Casca Project

Financial Document Analysis for Loan Eligibility

This project processes financial documents (e.g., bank statements) to evaluate loan eligibility using OpenAI's GPT-4 model (gpt-4o). The workflow includes converting PDF files into images, organizing them into folders, and analyzing the data using GPT-4 along with a custom text prompt.

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Features

• PDF to Image Conversion:

  • Converts each page of a PDF document into high-resolution images.
  • Stores the images in separate folders, with one folder per PDF.

• Custom Financial Analysis:

  • Sends the images to OpenAI's gpt-4o model for analysis.
  • Includes a custom text prompt to extract key financial insights:
    • Total monthly deposits and withdrawals.
    • Identification of recurring expenses (e.g., rent, employee salaries, utilities).
    • Detection of outstanding loans or liabilities.
    • A final evaluation of loan eligibility based on spending patterns and financial health.

• Automated Workflow:

  • Handles multiple PDFs and folders seamlessly.
  • Encodes images into base64 for efficient transfer to the GPT model.

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Workflow

1. PDF Processing:

   • Input: A folder containing one or more PDF files.
   • Output: Each PDF is converted into a folder containing images of its pages.

2. Image Preprocessing:

   • Converts images to grayscale and applies thresholding to enhance text readability.
   • Prepares the images for OCR and GPT processing.

3. GPT Analysis:

   • Encodes images into base64 format and sends them to gpt-4o.
   • A custom text prompt guides GPT to extract financial insights and make loan recommendations.

4. Output:

   • A detailed report for each PDF, including:
     • Monthly cash flow summary.
     • Key recurring expenses.
     • Loan eligibility decision and reasoning.

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Prerequisites

• Python 3.12 or later.
• OpenAI API Key with access to gpt-4o.
• Required Python libraries