Practical Applications of AI in Finance, Python and machine learning for FP&A
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Hi Reader , Big news: Claude Sonnet 5 was released, and if you work in Finance or FP&A, this is one of the most exciting AI model updates to test. The reason is simple: finance teams do not need AI that only writes emails faster. They need AI that can help build analysis, dashboards, forecasts, commentary, and decision-support tools. I created a full video guide for you: I Tested Claude Sonnet 5 on Real Finance and FP&A Use Cases That is what makes Sonnet 5 interesting. In my test, I used it across several real Finance and FP&A use cases:
I also created an interactive guide with 100 use cases: https://claude.ai/public/artifacts/13fbc0e4-4bf0-463d-a4c8-cd0c5e2dab20
And the results were genuinely impressive. Below is a breakdown of each use case, how it works, and why it matters for finance teams. But first, if you're looking to go deeper, my friend Nicolas Boucher will be demonstrating practical AI use cases, including some with Claude, in his free AI CFO Masterclass this Tuesday. You'll learn how to master AI with just one hour per week, automate reporting, forecasting, and analysis without writing code, reduce days of manual work to minutes, adopt AI securely, and stay up to date with the latest AI tools and when to use them. Register here: https://nicolasboucher.online/op/ai-cfo-live-masterclass/?utm_medium=partners&utm_source=christian-martinez&utm_campaign=wky-become-an-ai-cfo In case you cannot attend live, email me back and I can send the recording after the masterclass! Now to the use cases: Claude Sonnet 5 for Finance and FP&A: Practical Use Cases1. Scenario Modeling DashboardOne of the first use cases I tested was a scenario modeling dashboard. The idea was simple: Give Claude Sonnet 5 a realistic finance dataset and ask it to build an interactive dashboard with three scenarios: Base case, Best case, Worst case Instead of just giving a written answer, Claude created a full dashboard-style output with KPIs, assumptions, sensitivity ranges, scenario values, and an executive summary.
Why this matters for FP&A: This was the prompt used:
And got this amazing output on the first try:
Then you can go top right and download it or share it:
I demonstrate step by step here: I Tested Claude Sonnet 5 on Real Finance and FP&A Use Cases 2. Use Claude Sonnet 5 for Budget vs Actual Variance Analysis with CFO-Ready Executive CommentaryThe second use case was budget vs actual variance analysis. This is one of the most practical applications for any finance team. Every month, finance teams need to explain what changed:
In the test, I gave Claude Sonnet 5 a budget-vs-actual dataset and asked it to prepare monthly variance commentary for a CFO pack. The output was:
Why this matters for FP&A: This was the prompt I used:
3. Forecasting SimulatorThe third major test was a forecasting simulator. I gave Claude Sonnet 5 six months of actuals and a set of assumptions, then asked it to build a forecasting tool. The result was an interactive simulator where you could adjust assumptions like: Monthly revenue growth, December seasonal uplift, Cash collection rate andVolatility assumptions As the assumptions changed, the forecast updated automatically.
This is one of the most exciting use cases because forecasting is usually not a static process. In real FP&A work, stakeholders constantly ask: What happens if growth slows? A forecasting simulator lets you answer those questions interactively. Instead of building one static forecast, you create a tool where management can test different assumptions. This is a big shift.
The forecasting simulator also included Monte Carlo analysis. This is an advanced but very useful FP&A technique. Instead of showing only one forecast, Monte Carlo analysis runs many simulations based on different possible outcomes. For example, rather than saying: “Revenue will be $25M.” You can say: “Based on the current assumptions and volatility range, revenue is likely to fall between $23M and $27M, with a base case around $25M.” That is much more useful for decision-making. In finance, the future is uncertain. Revenue growth can change. Margins can move. Cash collections can be delayed. Seasonality can be stronger or weaker than expected. Monte Carlo analysis helps show a range of outcomes instead of pretending that one number is perfectly certain. Claude Sonnet 5 can help create a simulator where the user can adjust assumptions and run simulations directly. Why Claude Sonnet 5 Matters for Finance TeamsThe biggest takeaway from my test is this: Claude Sonnet 5 is not just useful for writing. It is useful for building. That distinction matters. Many finance professionals still think of AI as something you use to draft emails, summarize documents, or rewrite commentary. Those use cases are helpful, but they are only the beginning. The more interesting use cases are:
I also created a guide for Fable 5! You can look at the guides for the latest Claude models here: https://drive.google.com/drive/folders/1pKoWsBw_C0oz7N51w3KJ1sFuZOBVIjZW?usp=drive_link Thanks, Christian Martinez |
Practical Applications of AI in Finance, Python and machine learning for FP&A