GitHub Copilot Prompt for Analyzing a Financial Balance Sheet
GitHub Copilot, the AI-powered coding assistant, is not limited to code generation. With its data analysis and processing capabilities, it becomes a formidable ally for finance professionals looking to automate the analysis of financial balance sheets. By using Copilot in a development environment like VS Code, you can ask it to generate analysis scripts, interpret financial ratios, detect accounting anomalies, and produce summary reports from raw data. Whether you are a CFO, management controller, or financial analyst, a well-structured prompt allows Copilot to transform tables of numbers into actionable insights. The key is to formulate your request with enough context — balance sheet structure, accounting standards, key indicators — so that the AI produces a rigorous and usable analysis. This guide provides an optimized prompt as well as variants tailored to your level of expertise to get the most out of GitHub Copilot in your financial analyses.
Paste in your AI
Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
Analyze the following financial balance sheet in accordance with French accounting standards (PCG). For each item, calculate N/N-1 variations in absolute value and percentage. Then produce: 1) An analysis of the financial structure (working capital, working capital requirement, net cash) with interpretation. 2) Liquidity ratios (current, quick, cash), solvency ratios (financial autonomy, debt repayment capacity) and profitability ratios (ROE, ROA). 3) A synthetic diagnosis of identified strengths and weaknesses with prioritized recommendations. 4) A summary table formatted in Markdown. Here is the balance sheet data: [PASTE DATA HERE]. Present the analysis in a structured manner with clear headings, professional comments, and alerts on critical thresholds exceeded.
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Why this prompt works
This prompt works because it imposes a complete financial analysis methodology in four distinct steps, forcing Copilot to structure its response exhaustively rather than superficially. The explicit reference to PCG standards and specific ratios removes ambiguity and directs the AI toward recognized financial calculations. Finally, the request for a diagnosis with prioritized recommendations pushes the model beyond simple number reporting toward true analytical interpretation.
Use Cases
Variants
Expected Output
You will obtain a comprehensive and structured financial analysis including item-by-item variations, key ratios calculated with their values and interpretation (favorable, neutral, or unfavorable), as well as an overall diagnosis of the company's financial health. The result will include a summary Markdown table ready to integrate into a report, with visual alerts on indicators that exceed commonly accepted critical thresholds.
Frequently Asked Questions
Can GitHub Copilot analyze a financial statement directly from an Excel file?
GitHub Copilot does not read Excel files directly. You first need to convert your data into structured text (CSV, Markdown table, or JSON) and then paste it into your editor. Copilot can then generate a Python script using pandas or openpyxl to automate the import and recurring analysis of your Excel files.
Are the financial calculations produced by GitHub Copilot reliable?
Copilot correctly applies standard financial formulas when the prompt clearly specifies them. However, it's essential to verify the results, especially ratio calculations and variances. For critical decisions, use Copilot as an acceleration and structuring tool, but systematically validate key figures with a spreadsheet or accounting software.
How do you adapt the prompt for an IFRS balance sheet rather than French GAAP?
Replace the 'French GAAP standards' reference with 'IFRS standards' in the prompt and specify the desired specifics: goodwill treatment, fair value of assets, presentation of equity under IAS 1. Also add relevant IFRS indicators like adjusted EBITDA or the net debt/EBITDA ratio that international analysts commonly use.
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