Audit Your Financial Model for Formula Errors and Structural Risks

The Real Cost of Financial Model Errors

JPMorgan Chase lost an estimated $6 billion in 2012 — the "London Whale" trading loss — partly attributed to errors in a VaR model built in Excel, including a formula that divided by the sum of two numbers rather than their average. Fidelity's Magellan Fund miscalculated a capital gains distribution by $2.6 billion due to a sign error in a spreadsheet. Citigroup accidentally sent $900 million to Revlon's creditors in 2020, partly enabled by software configuration that mirrored a spreadsheet error.

These aren't outliers. Research finds that 94% of spreadsheets contain at least one error. For models that drive investment decisions, capital allocation, or regulatory submissions, an undetected error doesn't just produce a wrong number — it produces a wrong decision.

Financial Model-Specific Checks

General-purpose formula checkers catch obvious errors. Financial models have additional failure modes that require specific attention:

• Circular references in DCF models: Interest expense calculations that reference debt balances which include interest often create intentional circularity — but unintentional ones are dangerous and structurally identical. The tool identifies all circular reference chains so you can determine which are deliberate.
• Volatile functions in projection models: INDIRECT() and OFFSET() recalculate every time anything in the workbook changes. In a monthly forecast model with 10 years of projections, this can cause different results each time the file is opened depending on calculation order. NOW() and TODAY() update the timestamp silently on every open.
• Broken external links: Models that pull actuals from accounting system exports or source files break when those files are moved or renamed. The model shows last-known cached values without any visible warning.
• Hidden assumption sheets: Financial models frequently contain hidden sheets with hard-coded inputs — macro assumptions, tax rates, depreciation schedules. These may contain stale data that is still feeding visible calculations.
• Structural inconsistencies: Missing data in forecast periods, mixed data types in assumption ranges, and inconsistent formula patterns across columns — for example, a 12-month projection where one month's formula is hard-coded instead of referencing the assumption row.

Who This Is For

This tool is for anyone whose job involves models that will be acted on, shared, or scrutinized:

• Investment bankers building LBO, M&A, and valuation models before they go to principals or clients
• FP&A analysts managing rolling forecasts and board reporting packages
• PE/VC associates validating portfolio company models before investment committee
• Auditors reviewing financial models as part of SOX compliance or model risk management programs
• CFOs who need to present models to boards and cannot afford to be caught with a formula error in the room

The Audit Workflow

1. Upload your model — .xlsx or .xlsm, up to 50MB, no account required
2. Review the risk score — the 0–100 score tells you at a glance whether this model needs attention before it goes further
3. Drill into issues by category — formulas, references, structure, and data quality are each scored separately so you know where to focus
4. Fix the issues identified — the report gives exact cell locations and formula text so you can navigate directly to each problem
5. Re-upload to verify — confirm the fixes resolved the issues and generate a clean audit report for documentation or review trail

Your Data Is Private

Financial models contain sensitive projections, deal terms, and portfolio data. Your file is analyzed and immediately deleted after the scan. We do not store spreadsheet contents, formula text, or any financial data from your model. The analysis result and risk score are returned to you and are not retained on our servers.