My Bank Wanted $17.63 so I Used Python Instead.

Introduction

This tutorial demonstrates how to automate the retrieval of credit card statements using Python, highlighting a solution to avoid unnecessary bank fees. By leveraging web requests and Python libraries, you can efficiently gather your financial data without relying on your bank's cumbersome procedures.

Chapter 1: Understanding the Problem

• You need access to credit card statements for tax purposes but cannot retrieve them easily due to:
  • The closure of your credit card account.
  • Limited access on the bank's desktop client.
  • The mobile app displaying statements one at a time, making it time-consuming.
• The bank charges $17.63 for printing the statements, prompting the desire to find an alternative solution.

Chapter 2: Setting Up Your Environment

• Use Charles Proxy to intercept web requests from your mobile app:
  • Download and install Charles Proxy on your Mac.
  • Connect your smartphone to the same Wi-Fi network as your Mac.
  • Configure your smartphone to use Charles as a proxy.
• Start capturing network requests while navigating to the credit card statements page in the mobile app.
• Review the captured requests to identify the URLs and parameters necessary for retrieving the statements.

Chapter 3: Analyzing the Network Requests

• Examine the response data from the network requests:
  • Note that the bank's app fetches all statements in a single request, but displays them in a paginated interface.
  • Recognize this as a "dark pattern" designed to discourage easy access to your data.

Chapter 4: Using Python to Automate Retrieval

• Use Python to programmatically retrieve your statements:
  • Save the response from Charles Proxy as a .json file for reference.
  • Install the requests library if you haven't already:

    pip install requests
    

  • Create a Python script that executes the following:

    import requests
    import time
    
    # Load your JSON data and extract necessary URLs and headers
    url = "YOUR_STATEMENT_URL"
    headers = {
        "Authorization": "Bearer YOUR_ACCESS_TOKEN",
        # Add any other required headers
    }
    
    for i in range(NUMBER_OF_STATEMENTS):
        response = requests.get(url, headers=headers)
        with open(f'statement_{i}.pdf', 'wb') as file:
            file.write(response.content)
        time.sleep(1)  # Pause to avoid overwhelming the server
    

  • Replace YOUR_STATEMENT_URL and YOUR_ACCESS_TOKEN with the appropriate values from your captured requests.
  • Adjust NUMBER_OF_STATEMENTS based on how many statements you want to download.

Chapter 5: Exploring Additional Open Source Tools

• Consider using open-source projects that convert bank statements to CSV format:
  • Search GitHub for repositories related to bank statement parsing.
  • Review and test projects, keeping in mind that some may require modifications to work with your specific bank.

Chapter 6: Understanding the Bank's Pricing Strategy

• Recognize why banks charge for statements:
  • The fee is set at a price point where customers are likely to pay rather than pursue alternatives.
  • This reflects a broader strategy to monetize services that should be accessible to customers.

Conclusion

By following this guide, you can automate the retrieval of your credit card statements using Python, saving both time and money. Exploring additional open-source tools can enhance your financial data management. If you're interested in similar projects or need further assistance, consider reaching out for more tutorials. Happy coding!