AIApplied AI World
Beginner45 min

Build a Credit Card Statement Analyzer in 45 Minutes

Use Cursor AI and Python to parse PDF statements, categorize transactions, and surface spending insights.

#python#cursor#finance#pdf

Companion Video

What you’ll build

A Python script that reads credit card statement PDFs, extracts transactions, categorizes spending, and prints a summary report. Perfect for understanding where your money goes.

Prerequisites

  • Cursor installed
  • Python 3.10+
  • A sample credit card statement PDF (redact sensitive info)
1

Set up your project

Create a new folder and open it in Cursor:

mkdir statement-analyzer
cd statement-analyzer
cursor .

Ask Cursor to create a requirements.txt with pypdf, pandas, and python-dotenv.

2

Extract text from the PDF

Create extract.py and prompt Cursor:

Write a function that reads a PDF file path and returns all text content using pypdf.

Test with your sample statement:

python extract.py sample-statement.pdf
3

Parse transactions with AI

Paste a chunk of extracted text into Cursor and ask:

Parse this credit card statement text into a list of transactions with date, description, and amount. Return as JSON.

Save the parsing logic in parse.py.

4

Categorize and summarize

Add simple category rules (groceries, dining, transport) or ask Cursor to classify merchants. Build a summary:

# Example output
# Groceries:    $342.18
# Dining:       $189.50
# Transport:     $67.00
5

Run the full pipeline

Wire everything together in main.py:

python main.py sample-statement.pdf

You should see a categorized spending breakdown in your terminal.

Next steps

  • Export results to CSV
  • Add month-over-month comparison
  • Build a simple Streamlit dashboard

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