Accelerating the downstream analysis: From spread to IC-ready memo
An analyst’s job isn’t finished once the financials are spread — the final deliverable is often the Investment Committee (IC) memo. Today, the bridge between your Excel model and your Word document is entirely manual.
The current process is dangerously slow and error-prone — analysts are forced to start every memo from scratch or from a saved version of their last deal. When new data arrives, or a model assumption changes, the entire report must be manually updated — re-pasting tables, retyping ratios, and cross-checking every figure. Without a direct link between the memo outputs and the source calculations, analysts must manually locate each input when the investment team requests it.
F2 eliminates this ‘last mile’ friction by treating the memo as a live extension of the spread. It replaces manual transcription with a linked, automated workflow that ensures your narrative always matches your latest data.
How analysts draft an IC memo today
Friction in the current workflow begins the moment spreading is complete.
To create the investment committee memo, most analysts rely on two archaic methods:
- Starting from scratch: A massive waste of time that requires rebuilding standard tables, headers, and legal disclaimers.
- Duplicating a previous memo: Taking an old memo, deleting the old data, and manually checking that no references from the past deal make it to the final IC-ready version.
An analyst might take a screenshot of a table from the spread and paste it into the document. If the Managing Director (MD) requests a sensitivity change, the analyst must rerun the spread, rescreenshot the table, and repaste it into the memo. This is (unfortunately) true of any aspect of the memo that an MD requests be changed.
Generating the first draft using your firm’s institutional memory
Every top-tier firm has its own house style — specific ways of calculating Adjusted EBITDA, specific risk factors it prioritizes, and a distinct voice.
For commercial banks, this standardization is driven by scale and compliance. Banks face strict regulatory oversight, including Fair Lending standards, which require every memo to adhere closely to established criteria.
F2 helps firms generate IC materials aligned with their unique formatting preferences by first ingesting precedent materials to ensure every output adheres to the exact same document type (e.g., slide deck vs. Word document), formatting, and compliance guardrails, creating a predictable, audit-ready paper trail.
The AI parses these documents to learn the firm's specific patterns:
- Structure: Which sections appear in what order? (e.g., Executive Summary -> Deal Overview -> Financial Analysis) .
- Formatting: How are charts and tables styled (e.g., color, font, type of chart/table)? What logic is used for headers, axes, columns/rows?
- Tone: Is the writing persuasive or objective?
This allows the platform to generate a first-draft memo that reads and feels like it was written by your firm, reducing formatting friction.
Using prior deal logic to build a better narrative
Once the template is loaded, the spread data flows into it automatically. But F2 does more than just populate financials; it helps write the accompanying narrative. Because the AI understands the reasoning behind the spread, it can synthesize the data into text.
Leveraging prior deal logic
One of the most effective ways to accelerate drafting is to reference prior work. Deal teams often want to replicate a specific analysis from a successful past deal.
In F2, an analyst can use natural language to reference institutional history: "Based on the financial summary I did for [past company], create a similar section in this report for this company." With the help of F2, underwriting teams can easily identify the right companies in their portfolio to compare and contrast with new opportunities.
The system retrieves the logic from the previous deal (e.g., how it presented customer concentration or churn analysis) and applies it to the current deal’s spread data. Along the way, an analyst can verify that the correct logic is being applied and track the deal’s spread data to confirm accuracy. This ensures consistency across the portfolio and significantly speeds up the drafting process.
Contextual drafting and refinement
Instead of manually typing out a description of the revenue growth, an analyst can prompt the system: "Write a short summary of this company's revenue model and output it to this report.”
The AI analyzes the spread, identifies revenue streams, and generates the draft. If the output isn't quite right, the analyst can edit it in-line using natural language: "Rewrite that section to be three bullets of management discussion on key risks."
Leveraging live data to update a memo
In a standard workflow, data is static the moment it’s pasted into a Word document. If anything in the input calculations changes — such as an applicant uploading a new document version or an analyst changing sensitivity scenarios — financials must be respread and repasted into the memo draft.
In F2, the full lifecycle of an analyst’s workflow is managed on a unified platform. All outputs are tied to the spreads, which are linked to the applicant’s data room. This means that whenever new data is added to the deal or spreads are manually updated, the platform regenerates the memo’s tables, charts, and narratives based on the latest data.
Visualizing the data
Analysts can generate visuals directly from the spread data using natural language commands. For example: "Create a table showing EBITDA over time for these three companies." The system pulls the normalized data from the spread and renders the table instantly.
If the chart needs adjustment, there is no need to return to Excel. You can edit the output directly: “Make it green and yellow, or change the periods from years to months.”
The dynamic update loop
Importantly, these outputs are linked to the underlying model. If you go back to the spread and adjust a normalization mapping (e.g., moving an expense from "One-time" to "Recurring"), the resulting EBITDA changes. As a deal progresses, it’s common to have to rerun certain models and update relevant reports.
In F2, the tables and charts in the memo update automatically. This eliminates the version-control challenge of saving multiple files. Teams can collaborate on a single, living document where the narrative and the numbers stay in sync.
Defending the deal with complete auditability
Any data presented to the Investment Committee must be defensible. Whether it’s an IC member tracing the logic chain of a specific calculation or an analyst double-checking their work, auditability should be instantaneous.
F2 embeds an Audit Mode feature directly into memo generation to address this.
Interactive citations
Every chart, table, and sentence in the generated memo is audit-ready. When an analyst clicks a data point in the report, the system highlights the source.
Traceability to the source
The citation points directly to the specific page in the diligence document or the specific cell in the spreadsheet that supports the claim. If the memo references "Share of Ownership," the system points to the Cap Table in the Excel model. Furthermore, for financial outputs that F2 calculates based on the borrower’s materials, the platform will reference all cells in a spreadsheet used for each calculation, giving analysts a path to verify second-order analysis.
This creates a layer of trust that enables the IC to verify assumptions in real time without slowing down their review.
Conclusion
Investment Committees don’t care how long an analyst spends copy-pasting tables or re-formatting headers; they care about the quality of their thesis and the reliability of their numbers. But when the process of converting a spread to memo is manual, analysts spend their best hours on data entry rather than deep analysis and judgment.
By bridging the gap between spreads and memos, F2 helps investment teams eliminate the risk of version-control errors and the friction of starting from scratch — enabling analysts to build defensible, audit-ready paper trails and present their analysis to the Committee with complete confidence.
With automated templates, dynamic updates, and complete auditability, investment teams can produce higher-quality, data-backed investment theses in a fraction of the time.
