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SMART CATCHER is CRIF’s AI-powered document intelligence solution for financial institutions and insurance companies, available as an advanced capability of CRIF ORCHESTRA. It automates document classification, data extraction, and quality checks across multiple document types, supporting digital onboarding and lending processes. The solution also helps detect document tampering and data inconsistencies before information enters the credit workflow, improving data quality and reducing risk.
Document intelligence for faster, safer digital onboarding
Financial institutions and insurance companies rely on customer documents to support digital onboarding, lending, underwriting, and compliance processes. As document fraud and manipulation become increasingly sophisticated, organizations increasingly need automated document verification and fraud detection capabilities. SMART CATCHER uses AI-powered document processing, verification, and anti-tampering capabilities to detect inconsistencies early, automate document-intensive lending processes, and support compliance requirements, including Asset Quality Reviews.
SMART CATCHER is designed for:
Explore real-world scenarios where SMART CATCHER helps organizations detect risks, uncover insights, and make smarter decisions.
SMART CATCHER automates document processing and verification across customer onboarding and business workflows. It classifies files, separates multiple documents contained in a single upload, extracts key data from structured and unstructured formats, assesses document quality, and flags potential manipulation before information enters operational processes.
SMART CATCHER combines multiple layers of analysis to identify potential document manipulation. AI models examine visual artifacts, such as compression, noise, and copy-and-paste traces, while metadata analysis identifies signals including editing software, creation and modification dates, and PDF layers. Document data is also checked for logical, formal, and calculation inconsistencies, such as invalid IBAN or VAT formats, salary discrepancies, and mismatches between vehicle details and VIN data. Specialized models can also identify patterns associated with AI-generated or AI-modified images and documents.
SMART CATCHER handles documents captured in a wide range of real-world conditions, including folded or warped pages, rotated documents, smartphone captures, low or uneven lighting, blurred images, and different layouts of the same document type. It combines CRIF’s proprietary AI with state-of-the-art OCR, large language models, expert rules, and task-specific optimization.
Beyond anti-tampering, SMART CATCHER supports the full document lifecycle, from acquisition and quality assessment to automated classification, data extraction, and fraud signal generation. By detecting potential inconsistencies earlier and automating document-intensive activities, it helps reduce manual intervention and document-related back-and-forth, accelerate processing, and improve the overall digital onboarding experience.
SMART CATCHER can be integrated through APIs or orchestrated within broader digital onboarding and customer management environments alongside identity verification, Anti-Money Laundering (AML) and Know Your Customer (KYC) checks, digital signatures, and other process capabilities.
SMART CATCHER is designed to support financial institutions and insurance companies operating in regulated contexts. It aligns with ISO 27001 security standards, is supported by group-wide data protection governance structures, and is built to evolve alongside financial services and AI regulatory frameworks.
CRIF combines data, analytics, artificial intelligence, and fraud intelligence to help financial institutions and insurance companies address evolving document and digital fraud risks. Its ecosystem brings together more than 40 data sources and over 100 advanced algorithms, supported by continuous fraud and cyber intelligence observatories that analyze millions of fraud and cyber alerts every year.
Discover how SMART CATCHER can help detect document inconsistencies earlier and accelerate digital onboarding