Meeting\u00a0the\u00a0high\u00a0bar of professional finance work\u00a0isn\u2019t\u00a0something\u00a0we\u2019ve\u00a0done alone. We\u2019ve also partnered with Financial Modeling Institute (FMI),<\/a>\u00a0the global body that credentials the\u00a0industry\u2019s most demanding modelers.\u00a0Its\u00a0library of real-world financial modeling cases has become a foundational part of how we evaluate Copilot in Excel for\u00a0finance\u00a0work.\u00a0<\/p>\n Tuned\u00a0to your standards\u202f\u00a0<\/p>\n Today,\u00a0we\u2019re\u00a0introducing\u00a0skills\u00a0that\u00a0let teams define how Copilot should complete common processes such as building a DCF, closing the books, refreshing a monthly reporting model, or preparing\u00a0a\u00a0variance analysis. Instead of\u00a0starting from\u00a0scratch\u00a0each time,\u00a0a\u00a0skill\u00a0guides\u00a0Copilot through the steps, applying\u00a0the right structure and formatting, and helping produce an output that is easier to review, reuse, and trust.\u00a0\u00a0<\/p>\n A library of sample finance skills is now available, and you can build your own custom skills using an open-standard markdown file. Save a SKILL.md file in your OneDrive,\u00a0and Copilot\u00a0will\u00a0pick it up\u00a0to build\u00a0a three-statement model or a board package\u00a0using the process you define for it.\u00a0Learn more on how to create, use, and manage skills here<\/a>.\u00a0<\/p>\n Developers and partners\u00a0can\u00a0soon\u00a0build\u00a0and deploy skills through Microsoft Marketplace and Microsoft 365 Admin Center.\u00a0We\u2019ve\u00a0already\u00a0begun working with\u00a0a first wave\u00a0of partners,\u00a0including finance\u00a0and ERP solutions like LSEG, Ramp, Rogo,\u202fSamaya AI,\u202fVelixo, and Vena.\u00a0<\/p>\n Copilot\u00a0can also\u00a0adapt to how you like to work in Excel. With\u00a0Personalization<\/a>,\u00a0you can set preferences once and have Copilot apply them consistently, while workbook rules<\/a> capture structure, naming, and formula conventions\u00a0as a sheet in\u00a0the\u00a0workbook that follows\u00a0the file.\u00a0<\/p>\n Grounded\u00a0in data you trust\u00a0<\/p>\n Copilot in Excel connects directly to the data financial professionals rely on, bringing market data, fundamentals, and research directly into the\u00a0workbook\u00a0so analysis starts from\u00a0the latest sources instead of\u00a0manual data pulls.\u00a0In addition to\u00a0the\u00a0LSEG and Moody\u2019s<\/a> connectors we released in May, today we\u2019re expanding your options with more financial data connectors for bringing public and private market data into\u00a0Copilot\u00a0in Excel.<\/p>\n CB Insights brings predictive intelligence on private companies and markets into Excel. Teams use it to source promising companies, evaluate emerging markets, and support strategy, M&A, and corporate development workflows.\u00a0<\/p>\n Daloopa provides audit-ready fundamentals sourced from SEC filings, investor presentations, press releases, and other public company materials. Analysts use it to update operating models, build comp tables, complex financial analysis, and reduce manual data entry from filings.\u00a0<\/p>\n FactSet connects Excel workflows to financial and alternative data used by investment professionals, financial institutions, and corporations. Teams use it for modeling, screening, market analysis, and research workflows that rely on trusted institutional data.\u00a0<\/p>\n Morningstar brings investment research and data into Excel, including analyst research, ratings, and portfolio analytics. Investment teams use it to evaluate holdings, compare funds, analyze portfolios, and support asset allocation decisions.\u00a0<\/p>\n PitchBook brings institutional-grade private capital market intelligence, including company profiles, deal histories, fund data, and analyst research, directly into Excel. Teams use it to build target lists, support diligence workflows, and screen investments using trusted private market data and expert analyst research.\u00a0\u00a0<\/p>\n S&P Global \u2013 Deterministic Retrieval, developed by Kensho, provides structured, API-driven access to S&P Global data for LLMs and agent-based systems. Teams use it for company research, financial analysis, transcript intelligence, and multi-entity comparisons, with predictable, cited results and full control over orchestration and execution.\u00a0<\/p>\n Note: Third-party connectors and data providers may require separate licensing or subscriptions from the respective provider. Learn more here<\/a>.\u00a0FactSet is in preview and will be generally available in July.<\/p>\n Unlocking finance workflows\u00a0<\/p>\n Combined with Work IQ for grounding\u00a0in\u00a0work context, these features\u00a0unlock real scenarios finance teams work on\u00a0every day. A few example prompts you can now try with Work IQ, skills and connectors (Note: external data\u00a0mentioned\u00a0in the below prompts\u00a0may\u00a0require\u00a0one or more\u00a0connectors).\u00a0<\/p>\n Close the books:\u00a0Compare last quarter\u2019s actuals to plan using internal forecast reviews and planning decks.\u00a0Identify the five largest revenue, expense, margin, and cash flow variances, explain likely drivers, and draft an executive-ready business review summary\u00a0with\u00a0@variance-analysis.\u00a0<\/p>\n Update the forecast:\u00a0Roll forward the current forecast using\u00a0the latest approved assumptions\u00a0and\u00a0budgets\u00a0from my team. Incorporate market data, reconcile changes against the current operating plan, and summarize the key drivers behind the updated outlook\u00a0with\u00a0@model-update.\u00a0<\/p>\n Build the valuation model:\u00a0Use\u00a0@comps-analysis\u00a0to build a DCF, comparable company analysis, and sensitivity model for this company. Pull financial fundamentals, analyst expectations, market benchmarks, and transaction multiples to explain key valuation drivers.\u00a0<\/p>\n Find the next acquisition:\u00a0Use\u00a0@deal-screening\u00a0to help identify acquisition candidates that match\u00a0our internal\u00a0strategy documents and acquisition criteria. Combine company performance and market signals with funding history and investor activity to evaluate, rank, and recommend the strongest opportunities.\u00a0<\/p>\n Analyze portfolio performance:\u00a0Use\u00a0@portfolio-monitoring\u00a0to assess\u00a0this portfolio\u2019s performance against investment objectives, and internal investment committee materials. Pull fund analytics and ratings alongside market performance and risk data to identify concentration risks and recommend portfolio adjustments.\u00a0<\/p>\n Stay\u00a0ahead of\u00a0earnings:\u00a0Use\u00a0@catalyst-calendar\u00a0to analyze\u00a0earnings results, estimate revisions, analyst expectations, and management commentary for the companies in this list.\u00a0Pull consensus forecasts, transcript intelligence, and market data to identify sentiment shifts and summarize the developments that matter most to investors.\u00a0<\/p>\n Controllable by design\u00a0<\/p>\n In finance, the answer\u00a0alone\u00a0isn\u2019t enough. You need to know how you got there. Whether updating a forecast, refreshing a board reporting model, or reviewing changes before quarter close, finance teams need the same things they\u2019ve always demanded from Excel: visibility into what changed, confidence in the methodology, and a clear\u00a0trail.\u00a0<\/p>\n
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