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Evaluate loan applications and borrower profiles with their overwhelming piles of complex documents in minutes to enable intelligent, data-driven, and instant underwriting decisions. Cut cycle times, reduce financial risk, and improve the borrower experience.
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Insurers and loan providers relying on traditional ways of underwriting face significant challenges and can start a negative spiral that is difficult to reverse.
Data intake from third-party or multiple sources requires a rigorous amount of cleanup and is often neither reliable nor aligned with set standards, even after validation.
Anywhere from 30 to 40 percent of underwriting time is spent on administrative, non-value-added manual tasks.
Notorious, error-prone, and inconsistent underwriting leaves affluent clientele demanding fast-change coverage with frustrating experiences.
Legacy systems’ inability to consolidate financial data across programs makes it difficult to enable informed risk assessment and effective decision-making.
Collatio Underwriting is Scry AI’s platform that utilizes context-based data parsing and AI-driven risk recognition to process and evaluate document-heavy loan files for faster, more accurate underwriting. It automates the classification of loan-related documents and extracts borrower, asset, collateral, and financial data with precision. The platform then links and reconciles information across documents to surface validated insights for rapid, standards-driven underwriting decisions.
Collatio Underwriting optimizes document-heavy lending workflows to support faster, more accurate credit decisions.
Collatio ingests financial documents from third-party and internal sources across multiple channels and preprocesses and cleans the data for downstream use. It applies advanced OCR, NLP, and machine learning techniques to identify critical data elements, extract them with high accuracy, and convert unstructured loan documents into structured, actionable information. The system interprets the context behind each field rather than treating data as isolated text and delivers high-quality information for underwriting.
The platform links and reconciles extracted data against relevant records, including purchase orders, contracts, and statements, to ensure consistency and completeness across loan files. Any discrepancies, such as duplicate entries, mismatched values, irregular ratios, or missing items, are automatically flagged for review.
Loan files and their associated data move through classification, extraction, and reconciliation, with integrated risk evaluation and automated checks. The platform uses predictive modeling and pattern recognition to assess borrower risk, analyze credit history, and verify the authenticity of assets, collateral, and financial information. It provides actionable insights to underwriters, enabling accurate assessment of repayment capacity, reducing bias, and supporting accelerated underwriting.
Dashboards and analytical reports provide lenders with key insights, including financial summaries, efficiency metrics, pipeline status, and visibility into funded files. Underwriters can assess collateral, credit, character, capital, and capacity using policy-aligned views that centralize supporting documents to ensure consistent decisions.
The system can easily integrate with internal and external financial systems, allowing underwriting data to flow directly across workflows without redundant reentry. It standardizes how data is organized and presents lenders with a complete borrower profile. As a result, loan-closure cycles move faster, and borrowers receive consistent decisions, timely updates, and clear documentation.
Organizations using Collatio Accounts Receivable Automation Software consistently see measurable improvements across speed, accuracy, and collections predictability.
Data-Extraction Accuracy for high-fidelity loan files
Reduction in Manual Administrative Tasks, including document review & data entry
Faster Underwriting Turnaround with structured, validated, decision-ready data
Document Types Supported with Multi-Language Capability
Loan package documents enter the system through portals, LOS platforms, email, SFTP, or internal data feeds. The pipeline accepts structured, semi-structured, unstructured, and handwritten files from internal and third-party sources.
The system identifies each document in the loan package and applies structured indexing metadata. It recognizes loan applications, W-2s, 1099s, paystubs, tax transcripts, appraisal reports, title documents, credit files, bank statements, and other underwriting documents.
AI models capture borrower details, income data, collateral attributes, property information, and other underwriting-critical fields across all document formats. They interpret the context of each field rather than treating it as an isolated field, using OCR, NLP, and machine learning to convert unstructured content into structured, high-quality data for downstream underwriting.
Extracted data is linked and compared across the loan file to validate consistency. Income values are matched against bank statements, property details are verified against appraisals and title documents, and identifiers such as SSN, employer information, and liabilities are checked for accuracy. Any mismatches or irregular patterns are automatically flagged.
Validated, reconciled data flows directly into underwriting systems, decision engines, and downstream workflows. The output includes structured fields, contextual insights, and reconciliation results, which support decision-making and give underwriters the clarity they need to move faster with confidence.
The system maintains field-level lineage, document version history, and comprehensive audit trails to provide end-to-end transparency. It supports regulatory examinations with verifiable and validated data, and ensures underwriting decisions are consistently backed by clear, review-ready evidence.
Collatio Underwriting supports a wide range of loan-related documents across structured, semi-structured, unstructured, and handwritten formats.
Collatio applies rigorous security controls and adheres to lender-required regulatory standards across every workflow. It protects sensitive loan data, enforces governance, and ensures each file is processed with audit-ready integrity.
Role-based access, encryption, audit logs, and adherence to ISO 27001, SOC 2, and financial services controls.
Validation rules, credit-policy checks, and lender-specific workflows ensure decisions remain consistent.
Every extracted field, document version, and decision pathway is traceable for regulators and auditors.
We are trusted by enterprises globally.
Connect with your existing enterprise platforms through APIs and direct data exchange, keeping your workflows intact and your teams in sync.
Accelerate underwriting with AI-driven classification, extraction, and reconciliation across income, identity, property, and loan documents for faster, more accurate credit decisions.
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