AI Financial Document Parser & Report Generation System

Overview

The AI Financial Document Parser & Report Generation System is a full-stack platform designed to automate the processing and analysis of financial documents. It helps transform unstructured financial documents into structured, validated data that can be reviewed, analyzed, and exported through a centralized dashboard.

The system supports multiple financial document types, including bank statements, Income Tax Returns (ITRs), GST returns, invoices, salary slips, and financial statements.

Document Processing Pipeline

The platform follows a structured processing workflow:

Document Upload → Classification → Data Extraction → Validation → Manual Review → Reporting

This pipeline helps reduce manual effort involved in reviewing and processing financial documents.

Key Features

📄 Multi-Format Financial Document Processing

The system is designed to process different types of financial documents, including:

Bank Statements
ITR Documents
GST Returns
Invoices
Salary Slips
Financial Statements

🤖 Intelligent Document Classification

A deterministic, rule-based classification system identifies the type of uploaded financial document and routes it to the appropriate extraction workflow.

🔍 Data Extraction

The system extracts relevant financial information from documents using:

PDF text extraction
OCR for scanned documents
Pattern and regex-based extraction
Document-specific extraction rules

Tesseract OCR, PyPDF2, and pdf2image are used as part of the document-processing pipeline.

✅ Data Validation

Extracted information is validated against predefined rules to identify inconsistencies, missing information, and potentially incorrect values.

The validation layer helps ensure that extracted financial data is reliable before it is used for reporting and analysis.

👤 Manual Review

Documents or extracted fields requiring additional verification can be reviewed manually, providing a human-in-the-loop workflow instead of relying entirely on automated extraction.

📊 Dashboard & Analytics

The application provides dashboards for viewing processed documents and extracted financial information, making it easier to monitor document-processing activities and analyze results.

📑 Report Generation

Processed data can be exported into different formats for further analysis and record keeping, including:

PDF
Excel
CSV

📝 Audit Logs

The system maintains audit information to help track document-processing activities and provide better transparency over changes and operations.

Technology Stack

Frontend

React.js
Vite
Tailwind CSS

Backend

Python
FastAPI
SQLAlchemy

Database

PostgreSQL / SQLite

Authentication & Security

JWT Authentication
bcrypt password hashing

Document Processing

Tesseract OCR
PyPDF2
pdf2image
Regex-based extraction

Report Generation

ReportLab
openpyxl
CSV generation

Deployment

Docker
Docker Compose

Architecture

The application follows a full-stack architecture where the React frontend communicates with the FastAPI backend through APIs. The backend manages authentication, document processing, extraction, validation, database operations, and report generation.

The modular architecture makes it possible to extend the system with additional document types and extraction rules.

My Contribution

I developed the system across the frontend and backend, including the document-processing workflow, API integration, authentication, database operations, extraction and validation logic, dashboards, reporting functionality, and audit mechanisms.

Outcome

The project demonstrates how document-processing automation, OCR, structured extraction, validation, and analytics can be combined into a practical financial document management system.

It provides a structured workflow for converting financial documents into usable data while retaining validation, manual review, reporting, and auditability.