General Ledger Review for M&A Due Diligence
Published February 2026
The general ledger is where the truth lives. Every adjustment, every add-back, and every red flag starts with a transaction in the GL.
10,000+
Typical GL transactions per year (SMB)
5–15%
Transactions that typically warrant review
Hours vs weeks
AI review vs manual review time
Why Review the General Ledger?
Financial statements summarize; the general ledger tells the full story. During QoE analysis, the GL is the source of truth for identifying:
Hidden add-backs
Personal expenses, one-time costs, and discretionary spending buried in operating accounts
Misclassifications
Revenue coded as other income, COGS mixed with operating expenses, capital expenditures expensed
Manipulation signals
Round-dollar entries, end-of-period journal entries, unusual vendor payments
Completeness gaps
Missing accruals, unrecorded liabilities, off-books transactions
Anomaly Detection Techniques
Round-dollar analysis
Transactions in round amounts ($5,000, $10,000) may indicate estimates rather than actual transactions — flag for review
Benford's Law
The first-digit distribution of transaction amounts should follow a predictable pattern — deviations suggest data manipulation
Duplicate detection
Same amount, same vendor, same date — potential duplicate payments that inflate expenses
Threshold analysis
Transactions just below approval thresholds suggest deliberate structuring to avoid oversight
Period-end clustering
Unusual concentration of entries in the last days of a period may indicate earnings management
Variance from average
Individual transactions significantly larger than the account average warrant investigation
Unusual Journal Entries
Journal entries — especially manual ones — are a primary tool for earnings manipulation. Focus on:
Manual entries
Entries not generated by the accounting system's normal processes
Top-side entries
Adjustments made after the trial balance is pulled — often for 'corrections'
Revenue-affecting entries
JEs that credit revenue accounts outside the normal billing process
Round amounts
Large round-dollar JEs suggest estimates or manual overrides
Off-hours entries
Entries posted on weekends, holidays, or outside business hours
Missing descriptions
JEs without adequate descriptions may be hiding their purpose
Personal Expense Detection
In owner-operated businesses, personal expenses running through the company are one of the most common EBITDA add-backs. Common keywords and patterns to search for:
Travel & entertainment
Vacation travel, family dinners, sporting events, personal memberships
Vehicle expenses
Personal vehicle payments, fuel for non-business use, luxury vehicles
Insurance
Personal life insurance, health insurance for non-employees, umbrella policies
Professional services
Personal legal fees, financial planning, estate planning
Retail & online purchases
Amazon, retail stores, personal subscriptions coded as business expenses
ATM & cash withdrawals
Cash withdrawals with no business purpose documentation
Related Party Transactions
Related party transactions are not inherently problematic, but they require scrutiny because they may not be at arm's length:
Below-market rent
Company leasing property from the owner at below-market rates — creates a pro forma adjustment
Management fees
Fees paid to related entities for services that may not be necessary post-acquisition
Vendor relationships
Suppliers owned by the seller's family — verify pricing is competitive
Intercompany charges
Shared services, cost allocations, and transfers between related entities
Account Reclassification
COGS vs OpEx
Direct costs misclassified as operating expenses (or vice versa) distort gross margin
CapEx vs expense
Capital expenditures expensed inflate operating costs; repairs capitalized understate them
Revenue classification
Operating revenue vs other income — impacts core earnings analysis
Below-the-line items
Ensure non-operating items are properly separated from operating results
GL Review Process
Export the complete GL
Get the full general ledger with all fields: date, account, amount, description, vendor, entry type
Profile the data
Count transactions, identify accounts with highest volume, flag accounts with unusual activity
Run anomaly scans
Apply round-dollar, duplicate, threshold, and period-end clustering tests
Keyword search
Search transaction descriptions for personal expense indicators
Review large transactions
Examine all transactions above a materiality threshold
Analyze journal entries
Focus on manual, top-side, and round-dollar journal entries
Quantify adjustments
Calculate the EBITDA impact of identified items
AI-Powered GL Review
Traditional GL review means an analyst manually scanning thousands of transactions. AI changes the equation:
Pattern recognition
AI identifies anomalous patterns across the entire ledger simultaneously
Keyword intelligence
Natural language processing catches variations human searchers miss
Continuous learning
Each review improves the detection of industry-specific patterns
Comprehensive coverage
Every transaction reviewed — not just a sample
Learn more about how Shepi's AI assistant accelerates GL-level analysis.