Financial modeling demands precision. A single wrong cell reference or circular reference can cascade through an entire model and produce outputs that look correct but are fundamentally wrong. Financial modelers spend hours checking formulas, tracing precedents, and validating outputs against expectations. The problem is that human review has natural limits — after the third hour of checking cell by cell, concentration drops and errors slip through that a fresh pair of eyes would catch immediately.
ChatGPT and Claude complement each other for financial modeling. ChatGPT excels at generating formulas and VBA automation — it produces working Excel formulas with clear explanations that you can copy directly into your workbook. Claude has a much larger context window at 200K tokens that lets it review entire multi-tab models at once, catching structural inconsistencies that tab-by-tab review misses. Using both tools in parallel catches formula-level errors and structural issues in a single session rather than requiring multiple review passes.
The two workflows below show exactly when to use each tool. Use ChatGPT during the build phase when you need formulas created and explained. Switch to Claude during the review phase when you need the complete model evaluated for structural integrity. The combined effect is a cleaner model delivered in less time than using either tool alone.
Building vs Reviewing
Most financial modelers spend roughly 60% of their time building formulas and 40% reviewing and debugging. ChatGPT shifts the build phase from hours to minutes by generating complex formulas with working logic. Claude shifts the review phase from manual cell-by-cell checking to a structural analysis that catches cross-tab references, circular paths, and integrity issues that a human reviewer would need hours to find. Together they compress the entire modeling cycle significantly.
Prompt: Build a DCF Model (ChatGPT)
Generate Excel formulas for a 5-year DCF valuation. Use opening revenue of EUR 100M with 5% annual volume growth and 2% price increase. Apply COGS at 60% of revenue, SG&A at 25%, R&D at 8%, CAPEX at 8% of revenue, and depreciation at 5% of beginning PP&E. Working capital assumptions: DSO 45 days, DPO 30 days, DIO 60 days. Tax rate 30%, WACC 9%, terminal growth 2%. Include a sensitivity table showing valuation across WACC from 7% to 11% and terminal growth from 1% to 3%. Explain each formula segment so I can adapt the logic to other models.Reviewing the Complete Model
Once your model is built, the risk shifts from formula errors to structural issues. A model might have correct individual formulas but still be wrong because of a cross-tab circular reference or an assumption that should link to the balance sheet but was hardcoded in a cell. Claude catches these issues by reviewing the complete model structure rather than individual formulas.
Prompt: Review a Model (Claude)
Review this financial model by examining the full formula documentation. Identify all circular references including indirect paths where tab A references tab B references tab C back to tab A. Check balance sheet integrity across all projection years and verify it balances correctly each period. Confirm that cash flow logic handles negative balances realistically with financing assumptions that activate automatically. Check that tax calculations properly handle loss carryforwards if a projection year shows a loss. Rank the top three structural issues by their potential materiality on the valuation output and suggest specific fixes for each.For sensitive company data use enterprise versions of either tool with data privacy guarantees enabled. Your model data stays in your controlled environment and is not used for training. The best workflow is build with ChatGPT and review with Claude -- each tool catches different error types and together they produce a more robust model than working with either tool alone.