AI Finance Club

7 Proven Frameworks to 10X Your Finance Team’s Productivity! ?? Watch the full video here: https://lnkd.in/dG6_XMnW Managing a finance team is tough - but with the right systems, you can maximize efficiency and get more done with less effort. In this video, Nicolas Boucher shares 7 powerful frameworks that top finance leaders use to streamline processes, reduce inefficiencies, and boost performance: ? The AI-First Approach – Leverage AI to automate tasks and increase efficiency ? 1-3-1 Decision Framework – Identify problems, explore solutions, and take action fast ? Pareto Principle (80/20 Rule) – Focus on the 20% of tasks that drive 80% of results ? Elon Musk’s 5-Step Process – Optimize workflows BEFORE automating them ? Kanban for Finance – Visualize tasks and track progress in real-time ? Getting Things Done (GTD) – A productivity system to reduce overwhelm ? Eisenhower Matrix – Prioritize urgent vs. important tasks effectively This video is a must-watch if you want your finance team to work faster, make better decisions, and eliminate wasted effort. ?? Watch now: https://lnkd.in/dG6_XMnW Which framework will you try first? Let me know in the comments!

Socratic Prompting PS. Download my Top 100 ChatGPT Tips for free here: https://lnkd.in/drq79Pdr "Socratic Prompts" involve asking questions that lead the AI to explore a topic deeply, encouraging critical thinking and uncovering underlying assumptions This method is highly beneficial for SME CFOs, as it aids in exploring complex financial issues, uncovering new perspectives, and fostering strategic thinking. How to use Socratic Prompts: Ask Open-Ended Questions Ask questions that don't have straightforward answers, prompting deeper exploration. Example: I have a team of 5 Finance professionals, what would be for them the best development program & why? Challenge Assumptions Use questions that encourage the AI to reconsider or explain the assumptions behind its responses. Example: Which assumptions did you use when creating this output? Seek Clarifications Prompt the AI to clarify and expand on its answers, leading to more nuanced understanding. Example: Can you clarify on ___________? ?? Have you ever tried this prompting technique?

Benefits of ChatGPT for Finance Teams PS. My ChatGPT For Finance Video Course is at 50% discount for 8 more hours only: https://lnkd.in/dfks3A3S Here are 30 ways of how you can use ChatGPT to help your Finance Team: Productivity 1. Idea generation 2. Correcting a text 3. Summarized a text 4. Translating a text 5. Research terms & definitions 6. Simplify a complex text Financial Analysis 7. Break-even analysis 8. Inflation 9. Hourly rate 10. Compare two scenarios 11. Change of price and demand 12. Business Case ROI Tutorial for Tools 13. Excel 14. PowerPoint 15. Word 16. PowerBI 17. SAP 18. Quickbooks Create Finance Procedures 19. Closing checklists 20. Finance guidelines 21. Internal control 22. Standard Operating Procedures 23. Step-by-step guide 24. Dunning procedure and letters Write High-Quality Text 25. Budget guidance 26. Request input 27. Prepare a meeting 28. Communication with clients 29. Executive summary 30. Minutes

History of LLMs PS. Download my Top 100 ChatGPT Tips for free here: https://lnkd.in/d6TxRwFD How many do you know? 1. LLAMA 2 7B to 70B parameter text models evolve. Llama-2-Chat shines in dialogue, and rivals top models in safety. Released July 18, 2023, with a custom commercial license on Meta's site. 2. GPT-2 GPT-2, predecessor to GPT-3 by OpenAI, generates human-like text, released in 2019 with fewer parameters but impressive language capabilities. 3. ERNIEBOT Limited knowledge on "Erniebot"; possibly a newer or specialized model post-January 2022 in the language model domain. 4. DOLLY 2.0 Abu Dhabi's TII created Falcon language models—Falcon-40B leads, aiming to rival closed-source LLMs. Parameters: 7B & 40B, Apache 2.0 licensed, launched June 5, 2023. 5. MPT MosaicML releases MPT-30B: English-code transformer, 8k token context, FlashAttention for speed, HuggingFace/NVIDIA support, 30B parameters, Apache-2.0 License since June 22, 2023. 6. ALPACA As of Jan 2022, ALPaCA wasn't widely known among large language models. Subsequent developments might have changed its recognition or status. 7. BLOOM BLOOM: 176B-parameter model in 46 languages & 13 programming languages, excels in text gen, adaptable for Info Extraction & QA. 8. BERT BLOOM: 176B-parameter model in 46 languages & 13 programming languages, excels in text gen, adaptable for Info Extraction & QA. 9. OPENCHATKIT Open-source chatbot, GPT-NeoXT-Chat-Base-20B-v0.16: sustainable, excels in dialogue, Q&A, classification, and summarization. 10. FLAN-T5 FLAN-T5, an evolved T5, excels in zero/few-shot NLP tasks with 1000+ tasks covered in multiple languages. Variants range from 80M to 11B parameters, targeting diverse language support. ??Which other LLMs do you know?

How to use AI and Python for FP&A Data Visualization? Credits to Christian M., follow him for more practical AI tips for finance. ------------------ Here's the content: Many hashtag #finance and FP&A teams asked me this. So I created a 5 steps framework to help you get started. With an LLM (ChatGPT, Copilot, Gemini, etc)+ Python, you can transform data into powerful visual stories. Here’s the 5-step approach I use: 1. Show ChatGPT your data Paste a few rows of your dataset and ask for visualization suggestions. This step is super important to understand. You do not need to GIVE your data to an "AI Company". You just need to show how your data LOOKS LIKE. Use this prompt: “I'm a FP&A analyst (replace this with your role) working with a dataset and I'd like your help picking the three most effective visualizations for it. Below is a sample of the data (including column names and a few rows). Based on the structure, types of variables, and any potential insights you notice, recommend three visualizations that would best highlight trends, patterns, or relationships in the data. Here is the data: (Paste a few rows of your "dummy" data here, ideally 5–10 rows, including the header. You don't need to add real data but the format of the data is important [e.g. date, number, percentage[)” 2. Get the 3 best examples Let AI recommend the most impactful charts for your dataset. 3. Ask for Python Code Get the code from the LLM and then run it in G. Colab, VS or even Excel. My recommendation: If you want the easiest to start → Google Colab If your company prefers Microsoft Products → Visual Studio If you want to stay in an environment you know → Python in Excel! If you need help with choosing, let me know and I can suggest or send you some courses to start! 4. Execute and visualize Generate dynamic charts that highlight key financial insights. 5. Improve and Customize! ?? This is where you take it to the next level: ? Refine Styling – Customize colors, fonts, and labels for readability. ? Add More Insights – Overlay trend lines, percentage changes, or KPIs. ? Make it Interactive – Use Plotly for drill-down capabilities. ? Automate Everything – Schedule updates and integrate into workflows. ? Leverage AI Further – Use predictive modeling to forecast trends. Hope this is useful and if you want the data and code I used for the belows examples just message me or comment and I can send! ------------ Follow the AI Finance Club for more AI use cases for finance.

Prompt Engineering PS. Grab my ChatGPT for Finance video course for 50% off now: https://lnkd.in/dfks3A3S There are different types of prompt engineering. We have compiled the best prompt engineering techniques to maximize your output. Basic Prompting Frameworks: CSI (Context Specific Instruction) + FBI (Format Blueprint Identity) Contextual Information: Include relevant background to provide a comprehensive understanding. Precise Language: Use specific, unambiguous terms for clarity. Analogies and Examples: Use comparisons to simplify complex financial concepts. Advanced Prompting Techniques Agent Prompting: Framing prompts to make GPT act as an 'agent‘. Explicit Reasoning: AI details its process or reasoning in a clear, step-by-step manner. Chain-of-Thoughts: Breaking down a complex query into a series of simpler, logical steps. Chunking: Complex information broken down into smaller, more manageable 'chunks'. Prompt Optimization & Expansion: Start with a basic prompt and ask the AI to improve it. Team Prompting: Simulates a collaborative team environment using multiple agents. Socratic Prompting: Asking questions that lead the AI to explore a topic deeply. Fact Checking: Using prompts to verify the accuracy and credibility of information. Meta Cognition: Prompting involves encouraging the AI to reflect on its own thought process. Meta Cognition: Prompting involves encouraging the AI to reflect on its own thought process. ??Which other LLMs do you know?

How can you use AI for Finance? ??Free AI Advance for Finance Course for Finance Leaders: https://lnkd.in/dkAR9YFs Below, I am telling you how ?? Here are the 5 stages you need to go through: 1. Beginner You know AI exist but you don’t know where to start and you are afraid to start because of confidentiality issues. ?? My advice to go to the next level: Start using ChatGPT or Bard (it doesn’t matter which one) and do this: Today take notes of all the mini tasks you do at work. Tomorrow, try to perform each of the tasks with ChatGPT by just asking: “My job is X and I want to do Y, can you draft it for me?” It might only work 20% of the time… but that’s already many use cases in one day! 2. Basic Now that you have discovered some ways where it works and some where it doesn’t, you need to be more methodologic. To go to the next level you need to use my framework for prompting. It will bring consistent results which provide you value. Here is the framework: CSI for Context / Specific / Instruction And then add FBI for Format / Blueprint / Identity CSI+FBI : this is the secret framework I teach in all of my courses and corporate workshops. 3. Intermediate You get consistent output but you are stucked when complex problems arise. This is where you need to learn prompt engineering. Here are the 3 most important you need to master: - Chain of thought: to solve problems - Chunking: to create procedures - Agent prompting: to make AI do financial analysis for you 4. Advanced Now you are a master at doing everything inside ChatGPT but you cannot do it on confidential data and you cannot scale (which is a pity as AI is by design made for scaling!) What is the magic way to go to the next step? The response scares a lot of people… Because they think it’s not for them. Or that they cannot learn it. The response is: Python Why? Because this is the language that can computes figures, create graphics, change and combine Excel files, processes mega data sets and all of these in your own secured environment. And Finance needs to use this language to unleash automation and financial analysis and forecasting abilities. But the good news: you don’t need to learn it anymore. You can have AI code it for you. 5. Master This is the path that i want to pursue for myself and some of my colleagues experts in the field. This is where you know how to parameter an AI model for Finance use cases. For this, you need to learn JSON & Python but also have access to environments like Azure. Start by getting access to a low code platform like PowerPlatform and then set up your first mini use case using AI Builder from Microsoft like an OCR or translation module.

30 Ways ChatGPT Helps in Finance PS. Save 5+ hours per week with ChatGPT and grab the 50% discount until Friday on my ChatGPT for Finance Video Course: https://lnkd.in/dfks3A3S Here are 30 ways you can use ChatGPT in Finance ranging in the 3 levels of mastery: Beginner / Basic / Advanced. Beginner level: You know AI exists but you don’t know where to start and you are afraid to start because of confidentiality issues. How to start? Try using ChatGPT for 3 tasks you did today at work. For example, you can: Prepare reminder letters Research-adapted performance metrics Ask how Excel formulas work Run a horizontal analysis Simplify Finance for non-finance people 2. Basic level Now that you have discovered some ways where it works, you need to be more methodologic. Use CSI for Context / Specific / Instruction & then add FBI for Format / Blueprint / Identity For example, you can: Draft impairment memo Identify cost-saving strategies Step-by-step PowerQuery tips Identify KPIs and give you their calculation Explain complex legal terms 3. Advanced level You get consistent output but you have difficulties with complex problems. You need to learn prompt engineering. Especially those 3: Chain of Thought / Chunking / Agent prompting. For example, you can: Draft Internal procedures Tax liability improvement Guide you to extract Quickbooks reports Put in place a distribution analysis Prepare a detailed training outline ?? What is your ChatGPT level now?

Agent Prompting PS. Enroll in my Advanced AI course for finance leaders for free: https://lnkd.in/dJUR2-DG "Agent Prompting" involves framing prompts as if they are tasks or queries for an 'agent' within the AI's framework. For SME CFOs, this technique can simulate consulting with a team of experts or advisors which provides diverse perspectives and solutions to financial challenges. How to make your own agent? Create your agent by: Defining the following traits: (you can customize at your convenience and see the different results) We will take the example of a Financial Analyst. 1. Name: You are an AI Financial Analyst 2. Definition: You are an experienced Financial Analyst 3. Knowledge: Top-tier management consulting firm, strategic consultant, financial consultant, management consultant, business analyst, data analyst. 4. Traits: High business acumen, complex problem-solving skills, adaptability, creativity, financial analysis, financial modeling, and meta-analysis. 5. Analysis: You can perform descriptive analysis, and diagnostic analysis, propose financial analysis by explaining the method and why it is relevant, & calculate KPIs. 6. Output: First propose the methods you want to use and ask the user for confirmation. Also, ask in which cell in Excel their table starts. Then in the second answer: calculate a sample showing calculations and ask the user for validation. Once the user has validated, show the formulas in excel using exactly the cell references, based on the information provided by the user. 7. Format: Bullet points, Headlines and present a summary in a table format. 8. English: Simple English, short sentences with figures. 9. Start: Do you understand? If yes, then ask the user for the data.

Copilot in Finance PS. Enroll in my 5-day Advanced AI course for Finance Executives here: https://lnkd.in/d9hApBVb How can you use AI Copilot for Financial Analysis? Here are the use cases: 1. Excel ??Create a formula to calculate the Net Present Value (NPV) of a series of cash flows. ??Explain how to use a Pivot Table to summarize your data. ??Generate a graph showing data insights. 2. PowerPoint ??Helps to create a presentation from scratch. ??Add a relevant stock photo picture to make your slide more enjoyable. ??Provide tips on how to create an engaging presentation. 3. Word ??Help draft a professional procedure. ??Explain how to use Word’s referencing features to manage your document sources. ??Provide a template or an example of a business proposal. 4. Outlook ??Draft a reply to an email for you ??Guide on how to set up an automatic reply for when you’re out of the office. ??Summarize email for you. 5. Teams ??Make the minutes of a meeting ??Summarize a discussion ??Ask which questions are unresolved