Microsoft is using Financial Modeling Institute material to support financial modelling guidance in Copilot in Excel, linking a widely used spreadsheet product with a professional accreditation body for financial modellers.
As it develops how Copilot in Excel handles finance work, Microsoft is drawing on the institute's library of real-world modelling cases and professional frameworks. The material is now also part of how the company evaluates the assistant for finance tasks in Excel, which has close to 750 million users worldwide.
The arrangement brings a specialist finance body into a broader debate over how artificial intelligence will be used in high-stakes spreadsheet work. Financial models sit at the centre of decisions across corporate finance, investment banking, private equity, accounting, infrastructure and strategic planning, where errors in assumptions or structure can have significant consequences.
For Microsoft, the link provides access to frameworks built around professional standards for model design and review. For the institute, it brings its accreditation approach into a mainstream software product used by finance teams around the world.
Microsoft said, "AI that meets the bar of professional finance work isn't something we've done alone. We've partnered with Financial Modeling Institute - the global body that credentials the industry's most demanding modelers. FMI's library of real-world financial modeling cases has become a foundational part of how we evaluate Copilot in Excel for finance work."
The institute said its framework has been developed over the past decade through credentialing finance professionals globally. It is designed to assess the rigour, transparency, flexibility, and decision usefulness of financial models, and is being used to benchmark the guidance generated within Copilot in Excel.
Rising scrutiny
The announcement comes as finance departments face growing pressure to introduce AI tools into reporting, forecasting and deal analysis without weakening controls. While AI can speed up model construction, the use of machine-generated numbers in regulated or high-value settings has raised questions about accountability when outputs are wrong, incomplete or poorly understood.
That is likely to sharpen the focus on human review rather than remove it. If a model can be assembled in seconds, the value may shift to testing assumptions, checking dependencies, understanding outputs and challenging whether a model is fit for the decision at hand.
"Financial models are not simply spreadsheet exercises - they are decision-making infrastructure. As AI becomes more deeply embedded into finance workflows, the profession needs more rigor, not less. AI can accelerate model construction, but professional judgment remains essential. The professionals best positioned to use these tools effectively are the ones who understand every assumption, dependency, and output inside the model," said Ian Schnoor, Executive Director of the Financial Modeling Institute.
That reflects a wider tension in finance roles. Investment bankers, financial planning and analysis teams, and corporate finance professionals may gain speed from AI-assisted drafting and scenario building, but they also face a greater burden to prove outputs have been checked and that critical judgments still rest with qualified staff.
The development also strengthens the relevance of the institute's Advanced Financial Modeler accreditation, known as AFM, as AI becomes more common in finance workflows. The organisation also offers Chartered Financial Modeler and Master Financial Modeler accreditations for professionals across banking, accounting, asset management, credit, venture capital and related fields.
Professional standards
The use of a professional framework inside Copilot in Excel suggests Microsoft is trying to position its finance-related AI features around accepted modelling practice rather than generic text generation alone. In practical terms, that means guidance is being shaped by standards intended to make models clearer, more auditable and more useful for decisions.
It also underlines a broader shift in software development, as major technology companies seek outside domain expertise to make AI tools more credible in specialist fields. In finance, where spreadsheet errors can affect valuations, budgets and transactions, tolerance for opaque outputs is low.
"Excel has always been the finance professional's tool of choice. The next chapter is about helping finance professionals use AI responsibly and effectively inside the tools they already rely on. This recognition is an important moment for FMI, for AFM accreditation holders, and for the financial modeling profession globally," Schnoor said.