document-understanding
2023.4
false
- Overview
- Document Understanding Process
- Quickstart tutorials
- Framework components
- ML packages
- Overview
- Document Understanding - ML package
- DocumentClassifier - ML package
- ML packages with OCR capabilities
- 1040 - ML package
- 4506T - ML package
- 990 - ML Package - Preview
- ACORD125 - ML package
- ACORD126 - ML package
- ACORD131 - ML package
- ACORD140 - ML package
- ACORD25 - ML package
- Bank Statements - ML package
- Bills Of Lading - ML package
- Certificate of Incorporation - ML package
- Certificate of Origin - ML package
- Checks - ML package
- Children Product Certificate - ML package
- CMS 1500 - ML package
- EU Declaration of Conformity - ML package
- Financial Statements - ML package
- FM1003 - ML package
- I9 - ML package
- ID Cards - ML package
- Invoices - ML package
- Invoices Australia - ML package
- Invoices China - ML package
- Invoices India - ML package
- Invoices Japan - ML package
- Invoices Shipping - ML package
- Packing Lists - ML package
- Passports - ML package
- Payslips - ML package
- Purchase Orders - ML package
- Receipts - ML Package
- Remittance Advices - ML package
- Utility Bills - ML package
- Vehicle Titles - ML package
- W2 - ML package
- W9 - ML package
- Other Out-of-the-box ML Packages
- Public Endpoints
- Hardware requirements
- Pipelines
- Document Manager
- OCR services
- Deep Learning
- Document Understanding deployed in Automation Suite
- Document Understanding deployed in AI Center standalone
- Licensing
- Activities
- UiPath.Abbyy.Activities
- UiPath.AbbyyEmbedded.Activities
- UiPath.DocumentProcessing.Contracts
- UiPath.DocumentUnderstanding.ML.Activities
- UiPath.DocumentUnderstanding.OCR.LocalServer.Activities
- UiPath.IntelligentOCR.Activities
- UiPath.OCR.Activities
- UiPath.OCR.Contracts
- UiPath.OmniPage.Activities
- UiPath.PDF.Activities
Document Understanding User Guide
Last updated Dec 18, 2024
FM1003 - ML package
The Uniform Residential Loan Application Form 1003 is the standard form nearly all mortgage lenders in the United States use to collect information on borrowers about their finances, the property type, and its value.
The model is trained to identify and extract up to 71 fields and 49 items containing all kinds of data relevant for the mortgage application process.
The model automatically detects data such as:
- Borrower Name, SSN, Date of Birth, Citizenship,
- Type of Credit, Other Borrowers Applying for this Loan, Martial Status, Dependents, Contact Information,
- Current Employment Info: Business Name, Address, Phone, Position/Title, Start Date, Period Employed, Monthly Income,
- Assets: Account Type, Financial Institution, Account Number, Cash or Market Value,
- Loan Originator Name, Address, NMLSR ID#.
Note: For the complete list of extracted fields, check the Out-of-the-box Models Details file.
You can download the a sample filled-in form from here.
You can also preview the sample of a filled-in form:
