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Automate Document Processing with Quick Automate and the IDP Accelerator
A mid-size mortgage lender automates its entire document intake pipeline using AWS solutions, significantly reducing processing time and errors.
AS1 NewsSource: aws.amazon.com
Mortgage lending relies heavily on document processing, which involves classifying, extracting, and validating large volumes of documents such as earnings statements, W-2s, and insurance applications. This process is resource-intensive and can cause delays, especially during peak periods. To address this, a typical mid-size lender can leverage AWS's GAIIC IDP Accelerator and Amazon Quick Automate to automate the entire pipeline.
The GAIIC IDP Accelerator is a serverless, open-source pipeline that uses Amazon Textract and Amazon Bedrock foundation models to convert documents into machine-readable text, classify them, extract structured data, and flag anomalies for review. It scales automatically with volume and charges only for processed documents.
Complementing this, Quick Automate provides a visual workflow builder and AI assistant to route extracted data to downstream systems, trigger verification checks, flag incomplete packages, and assign review tasks without custom coding. This orchestration reduces manual effort, errors, and processing time.
For example, Summit Mortgage, a fictional mid-size lender processing about 50,000 loans annually, reduced their document processing time from 15–20 minutes to under 6 minutes per file, with significant error reduction and capacity to handle peak volumes without additional staffing. The solution is adaptable to various document types beyond mortgages, including refinancing and commercial loans.
The combined AWS solutions are available today, with deployment guided by a comprehensive workshop. They offer a scalable, cost-effective approach to automating document-intensive operations, improving efficiency and borrower experience.
The deployment of AWS's AI solutions streamlines mortgage document processing, reducing cycle times and errors, and enabling scalable operations.