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M&A, audit & deal work Capability project

M&A due diligence and decision framework

Built a reusable M&A framework that turns valuation, quality-of-earnings and financial-risk analysis into consistent, board-ready decision support across live transactions. One engagement has reached an acquisition recommendation and integration plan; no completed transaction outcome is disclosed.

Engagement record

Counterparties withheld by design

  • Valuation

    Board-ready valuation packs · live transactions

    2026

  • Quality of earnings

    Normalised-earnings analysis · live transactions

    2026

  • Financial-risk matrix

    Deal risk assessment · live transactions

    2026

  • VDR Q&A

    Data-room-driven follow-up analysis · live transactions

    2026

Evidence inputs

  • Live transactions within the group; IFRS reporting basis.
  • IFRS IAS 21 · Quality-of-earnings analysis · AI-assisted workflows

Transformation

  • Codified IAS 21 currency translation, quality-of-earnings analysis and financial-risk matrices.
  • Structured outputs for consistent review and board-ready decisions across deals.
  • Used model assistance for first-pass reading and extraction while keeping every figure traceable and re-checkable.

Controls & assurance

  • Standardised the method while preserving transaction-specific judgement.
  • Kept numbers and conclusions under deterministic checks and reviewer authority.

Output

  • Deployed a consistent analytical structure across live transaction work.

Business value

  • Improves the speed, comparability and auditability of transaction decisions.
  1. Problem

    Each transaction needed faster analysis without sacrificing consistency, traceability or reviewer judgement.

  2. Approach

    Codified IAS 21 currency translation, quality-of-earnings analysis and financial-risk matrices.

  3. Outcome

    Deployed a consistent analytical structure across live transaction work.

Business value

Improves the speed, comparability and auditability of transaction decisions.

Transformation route

  1. 01

    Codified IAS 21 currency translation, quality-of-earnings analysis and financial-risk matrices.

  2. 02

    Structured outputs for consistent review and board-ready decisions across deals.

  3. 03

    Used model assistance for first-pass reading and extraction while keeping every figure traceable and re-checkable.

Decision log

  • Standardised the method while preserving transaction-specific judgement.
  • Kept numbers and conclusions under deterministic checks and reviewer authority.

This case study proves

  • AI-assisted financial analysis AI & Automation Strong
  • IFRS / UK GAAP Finance Strong
  • M&A due diligence Finance Strong

Full skill evidence →

What I learned

  • Standardising the method improves speed without predetermining the answer.

Future improvements

  • Build a redacted precedent library of worked examples and standard adjustments.

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