Automated document processing & forgery detection
Verify documents at scale and get comprehensive insights beyond simple trustworthiness.
Automated forgery and fraud detection
Effortlessly identify forged identity documents, fake bank statements, and manipulated invoices with our advanced, adaptable fraud detection system that covers various fraud types and comprehensively analyzes content and metadata.
Preempt fraud with profiling
Fraudsters commonly employ tactics such as blurriness, poor image quality, and flash reflections to disguise alterations on documents. Optical Character Recognition (OCR) systems are most effective with sharp, pristine documents. Therefore, within a mere three seconds of receiving a document, any unsuitable ones are promptly discarded.
Fraudsters manipulate document clarity to hide alterations
OCR systems quickly discard unsuitable documents
Quick document forensics analysis
Fraudsters are often using low-resolution and blurred images as well as flash reflections to hide document tampering. That's why our OCR technology is optimized for clean, unaltered documents.
Unsuitable documents are identified and discarded within three seconds of receipt.
OCR technology optimized for unaltered documents
Rapid identification of unsuitable documents
Quick discarding process within three seconds
Smart Document Processing
Our AI discerns unique issuer document traits for tailored processing, enabling auto-approval from specific issuers, preference for photos over scans, or routing to the most proficient OCR.
For new document types, our AI only needs 50-80 samples to be ready for tampering detection.
Tailored document processing
Optimal OCR routing
Quick learning for new formats
Advanced Document Verification Features
Ensure the document's origin using advanced features like logo detection for authenticity. Our anomaly detection assesses over 500 attributes, including those indiscernible to the human eye.
Verify a document's origin
Detect logos for authenticity
Evaluate 500+ hidden traits
Comprehensive historical analysis for fraud prevention
Cross-reference new documents with historical data for fraud detection. This effectively combats serial fraud, identifying repeat documents from diverse sources, indications for template farms, or metadata suggesting a singular origin of multiple PDF uploads.
Document cross-reference for fraud
Single-source upload identification
Identifying template farms via similar alterations
Streamline your regulatory compliance efforts
Streamline, cumulate and enhance your compliance measures to comply with KYC requirements and deliver a stellar customer onboarding experience.