AI, Excel, and the Future of Financial Modeling: Insights from the Latest Future of Finance Lab (Session#2)
Background
The latest session of the Future of Finance Lab continued its mission to empower finance professionals with the latest thinking and tools at the intersection of artificial intelligence (AI), Excel, and financial modeling.
Led by Lance Rubin, CFO and Excel automation specialist, the session offered a practical exploration of how AI is reshaping modeling workflows, the frameworks that underpin robust financial analysis, and the realities of integrating new technology into established processes. With a mix of live demonstrations, candid discussions, and resource sharing, this ongoing and free series remains a must-attend for anyone looking to future-proof their finance skills.
Key Insights and Frameworks Discussed
The Six Foundations of an AI-Powered Accountant
Lance Rubin began by revisiting the six foundational pillars for modern finance professionals: Excel fluency, process and data mastery, technology assessment, AI integration, growth mindset, and human skills. He emphasised that while AI is a powerful enabler, its effectiveness depends on strong underlying processes and data structures. “Everyone’s doing the cart before the horse, AI first and forget all of the first three, and that’s a big problem,” Lance noted, urging attendees to build on solid foundations before layering on advanced technology.
The HACK Framework
Central to the discussion was the HACK framework—Hygiene, Automation, Capability, and Knowledge. This framework guides finance professionals in balancing technical rigour with adaptability and continuous learning. Lance illustrated how hygiene (clean data), automation (streamlining repetitive tasks), capability (technical skill-building), and knowledge (ongoing education) are all essential for thriving in a tech-driven finance environment.
Financial Modeling Best Practices
The session delved into the FAST standard—Flexible, Appropriate, Structured, and Transparent—as a best practice for model design. Lance explained that while there are several standards, the FAST acronym serves as a useful reminder to keep models adaptable, fit-for-purpose, well-organised, and easy to audit.
Scenario analysis, sensitivity checks, and dynamic dashboards were highlighted as essential features of modern models. Lance doesn’t adhere strictly to the FAST standard per se, but advocates for its high-level principles, which are sound.
Practical Takeaways and Actionable Strategies
Fortnightly Nugget: Give AI Structure
A recurring lesson was the importance of providing AI with structured, deterministic instructions. Lance shared a case where he reconciled trial balances across eight legal entities using Excel Cloud and TabAI, reducing a multi-day manual process to just a few hours. “Give AI structure. Give it deterministic type commands and even show or do it. It can replicate,” he advised, demonstrating how thoughtful prompts and data preparation can unlock AI’s potential.
Downloadable Resources and Community Learning
Participants received a SAAS financial model starting file during the session, reinforcing the series’ commitment to hands-on learning.
Lance encouraged attendees to experiment with the file and share their experiences, noting, “The recording, obviously, is going to be on the Knowledge Hub on Elquens, as well. The solution, you can purchase it.” This culture of resource sharing and peer feedback is a hallmark of the Lab.
Data Privacy and Governance
Lance issued a strong warning about uploading sensitive data to cloud-based AI tools, likening it to “taking a USB stick, plugging it into my laptop, taking a whole bunch of company data, walking down the road to an internet cafe, plugging it into the internet cafe PC, and sending that file to myself.” He and guest Craig Hatmaker stressed the need for clear governance and adherence to company policies when experimenting with AI in finance.
Notable Examples and Case Studies
AI Tools Put to the Test
A highlight of the session was Lance’s live comparison of multiple AI tools—Anthropic’s Claude, Microsoft Copilot, Gemini, Grok, and ChatGPT—each tasked with building a complex five-year SaaS financial model. His candid evaluations included:
- Copilot Agent Mode: Rated highest for balancing the model and handling complexity, though not flawless.
- ChatGPT: Produced hard-coded numbers, lacking dynamic formulas.
- Gemini and Grok: Did not generate usable models.
- Claude Opus: Underperformed, but Lance planned further testing.
“Copilot agents slightly ahead, copilot chat, not so much. ChatGPT is a little bit behind. Claude Opus underperformed… Grok and Gemini didn’t,” Lance summarised.
Real-World Modeling Challenges
Lance described a recent engagement where auditors required reconciliation of trial balances across entities and currencies. By leveraging structured data and AI, he reduced a task estimated at two to three days to just a few hours, illustrating the transformative potential of combining domain expertise with technology.
Looking Ahead
The Future of Finance Lab is more than a webinar—it’s an interactive community dedicated to learning, sharing, and growing together. We invite you to join our next session, connect with peers, and continue building the skills that will define the future of finance.
For resources, recordings, and more, visit our Knowledge Hub and stay tuned for further updates!
You can find more content on Eloquens, including the FREE slides, PDF exports of Excel workbooks and paid content, including all AI-built models and the human-built solution and a comparison file can be found here.
The session was also recorded and is available to be viewed on YouTube.
Want to discuss how AI can transform your finance function? Get in touch with Model Citizn to learn more about our approach to AI-powered financial modelling and strategic implementation.
Want to take action? You can by clicking here
We just launched our AI-Powered series of FREE fortnightly sessions to unpack all the hype and give solid foundations to finance professionals. Join our Friday Future of Finance Lab by registering here.
Friday’s Future of Finance Lab
AI-Powered Accountant
Join our fortnightly community where finance professionals share insights, solve real challenges, and stay ahead of the AI revolution (max 50 attendees).
Key Benefits:
✅ Live Problem Solving – Bring work challenges
✅ Expert Insights – Practitioners not trainers
✅ AI Integration – Leverage AI in finance
✅ Networking – like-minded professionals
✅ Zero Cost – Completely free, always
What You’ll Get:
✅ – Fortnightly Focus Areas in the following areas
✅ – Financial Modeling Deep Dives
✅ – Data Analysis & Power BI Techniques
✅ – AI Applications in Finance
✅ – Open Forum & Case Studies Exclusive Resources
✅ Meeting recordings and AI-generated summaries
✅ Templates and tools shared during sessions
✅ Resource library access
Who Should Attend:
✅ Finance professionals wanting to upskill
✅ Data analysts working with financial data
✅ Anyone curious about AI in finance
✅ Business leaders seeking data-driven insights
Buckle up and look forward to seeing you there!
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