Financial Due Diligence Checklist: A Senior Advisor’s Framework for 2026

The M&A landscape in 2026 is defined by a shift from deal volume to deal quality. While the number of transactions has stabilized, average deal sizes have increased by 23% compared to 2025. This concentration of capital into larger, more strategic assets raises the stakes for financial due diligence. Investors are no longer just looking for historical accuracy: they are seeking proof of sustainable growth and operational resilience.

Traditional FDD often suffers from a siloed approach, where financial analysts work independently of legal or commercial teams. Modern dealmaking requires an integrated view. For instance, a financial finding regarding revenue leakage must be immediately cross-referenced with customer contracts in the legal workstream. This cross-workstream synthesis is where material risks are often discovered.

Plausity facilitates this by running 9 DD workstreams simultaneously: Commercial, Financial, Legal, Tax, Organisation & Compliance, Tech, Cybersecurity, ESG, and Website Compliance. By breaking down these silos, deal teams can identify how a tax liability in one jurisdiction might impact the overall quality of earnings or how a cybersecurity breach could lead to significant unrecorded liabilities.

The Quality of Earnings (QoE) analysis is the core of financial due diligence. Its primary objective is to determine the sustainable, recurring earnings of the target company by stripping away one-time events and accounting anomalies. This results in "Normalized EBITDA," which serves as the basis for valuation multiples.

Advisors must scrutinize the bridge from reported EBITDA to adjusted EBITDA. Common adjustments include owner compensation normalization, non-recurring legal fees, and discretionary spending. In 2026, buyers are increasingly skeptical of "pro forma" adjustments that assume future cost savings without historical precedent.

• Owner Compensation: Adjust salaries and bonuses to market rates for equivalent executive roles.
• Non-Recurring Expenses: Remove one-time costs such as relocation expenses, litigation settlements, or M&A advisory fees.
• Discretionary Spending: Identify and remove personal expenses, club memberships, or non-business travel.
• Accounting Policy Alignment: Standardize revenue recognition methods (e.g., moving from cash to accrual) and depreciation schedules.
• Related Party Transactions: Adjust for above-market or below-market rents and service fees paid to affiliated entities.
• Stand-alone Costs: For carve-outs, estimate the additional costs required to replace corporate services provided by the parent company.

Plausity's AI Analysis Engine automates the detection of these anomalies by triangulating data across management accounts, audited financials, and general ledger extracts. Every finding is linked directly to the source document, page, and paragraph, providing 100% traceability for the deal team.

While EBITDA determines the multiple, net debt and working capital determine the final cash-to-seller. A common pitfall in FDD is failing to identify "debt-like" items that should be deducted from the purchase price. These often hide in the footnotes of financial statements or within off-balance-sheet commitments.

Working capital analysis focuses on the liquidity required to run the business day-to-day. Deal teams must establish a "working capital peg" based on historical averages to ensure the target is delivered with sufficient operational cash. Seasonality plays a critical role here: a business with high Q4 sales will have significantly different working capital needs than one with a flat revenue profile.

In 2026, working capital purchase price adjustments are included in over 90% of private-target M&A transactions. Having a defensible, trailing 12-month analysis is essential for both buyers and sellers to maintain deal momentum.

Financial due diligence must extend into the quality of the revenue itself. A company with high revenue growth but extreme customer concentration carries a significantly higher risk profile. If 30% or more of revenue comes from the top three customers, the loss of a single contract can derail the entire investment thesis.

Advisors should analyze revenue by cohort, geography, and product line. Understanding churn rates and renewal terms is critical for validating the "stickiness" of the business. In SaaS and recurring revenue models, this involves a deep dive into Net Revenue Retention (NRR) and Customer Acquisition Cost (CAC) payback periods.

1. Customer Concentration: Map revenue by customer over the last 36 months to identify dependencies.
2. Contract Review: Cross-reference financial revenue data with legal contract terms, specifically change-of-control and termination clauses.
3. Pricing Trends: Analyze historical price increases to determine if growth is driven by volume or price hikes.
4. Pipeline Accuracy: Compare historical sales pipelines with actual converted revenue to assess the reliability of management's forecasts.

Plausity's Findings & Risk Intelligence module automatically flags material contract expiry risks. For example, if three material contracts representing 15% of revenue expire within 12 months without evidence of renewal, the platform surfaces this as a critical red flag, linked directly to the relevant contract pages.

The traditional FDD process is often slow and manual, involving hundreds of spreadsheets and thousands of documents. A typical mid-market data room contains between 500 and 2,000 documents. Manually reviewing these for financial inconsistencies is a significant drain on senior advisor time.

Plausity transforms this workflow by providing an AI-native workspace that automates document ingestion and classification. Unlike simple chatbots, Plausity's AI Analysis Engine performs cross-document reasoning. It can detect if management accounts provided in the financial workstream contradict the audited statements or the disclosures made in the legal workstream.

This automation does not replace human judgment; it augments it. By handling the repetitive analytical work, Plausity allows senior advisors to focus on high-level strategy and risk mitigation. A Big Four Advisory partner reported that using Plausity cut their commercial DD timeline from three weeks to five days on a mid-market transaction. This speed is a competitive advantage in a market where top performers close deals 2-3 months faster than the average.

Financial due diligence cannot exist in a vacuum. To truly understand the risk profile of a target, deal teams must map financial findings against other workstreams. For example, a high EBITDA margin might be unsustainable if the Tech DD reveals significant technical debt or if the ESG DD identifies upcoming regulatory compliance costs that will increase operating expenses.

Plausity's platform is built for this multi-workstream reality. It provides a unified deal workspace where findings from 9 workstreams are synthesized in real time. This allows for the generation of investor-ready reports, red flag summaries, and executive briefings that are dynamically structured based on actual findings across the entire deal.

By adopting an AI-native approach, PE funds and advisory firms can scale their deal throughput without proportionally increasing headcount, while maintaining the highest standards of rigor and auditability.