Project Title: Integrated Life-Event Financial Model (ILEFM)
Objective: To create a unified financial intelligence system that manages high-variance outflows (Medical & Marriage) against fixed income/savings while on the bench.
1. The Requirement: Data Collection & Mapping
He must identify and categorize every data source before any analysis begins.
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Medical Stream: Hospital bills, pharmacy receipts, diagnostic charges, and health insurance claim statuses.
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Marriage Stream: Venue deposits, vendor quotes, and estimated future liabilities.
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Fixed Stream: Bangalore PG rent, utility bills, and Bhopal-Bangalore travel logistics.
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Inflow Stream: Salary (if any), interest income, and existing corpus.
2. The AI-Task: “The Intelligent Audit”
Ask him to perform the following using AI tools:
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Automated Categorization: Use ChatGPT (Advanced Data Analysis) or Claude to ingest his bank CSVs and auto-tag transactions based on a custom taxonomy (e.g., “Health,” “Wedding-Capital,” “Living-Essentials”).
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Predictive Scenario Modeling: Use AI to answer: “If Medical Expenses exceed the estimate by 15%, what is the impact on the Marriage budget for Q4 2026?”
Phase 1 Task for the Analyst: “The Discovery Memo”
Goal: He needs to define the problem before he looks for the solution.
Instructions for him: “I want you to act as a Consultant. Before you touch a spreadsheet, provide a Discovery Memo that includes:”
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Entity-Relationship Diagram (ERD): A simple map showing how his bank accounts, UPI apps, and cash interact with his major expense ‘buckets’ (Medical, Marriage, PG).
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Gap Analysis: What data is currently missing? (e.g., ‘I don’t have the final quote for the wedding caterer yet’).
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Tool Stack Proposal: A list of which AI tools he will use to ensure this is an automated system, not just a manual log.
| Category | Tool | How he should use it |
|---|---|---|
| Data Cleaning | ChatGPT/Claude | Uploading bank PDFs/CSVs to extract and clean “messy” data into a table. |
| Smart Sheets | Rows.com | An AI-spreadsheet that can pull live data and run AI functions natively. |
| Forecasting | Julius AI | For “What-If” scenarios regarding medical cost overruns. |
| Market Research | Perplexity AI | To benchmark wedding costs and medical recovery services in Bangalore |