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Insurance teams spend a significant amount of time daily doing manual work with documents. They spend whole workdays doing Loss Run data entry, ACORD form validation, and sorting of underwriting submissions. While you're organizing that 50-page broker package, complex cases that need real underwriting attention get pushed aside. Upstage Studio takes the entire process through automation. You can upload any insurance document of any format and receive structured data that is ready for your systems. 👉 Explore Insurance Automation Agents in Studio Why Insurance Documents Are Hard to Automate
Carrier-Specific Formats Even the same document type looks completely different across carriers. Loss Run reports from Aurora, Aegis, and Travelers use different field names, table structures, and layouts. 'Incurred Amount', 'Total Incurred', 'Loss Amount'these are different names for the same thing, but each carrier employs different terminologies. Complex Tables Documents may be loaded with policy information, claim details, and payment history dividing them into numerous nested tables. The layout of tables keeps changing from one page to another. Sometimes the tables may even contain other tables. Conventional OCR simply cannot figure out these complex layouts. Poor Scan Quality Faxed documents, scanned wrinkled papers, and handwritten corrections still still arrive daily in insurance operations. ACORD forms, though standardized, often have handwritten entries that make automatic recognition very difficult. Blurry text, skewed scans, and stained backgrounds are common for all document types. Mixed Document Packages An underwriting submission is a single 50+ page PDF that usually contains ACORD forms, Loss Runs, questionnaires, and other supporting materials. To automate processing, you first need to identify which page is which document type before applying the right extraction method. Time Pressure Brokers want fast quotes. But sorting one submission package and entering data takes 15-20 minutes. Complex cases never get proper review, and profitable risks get missed. AI Workflow for Insurance Document Processing Upstage Studio processes all insurance documents through a 3-step workflow: Parse → Classify → Extract.
Parse: Extract All Information from Documents
Extract text, tables, and layout structure completely from uploaded documents. For insurance documents: Accurately reads blurry faxed Loss Runs Converts handwritten corrections on ACORD forms to text Captures complex nested table structures intact Extracts multi-page claim history tables without missing data
How it works: Select the Parse step in Studio and upload your documents. Most insurance documents work with default settings. Enhanced mode is available for severely damaged or extremely low-quality scans. Classify: Automatically Sort Document Types
Automatically categorize parsed documents by type. For insurance documents: 50-page mixed broker package → automatically sorted into "5 ACORD forms, 3 Loss Runs, 2 questionnaires" Correctly identifies all Loss Runs even when multiple carriers are mixed together 95%+ classification accuracy
How it works: Define document categories in the Classification schema. Create classes like "ACORD" and "Loss Run" with descriptions of each type's characteristics, and AI automatically classifies all uploaded documents based on these definitions. Extract: Pull Specific Data by Document Type
Extract required information from each classified document in structured format. Schema Mapping - The Key Feature: Apply different extraction schemas for each document type. ACORD forms → Apply Acordschema Extract agency information, applicant details, business lines, policy information, contact details Loss Runs → Apply Lossrunschema Extract carrier name, report date, policy information, complete claim history table
Auto-Generate Schema: Simply provide instructions like "extract carrier information and complete claim history table," and AI automatically generates the necessary JSON schema. You can also upload your existing schema if you have one. Standardization: Unify different field names across carriers into single keys. 'Incurred Amount', 'Total Incurred', 'Loss Amount' → all standardized to 'Incurred', converting any carrier's document into the same JSON structure. Enterprise Features for High-Volume Processing The 3-step workflow above is sufficient for individual users or small-volume processing. However, companies processing hundreds or thousands of documents daily via API need additional quality control and monitoring capabilities.
Validate Review and correct extracted data in real-time using table view. For high-volume processing, quickly verify samples to improve accuracy. When you correct values directly in table view, AI learns from these corrections and provides more accurate results in subsequent processing. Monitor Dashboard for tracking speed, stability, and accuracy when processing thousands of documents via API. For example, when processing 9,900 Loss Runs, monitor average processing time, success rate by step, and error count in real-time. API Deployment Deploy your Studio workflow as an API endpoint to integrate with existing underwriting systems or CRM. Export extracted data in JSON or CSV format. Results: From Unstructured to Structured
Aspect Manual Processing AI Automation
Document Sorting Manually review 50-page package one by one Auto-sorted (5 ACORD, 3 Loss Runs, etc.)
Data Entry Find fields in ACORD forms and manually type Automatic extraction and structuring
Table Processing Copy Loss Run tables to Excel manually Entire claim history table auto-extracted
Time Required 15-20 minutes Under 3 minutes
Accuracy High error potential 95%+ accuracy
Output Manually entered data System-ready JSON/CSV
Real-World Use Cases Underwriting Operations Automatically classify mixed broker submissions and extract necessary information from each document. Underwriters focus on risk analysis instead of data entry. Faster review of complex cases means quicker responses to brokers and more deal opportunities. Broker Intake Convert various document formats...
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