AI for Finance & Accounting
Module 2: Financial Analysis with AI
Module Overview
Financial analysis is the bread and butter of finance work. In this module, you'll learn how to leverage AI to enhance your analytical capabilities—making you faster, more thorough, and more insightful.
Learning Objectives:
By the end of this module, you will be able to:
- Use AI effectively for ratio analysis and interpretation
- Conduct variance analysis with AI assistance
- Generate insights from financial data
- Build effective analytical prompts
- Avoid common pitfalls when using AI for analysis
Estimated Time: 1.5-2 hours
2.1 AI-Assisted Ratio Analysis
The Traditional Approach
Ratio analysis typically involves:
- Calculate ratios from financial statements
- Compare to benchmarks (prior period, budget, industry)
- Identify significant variations
- Interpret what the ratios mean
- Draw conclusions and recommendations
Where AI Helps:
- Steps 3-5: Interpretation, insights, and conclusions
- AI can quickly synthesize multiple data points into coherent analysis
Where You Lead:
- Steps 1-2: Calculations and data accuracy
- Never trust AI with your math
Template Prompt for Ratio Analysis
I need help analyzing financial ratios for [Company Name],
a [industry] company.
Here are the key ratios:
LIQUIDITY:
- Current Ratio: [X.XX] (Prior Year: [X.XX])
- Quick Ratio: [X.XX] (Prior Year: [X.XX])
PROFITABILITY:
- Gross Margin: [X.X]% (Prior Year: [X.X]%)
- Operating Margin: [X.X]% (Prior Year: [X.X]%)
- Net Profit Margin: [X.X]% (Prior Year: [X.X]%)
- Return on Equity: [X.X]% (Prior Year: [X.X]%)
- Return on Assets: [X.X]% (Prior Year: [X.X]%)
EFFICIENCY:
- Inventory Turnover: [X.X] times (Prior Year: [X.X])
- Receivables Turnover: [X.X] times (Prior Year: [X.X])
- Asset Turnover: [X.X] times (Prior Year: [X.X])
LEVERAGE:
- Debt-to-Equity: [X.XX] (Prior Year: [X.XX])
- Interest Coverage: [X.X] times (Prior Year: [X.X])
Industry averages: [Include if available]
Please provide:
1. Key observations and trends
2. Areas of strength
3. Areas of concern
4. Potential causes for significant changes
5. Questions I should investigate further
Real Example: Manufacturing Company Analysis
Your Input:
Analyze these ratios for ABC Manufacturing, a mid-sized
industrial equipment manufacturer:
Current Ratio: 1.8 (Prior: 2.1)
Quick Ratio: 0.9 (Prior: 1.2)
Inventory Turnover: 3.2x (Prior: 4.5x)
Gross Margin: 32% (Prior: 35%)
Operating Margin: 8% (Prior: 12%)
Receivables Turnover: 6x (Prior: 7x)
Debt-to-Equity: 0.8 (Prior: 0.5)
Industry averages: Current Ratio 1.5, Inventory Turnover 5x,
Gross Margin 30%
AI Response (Example):
Key Observations:
Inventory Concerns: The dramatic decline in inventory turnover (4.5x to 3.2x) combined with the drop in quick ratio suggests inventory buildup. This is moving against the industry trend (5x average).
Margin Compression: Both gross and operating margins declined significantly. The 3-point drop in gross margin could indicate rising input costs, pricing pressure, or product mix shift.
Increased Leverage: Debt-to-equity jumped from 0.5 to 0.8, suggesting the company took on significant new debt. Combined with declining profitability, this increases financial risk.
Questions to Investigate:
- What's driving the inventory buildup? Slower sales or production issues?
- Has the company changed suppliers or faced raw material cost increases?
- What was the purpose of the new debt? Capital expansion or covering operations?
- Are receivables aging appropriately despite lower turnover?
Best Practices for Ratio Analysis with AI
Do:
- Provide context (industry, company size, economic conditions)
- Include comparative data (prior periods, benchmarks)
- Ask for specific questions to investigate
- Use AI insights as starting points, not conclusions
Don't:
- Ask AI to calculate ratios (do this yourself)
- Accept interpretations without considering context
- Skip investigating the questions AI raises
- Present AI analysis as your own without verification
2.2 Variance Analysis with AI
Why AI Excels at Variance Analysis
Variance analysis requires connecting multiple data points and explaining relationships. AI is particularly good at:
- Generating possible explanations for variances
- Suggesting investigation paths
- Structuring findings clearly
- Identifying patterns across multiple variances
Template for Budget Variance Analysis
Help me analyze these budget variances for [Period] for
[Company/Department]:
REVENUE VARIANCES:
- Product Line A: Actual $[X], Budget $[Y], Variance [Z]%
- Product Line B: Actual $[X], Budget $[Y], Variance [Z]%
[Continue for each line item]
EXPENSE VARIANCES:
- Cost of Goods Sold: Actual $[X], Budget $[Y], Variance [Z]%
- Labor Costs: Actual $[X], Budget $[Y], Variance [Z]%
- Materials: Actual $[X], Budget $[Y], Variance [Z]%
[Continue for each line item]
Context:
- [Any relevant business context]
- [Economic conditions]
- [Known events during period]
Please provide:
1. Analysis of the most significant variances
2. Potential interconnections between variances
3. Likely root causes to investigate
4. Suggested management discussion points
Decomposing Variances
AI can help structure variance decomposition:
Prompt Example:
Our sales variance is unfavorable by $500,000.
Total units sold: 95,000 (Budget: 100,000)
Average selling price: $52 (Budget: $50)
Help me decompose this into price and volume variances
and explain what each component tells us.
AI Can Help With:
- Explaining the logic of variance decomposition
- Interpreting what each component means
- Suggesting business reasons for each variance type
- Recommending follow-up questions
You Must Do:
- Verify any calculations AI provides
- Apply company-specific knowledge
- Validate explanations against actual circumstances
2.3 Trend Analysis and Pattern Recognition
Using AI to Identify Trends
AI excels at synthesizing multiple data points into trend narratives.
Template Prompt:
Here is five years of key financial data for [Company]:
Year 1: Revenue $10M, Gross Margin 40%, SG&A $2.5M, Net Income $1.2M
Year 2: Revenue $11M, Gross Margin 39%, SG&A $2.8M, Net Income $1.1M
Year 3: Revenue $13M, Gross Margin 38%, SG&A $3.5M, Net Income $1.0M
Year 4: Revenue $14M, Gross Margin 36%, SG&A $4.0M, Net Income $0.8M
Year 5: Revenue $15M, Gross Margin 35%, SG&A $4.5M, Net Income $0.6M
Analyze the trends and identify:
1. The story these numbers tell
2. Key concerns
3. What might be driving the patterns
4. Questions management should answer
Red Flag Identification
Prompt for Identifying Concerns:
Review these financial metrics for potential red flags
or areas requiring investigation:
[Insert your financial data]
Specifically look for:
- Inconsistencies between metrics
- Trends that might indicate problems
- Ratios that seem unusual for the industry
- Signs of financial stress or manipulation risk
Comparative Analysis
Prompt for Peer Comparison:
Compare these metrics for three competitors in the
retail pharmacy industry:
Company A: Gross Margin 22%, Inventory Turns 8x, Current Ratio 1.1
Company B: Gross Margin 25%, Inventory Turns 12x, Current Ratio 0.9
Company C: Gross Margin 20%, Inventory Turns 10x, Current Ratio 1.5
Help me understand:
1. Which company appears operationally strongest?
2. What trade-offs might each be making?
3. What additional information would sharpen this analysis?
2.4 Building Your Analytical Prompt Library
Structure of Effective Analytical Prompts
The best prompts for financial analysis include:
-
Context Setting
- Company/industry description
- Time period
- Purpose of analysis
-
Data Presentation
- Clear, organized numbers
- Comparative figures (prior period, budget, industry)
- Relevant qualitative context
-
Specific Request
- What type of analysis you need
- What format you want
- What questions to address
-
Output Specification
- Structure expected (bullets, narrative, table)
- Level of detail needed
- Audience for the analysis
Sample Prompt Library for Finance
Quick Ratio Interpretation:
My client's quick ratio dropped from 1.5 to 0.8 year-over-year.
They are a [industry] company. What could cause this, and
what should I investigate?
Revenue Quality Assessment:
A company shows 25% revenue growth but accounts receivable
grew 60% and inventory grew 45%. What questions should I
be asking about revenue quality?
Margin Analysis:
Gross margin improved 3% but operating margin declined 2%.
What typically causes this pattern and what should I
look for in my analysis?
Cash Flow vs. Income Analysis:
Net income is $5M but operating cash flow is negative $2M.
Walk me through the common reasons for this divergence
and what I should investigate.
2.5 Common Pitfalls and How to Avoid Them
Pitfall 1: Trusting AI Math
The Problem: AI will sometimes perform calculations and get them wrong. It's pattern-matching, not computing.
The Solution:
- Always calculate ratios and variances yourself
- Use AI for interpretation, not computation
- Double-check any numbers AI provides
Pitfall 2: Missing Context
The Problem: AI doesn't know company-specific factors, recent events, or management decisions that explain the numbers.
The Solution:
- Add context to your prompts
- Validate AI explanations against what you know
- Use AI suggestions as investigation starting points
Pitfall 3: Over-Reliance on AI Conclusions
The Problem: AI analysis sounds authoritative but may miss critical factors or reach wrong conclusions.
The Solution:
- Treat AI output as a first draft
- Apply your professional judgment
- Verify significant conclusions independently
Pitfall 4: Generic Analysis
The Problem: Without specific context, AI provides generic textbook analysis that doesn't add value.
The Solution:
- Provide industry and company specifics
- Ask about your particular situation
- Request specific, actionable insights
2.6 Practical Exercise
Exercise: Complete Financial Analysis
Practice this workflow with sample data:
Step 1: Calculate Your Ratios (You do this in Excel)
Step 2: Structure Your Prompt
I'm analyzing [fictional company name], a [industry] business.
Here are the key metrics I calculated:
[Your calculated ratios]
Comparable period/benchmarks:
[Prior year or industry data]
Context:
[Any relevant information about the business]
Please provide:
1. Key observations (3-5 bullets)
2. Primary concerns (2-3 items)
3. Investigation questions I should pursue
4. How I might structure findings for management
Step 3: Evaluate AI Output
- Does the analysis make sense?
- What context might AI be missing?
- What would you change or add?
Step 4: Refine and Integrate
- Combine AI insights with your knowledge
- Add company-specific context
- Draw your professional conclusions
Module 2 Summary
Key Takeaways:
-
AI enhances interpretation: Use AI for synthesizing data into insights, not for calculating numbers.
-
Context is crucial: The more context you provide, the more useful AI analysis becomes.
-
Build a prompt library: Develop and refine prompts for common analytical scenarios.
-
Verify everything: AI analysis is a starting point, not a conclusion. Apply your judgment.
-
Focus on investigation questions: AI's best value may be suggesting what to investigate next.
Preparing for Module 3
In the next module, we'll explore using AI for report generation and summaries. You'll learn to:
- Draft management reports with AI assistance
- Create executive summaries efficiently
- Prepare board presentations
- Write analytical memos
Before Module 3:
- Practice the ratio analysis prompt template
- Try analyzing familiar financial data with AI
- Note what works well and what needs refinement
"The best analysts don't just calculate—they interpret. AI makes interpretation faster and more thorough, but never automatic."
Ready to continue? Proceed to Module 3: Report Generation and Summaries.