The Truth in Lending Disclosure Statement document skill is a pre-trained AI model for ABBYY Vantage, that extracts data from Truth-in-Lending disclosure statements (also known as Truth in Lending, TIL, The Truth in Lending Statement, TILA disclosure), which are reports that contain information (preliminary or final) about a mortgage loan, specifically - information about the lender, borrower, interest rate, monthly payments, and settlement fees.

The Truth in Lending Disclosure Statement skill is a preview skill. It has been trained on a small document set and is intended to be used by citizen developers as a quick-start basis for processing Truth-in-Lending disclosure statements. The skill may require further training on your specific documents in order to be used in production scenarios.

• Vantage document skills are extraction models, based on ABBYY's purpose-built AI, designed and trained to extract key data from business documents.
• Preview document skills provide a quick-start basis for conducting proof of concept and automating document-centric processes, without wasting time to train a new skill from the ground up. In most preview skills the main data fields have been labeled and the skill has been trained on a small document set to provide a starting point for further training on customer side. Preview skills generally come at no additional cost, but consume page volume from the base Vantage Core Skills volume.
• The AI model automatically detects key fields on TIL documents and extracts relevant data (type of TIL, date, loan number, lender name, borrower name, property address, amount financed, APR, finance charge etc.). For a full list of extracted fields, please see the skill documentation.
• Includes validation and data normalization rules. Further business rules can be added as required.
• Can be augmented by human-in-the-loop review and verification based on accuracy thresholds, missing or incorrect information.
• Requires further training in order to ensure sufficient accuracy levels on customer-specific documents. Training can be done up-front or during runtime as documents arrive and go through manual verification.