Industry: Financial Services
Solution Type: On-Premise OCR & Identity Verification
Technology: AI / ML
Project Overview
A leading life insurance company aimed to streamline ID verification by automating data extraction and validation from government-issued documents. The existing process was manual, slow, and prone to errors, creating operational bottlenecks.
Our team implemented a Proof of Concept (POC) on-premise OCR solution, capable of handling multiple Indian government IDs and integrating face-matching for reliable identity verification.
Objectives
- Automate high-priority compliance workflows involving ID verification
- Extract data from multiple Indian government-issued documents with high accuracy
- Integrate face-matching for reliable identity verification
- Ensure full compliance with regulatory and internal security protocols
Scope of the Project
- Operational Capacity: 200 documents per day, 6,000 documents per month
- Processing Volume: Up to 5,000 document pages during the POC
- Workflow: One page at a time, processing government-issued IDs
- Supported Input Formats: Base64, PDF, JPEG, PNG
- Supported Output Formats: JSON, XML
Solution Highlights
Advanced OCR
Automated extraction from Aadhaar Card, PAN Card, Passport, Voter ID, Driving License, and GST Invoice.
Face Matching Integration
Ensures reliable identity verification by comparing extracted data with user images.
Accuracy
Achieved 95.23% accuracy, significantly reducing errors from manual processes.
On-Premise Deployment
Compliant with all internal IT and regulatory security protocols.
Process Automation
Replaced manual verification workflows, reducing operational overhead.
Technical Approach
Multi-ID OCR Models
Trained AI models to recognize text and patterns across multiple Indian ID formats.
Face Verification
Integrated AI-powered face matching to confirm the authenticity of IDs.
Single-Page Processing
Designed for sequential, one-page-at-a-time processing for reliability during POC.
Flexible Data Handling
Supported multiple input and output formats for seamless integration with existing systems.
Business Impact
Reduced Manual Effort
Replaced manual verification with automated extraction and validation.
Improved Accuracy
Minimized errors in ID verification, ensuring compliance and reliability.
Scalable Framework
Laid the foundation for scaling to high-volume operations post-POC.
Enhanced Compliance
Fully on-premise deployment ensured adherence to regulatory and organizational security protocols.
Conclusion
The OCR proof of concept demonstrates the potential of AI-driven, on-premise document processing to streamline compliance-heavy workflows. By combining advanced OCR with face-matching, the solution delivers high accuracy, operational efficiency, and secure identity verification across multiple government-issued documents.