professional's own judgment and sign-off before it goes to a client.

08What does Vaultrix not replace in a transaction advisory engagement?

Vaultrix does not replace the reviewing professional's accounting judgment, the engagement's quality-control review, or the firm's own methodology. It accelerates the evidence-gathering and cross-checking work that judgment depends on — the analysis and conclusions remain the team's.

Related: financial due diligence · due diligence request lists · AI due diligence software · private equity · investment banking
Further reading: financial due diligence checklist · how AI detects conflicting information
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