ai budget tracker

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AI Financial Coach: Budget & Savings Predictor

Project Overview

This project implements a next-generation personal finance application that transforms historical transaction data into proactive, personalized financial advice using a continuous four-step AI/ML cycle: Collect, Analyze, Predict, and Recommend (CAPR).

The goal is to provide users with a "Financial Co-pilot" that helps them achieve specific savings goals and avoid unexpected budget shortfalls.

1. The AI Cycle Architecture (CAPR)

Phase

Description

Key Metric / Output

Underlying Technology (Simulated)

Collect

Data Ingestion & Cleaning: Securely import or manually input all user transactions (income, expenses, transfers).

Cleaned, normalized data set; 98% Auto-Categorization Rate

Python (Pandas), NLP for transaction description clustering (e.g., using simulated scikit-learn text embeddings).

Analyze

Descriptive Analytics: Understand current spending habits, identify trends, fixed/variable costs, an