Operator: The AI Agent for Investment Banking Workflows
5 MIN. READ
The way financial models get built hasn't changed in decades: a junior banker opens Excel, manually sources inputs, structures tabs to team-specific convention, and spends hours producing a first draft that a senior will spend twenty minutes reviewing.
The problem is that the most skilled people in financial services are spending the majority of their time on construction, not thinking. Every hour spent formatting a financial model is an hour not spent on the judgment call that actually moves the deal.
We built Operator, an AI agent for Investment Banking workflows, to change that.
How Operator Works
Operator is Model ML's AI agent for Excel, PowerPoint, and Word, and it works the way your team's bankers actually do. It runs on a new agentic framework that always knows exactly where to read and write in a document, and can plan and carry out many steps in sequence without losing track of the task.
Unlike AI tools that generate a static file from a template, Operator is an AI agent that builds financial models in Excel, creates pitch decks in PowerPoint, and drafts documents in Word the way an analyst would: step by step, with live formulas and editable outputs. It's AI for financial modelling and investment banking workflows that produces real first drafts, tailored to your data and your team's conventions.
Use Cases: Operator In Practice
Example 1: A pitch needs a sector story. Operator builds the whole book.
For coverage bankers, PE associates, and corp dev teams sizing up a new vertical, building a credible sector view from scratch triggers the same grind every time. Days of analyst time spent pulling data from a dozen sources, sizing the TAM top-down and bottom-up, benchmarking the competitive set, and formatting all of it into the deck an MD will actually bring to a client. Operator can research the sector end-to-end, build the TAM analysis in Excel, map the competitive landscape, structure the write-up to house convention, and return a full first-draft report for senior review in minutes.
Example 2: A client moves up the meeting. Operator builds the model on your way to it.
For bankers, a request to walk through numbers on short notice usually means rebuilding a model from scratch or working off a stale one. Operator builds the DCF and LBO the way an analyst would in Excel, with live formulas, linked assumptions, and sensitivity tables that actually recalculate. Request the leverage case, a sensitivity flexed on exit multiple, or a football field, and Operator returns a real, editable model, ready before the meeting starts.
Example 3: A deal needs buyers tracked. Operator builds the log.
Banking work isn't only financial modeling. A real share of it is process management: tracking buyers, managing workstreams, keeping the deal moving. That work is usually manual and ad hoc, pulled together in whatever spreadsheet is on hand and updated by hand as the process moves. Operator takes an existing dataset and produces a structured, formatted buyer log in Excel, ready to use immediately.
The first draft of even the most complex financial model has always required a human to build it. Operator changes that assumption. For investment banking teams, that means senior talent focused on judgment rather than construction, junior analysts moving faster and learning from better starting points, and clients receiving sharper, faster work.
Want to dive deeper? Book a demo.
