When structuring prompts for a large language model (LLM) to assist in financial due diligence, the goal is to make the questions as specific and targeted as possible. This allows the LLM to provide more precise, relevant, and actionable insights based on the financial data, historical records, and other documentation involved in the due diligence process.
Here’s how to break down an effective LLM prompt for financial due diligence:
1. Define the Objective
First, identify what you’re seeking from the model: Are you looking for risk analysis, financial health insights, or verifying compliance? Establishing a clear goal will guide the model’s response.
Example:
“Provide a risk assessment of the company’s financial health based on the last three years of balance sheet data and income statements.”
2. Specify the Data or Documentation
Provide clear and concise details on the documents or datasets that the model will be analyzing. It could be financial statements, investment summaries, capital structure breakdowns, etc. The model should understand what data it is looking at.
Example:
“Analyze the provided balance sheet and income statements from 2021-2023 to determine trends in revenue, expenses, and profit margins.”
3. Ask for Key Financial Metrics
LLMs can extract key financial metrics such as liquidity ratios, profitability ratios, solvency, etc. It’s best to specify which metrics matter for your specific due diligence.
Example:
“Calculate the liquidity ratios (current and quick ratios) and profitability ratios (return on assets, return on equity) based on the financial data provided.”
4. Request Detailed Insights
Ask the model to analyze trends, identify anomalies, or flag potential risks. If there’s anything unusual or worth investigating deeper, prompt the model to explore that.
Example:
“Identify any significant fluctuations in the revenue growth rate and gross profit margin between the years 2021 and 2023, and provide potential reasons for these changes.”
5. Direct the Model to Assess External Factors
Financial due diligence doesn’t occur in a vacuum. LLMs can be asked to consider broader market conditions, regulatory changes, or industry-specific factors.
Example:
“Assess how recent market trends and industry changes, such as interest rate hikes or supply chain disruptions, might impact the company’s financial position.”
6. Compliance and Legal Aspects
If you’re examining regulatory compliance or checking for legal risks, make sure to include these aspects in the prompts. Financial due diligence often involves verifying adherence to tax laws, accounting standards, or financial regulations.
Example:
“Review the company’s tax filings and compliance with local regulations in the past three years, flagging any potential risks for non-compliance or unusual practices.”
7. Scenario and Sensitivity Analysis
If applicable, ask the model to run financial scenario or sensitivity analyses, which are often a key component of due diligence.
Example:
“Perform a sensitivity analysis on the company’s earnings before interest, taxes, depreciation, and amortization (EBITDA) for 2023 under different market conditions, such as increased raw material costs or decreased demand.”
8. Summarize Findings and Recommendations
Finally, prompt the model to summarize its analysis in a way that’s actionable for the due diligence team, offering insights, potential concerns, and recommendations.
Example:
“Summarize the financial health of the company based on the analysis and provide recommendations on areas for further investigation or potential red flags.”
Sample Full Prompt for Financial Due Diligence
“Analyze the balance sheets and income statements of Company X from 2020 to 2023 to assess the financial health and risk factors. Calculate the following key financial ratios:
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Liquidity ratios (current ratio, quick ratio)
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Profitability ratios (gross margin, operating margin, return on equity)
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Leverage ratios (debt-to-equity ratio)
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Cash flow metrics (free cash flow, operating cash flow).
Flag any significant trends, anomalies, or risks such as fluctuating revenue growth, unbalanced debt levels, or potential tax non-compliance. Additionally, provide insights on how current macroeconomic trends (like interest rates or commodity price fluctuations) could impact the financial stability of the company.”
This approach to structuring prompts ensures that the language model is tasked with focused, actionable analysis, making it a valuable tool in the due diligence process. The more specific you are in your prompts, the more reliable and targeted the model’s responses will be.