Project 5: Analyst Review Mode (“Second Eyes”)

Expanded Problem Statement

Even experienced analysts seek a second pair of eyes to catch mistakes or provide feedback on reports. In fast-paced financial environments, it’s not always feasible to have a colleague review every memo or table. Current review processes are manual, sporadic, and often prone to oversight:

• Important calculation errors or outlier data points can be missed until a meeting or client sees them.

• Narrative reports might contain unclear logic or bias that the original author is “too close” to notice.

• Compliance or style inconsistencies (like using non-approved wording) slip through without a dedicated reviewer.

Feature Description

Analyst Review Mode is like an AI co-pilot that reviews analysts’ work with a fresh perspective:

• Users can upload a draft memo or analysis spreadsheet. The AI then performs a structured review, e.g., for a memo:

• • Clarity & Tone: Flags jargon or ambiguous statements.

  • Logical Consistency: Highlights if conclusions don’t follow from data.

  • Data Check: For tables, it might recalc key figures or check if any values look off/outliers.

  • Compliance/Standards: Notes if any section violates company style guidelines or regulatory phrasing.

• The output is a feedback report listing issues and suggestions, essentially giving analysts a checklist of improvements. It’s akin to having an editor or peer reviewer go through the document.

• The review mode emphasizes it’s a supportive tool, not a grader. Framing feedback constructively (“Consider explaining X in more detail…”) encourages adoption.

Deliverables

• Workflow Mockup: Illustrations of how an analyst uploads a document and views the AI-generated feedback.

• Feedback Report Template: A standardized layout for the AI’s review (sections for strengths, issues, suggestions).

• Prototype Demo: Perhaps using a sample memo to show how the AI comments on each part.

• Integration Plan: Outline how this mode hooks into the existing platform (e.g., an “Upload for Review” button next to document editor).

Skills to Manage

• Natural Language Processing: To analyze text for tone, clarity, and logical flow.

• Data Analytics: To cross-verify numbers and detect anomalies in tables or charts.

• UX & Content Design: Making the feedback understandable and helpful, avoiding overly technical language in the review.

• Financial Writing & Compliance Knowledge: Ensure the style and compliance checks are aligned with financial industry standards (like avoiding certain forward-looking statements or ensuring disclaimers are present).

Risks to Manage

• False Positives/Negatives: The AI might flag correct content as wrong (or miss an actual error). To manage this, allow easy dismissal of feedback items and maybe confidence levels on each item.

• Analyst Trust and Pride: Some may feel “evaluated” by a machine. We need to position it as a supportive tool that augments their work (and perhaps allow opting out for sensitive docs).

• Privacy: Uploaded content could be sensitive (e.g., unpublished financials). The system must secure this data, possibly doing on-device or on-premise analysis to alleviate confidentiality concerns.