Optical Character Recognition
Experience AI-powered OCR precision
Purpose-built to extract and process data from thousands of different types of identity documents around the world, Incode’s proprietary Optical Character Recognition (OCR) technology ensures fewer data discrepancies, enhanced fraud detection, and global compliance.
What is OCR?
What is Optical Character Recognition (OCR)?
Optical Character Recognition (OCR) technologies for identity verification extract text from images of government-issued IDs and translate it into machine-readable data.
Key challenges
Where basic OCR falls short
Thousands of document types
Text readability
Language limitations & special characters
Tricky symbols
Confusing designs & similarities between different document types
Dependency on third-party developers
Challenging environmental conditions
Poor image quality
Thousands of document types
Text readability
Language limitations & special characters
Tricky symbols
Confusing designs & similarities between different document types
Dependency on third-party developers
Challenging environmental conditions
Poor image quality
Why accuracy matters
Risks for your business
Identity fraud
Misinterpreted credentials or failure to detect counterfeit or tampered identity documents can result in unauthorized individuals gaining access to systems, areas, and services, putting people and organizations at risk of being exposed to criminal activity or dangerous behaviour.
Misinformation
Incorrect or incomplete data extraction can spread misinformation, propagate errors, and disrupt business operations. Decisions made in response to analysis of defective data can harm your organization.
Regulatory breaches
When extracting data for compliance purposes —such as KYC (Know Your Customer) requirements in banking—, inaccuracies can result in regulatory breaches, litigation, and criminal penalties.
Disrupted business operations
Poorly interpreted data can require extensive manual review, which is time-consuming and costly. Errors in extracting data slow down business operations.
Poor UX & damage to reputation
Data processing errors can damage your organization’s reputation, result in user dissatisfaction and loss of trust, and attract negative media attention. Errors such as false rejections —when OCR technology incorrectly flags valid documents as invalid— can frustrate users. If the OCR process is slowed down by complex conditions, languages, and layouts, this can impact the user experience and increase drop-off rates.
Missed opportunities for global expansion
The inability to recognize non-Latin languages and updates to international identity documents can hinder opportunities to expand globally and reach international clients or customers.
Data leaks
Errors in data classification could expose sensitive data.
Our scalable solution
Incode OCR technology guarantees accuracy and scalability
Incode’s purpose-built proprietary OCR technology uses machine learning to capture, classify, and process data from over 4900 global identity documents with improved accuracy.
From capturing high-quality images in suboptimal conditions to parsing complex fonts, elements, and special symbols, our document-specific OCR pipelines are robust, scalable, and constantly evolving.
Purpose-built for global IDs
Recognizes complex fonts & elements
Built for global scalability
Ensures regulatory compliance
Works at lightning speed
Real-time feedback & image optimization
Full air gap solution
Stay one step ahead
User experience
Drive conversions and completion rates with our streamlined workflow
Our ML models handle all the heavy lifting, making every user interaction feel effortless. By delivering improved results —even in suboptimal conditions—, we save our users time and minimize the need for manual intervention.
Features such as smart frame selection, automatic ID orientation detection, and real-time feedback help to ensure our process is straight-forward and easy to navigate. By simplifying and speeding up the process, we boost completion rates and drive conversions.
Get to grips with the tech
How our OCR technology works
From capture to completion, this is our step-by-step guide to how Incode’s proprietary OCR technology uses machine learning to achieve improved accuracy during identity verification.
Step 1: ID Capture
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Performance metrics & bias analysis
Performance analysis
Our OCR technology achieves improved accuracy across various document types. It has been shown to outperform general-purpose OCR solutions in extracting and interpreting data from key fields such as name, address, birth place, document number, expiry date, and machine readable zones (mrz).
Bias analysis
We continuously review our model performance across different document types, languages, and visual conditions to minimize any biases in document recognition and improve overall performance.
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Experience faster, more reliable data extraction
Request a demo today and discover the power of our OCR solution.
