Intelligent Bank Statement Transcription and Data Extraction Workflow
This workflow aims to automate the processing of bank statements by downloading PDF files and converting them into images. It utilizes a visual language model to accurately transcribe text while preserving the table structure. Subsequently, a language model extracts key deposit detail data, enabling intelligent parsing and structured information extraction from complex documents. This process significantly enhances the efficiency of financial data processing and is suitable for users such as finance departments, auditors, and data analysts who need to quickly organize and analyze bank statements.
Workflow Name
Intelligent Bank Statement Transcription and Data Extraction Workflow
Key Features and Highlights
This workflow automatically downloads bank statement PDF files, converts each PDF page into images, and leverages advanced Vision Language Models (VLMs) to accurately transcribe the scanned or downloaded PDF content into Markdown-formatted text while preserving the original document’s tables and structural information. Subsequently, based on the transcribed text, a language model extracts key deposit detail data, enabling intelligent parsing and structured information extraction from complex scanned documents.
Core Problems Addressed
Traditional OCR technologies struggle to effectively process scanned PDFs, especially those containing tables and complex layouts. This workflow utilizes vision language models to achieve high-fidelity transcription of scanned PDFs, overcoming challenges such as difficulty in extracting text from scanned images, loss of structural information, and insufficient data accuracy. Additionally, it automates the extraction of deposit entries, significantly enhancing the efficiency of financial data processing.
Application Scenarios
- Automated processing of bank statements by finance departments or individuals for rapid organization and analysis of deposit transactions
- Scenarios requiring parsing of scanned or downloaded bank statements
- Any document automation tasks involving extraction of structured data from scanned PDF documents
- Intelligent document processing needs in financial services, auditing, data analytics, and related industries
Main Workflow Steps
- Download Bank Statement PDFs: Retrieve sample or real bank statement files via the Google Drive node.
- Convert PDF Pages to Images: Use the third-party Stirling PDF service to convert each PDF page into high-resolution JPG images (custom service replacement supported).
- Unzip Image Files: Extract the returned ZIP archive and organize the images into a list.
- Sort and Resize Images: Sort images by filename and reduce their size to optimize subsequent model processing speed.
- Vision Language Model Transcription: Employ the Google Gemini vision language model to transcribe image content into Markdown text, preserving tables and text structure.
- Merge Transcribed Texts: Combine the transcription from all pages into a single unified document.
- Key Data Extraction: Use a language model with predefined prompts to extract all deposit table rows, outputting structured data fields (date, description, amount).
Involved Systems and Services
- Google Drive: File storage and download
- Stirling PDF Webservice: PDF-to-image conversion service (supports self-hosted alternatives)
- Google Gemini Chat Model (PaLM API): Vision language model for transcription and data extraction
- Built-in n8n Nodes: File unzipping, sorting, image processing, code execution, data aggregation, etc.
Target Users and Value
- Finance professionals and auditors requiring automated processing and analysis of bank statements
- Data analysts and developers focused on document digitization and structured information extraction
- Enterprises or individuals aiming to reduce manual data entry costs and improve scanned document processing efficiency
- Users with high data privacy requirements can flexibly replace the PDF conversion service to enable secure local processing
By integrating multiple automation and AI technologies, this workflow delivers an end-to-end intelligent solution for transforming scanned PDFs into structured financial data, serving as a powerful tool for financial digital transformation and intelligent document parsing.