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Natural Language Query Assistant for Financial Calculations

Added Jun 2025 3 design docs

Finance professionals spend hours translating questions like how a fifty basis point rate rise changes weighted average cost of capital into spreadsheet models, and junior analysts often do not know which formula applies in the first place. An assistant that interprets financial questions and shows its working can compress that loop from hours to minutes.

The intern builds a Flask web tool in Python where users type complex financial questions and receive AI-generated, context-aware explanations with step-by-step calculations. Generative AI is the core of the system: the intern designs prompts and guardrails so answers cite the formulas used, state their assumptions explicitly, and walk through the arithmetic rather than asserting a bare number. PostgreSQL stores user accounts, query history, and saved results, so professionals can revisit and export prior analyses, while authentication keeps each user's financial context private.

The project develops real skill in natural language interfaces for quantitative domains: prompt engineering for accuracy, structuring AI output so humans can verify it, and wrapping everything in a dependable, database-backed web application.

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