Automated Document Processing with Google Cloud Document AI

summary

Implemented several proof of concepts (PoC’s) for multiple clients across banking and insurance to automate manual service processes, including document classification, entity extraction, and document scanning, resulting in improved efficiency and accuracy.

goals

• Automate document processing in banking and insurance industries
• Improve accuracy and speed of document classification
• Enhance entity extraction from various document types
• streamline document scanning processes

key achievements

• Implemented proof of concepts with Document AI for multiple clients in banking and insurance
• Automated document classification and entity extraction with high accuracy rates for various document types
• Streamlined document scanning processes, reducing manual effort significantly

business impact

• Reduced processing time for document classification by up to 80% compared to manual processing
• Enabled faster decision-making in loan approvals and insurance claims
• Increased overall operational efficiency for document processing workflows

technical highlights

• Utilized Google Cloud Document AI for advanced document processing
• Implemented custom machine learning models for industry-specific document types
• Integrated Document AI with existing systems via API
• Ensured compliance with data privacy regulations in financial services

techstack

• Google Cloud Platform (GCP):
  • Document AI
  • Cloud Storage
  • BigQuery
  • Cloud Functions
• Python
• Docker

relevant links

• Google Cloud Document AI Overview
• Case Study: Document AI in Banking
• Whitepaper: AI in Insurance Document Processing