Post-Closing of mortgage loans involves a multitude of processes and tasks across lenders, brokers and investors. At this stage the closed loan is monitored to ensure all trailing documents are gathered and processed to meet all investor guidelines for loan saleability.
Over the last 3 years we have optimized our digital platform to transform post close processes. If your goal is to streamline retrieval, processing and upload of trailing documents so your staff can focus on high value activities, we have the right solution for you. Our post-closing solution combines the right technology, tools and people to help you achieve your objectives. The platform supports open API architecture which enables us to integrate with any up/downstream systems.
Input
Metadata can be input through our predefined excel, xml schema or APIs. Mandatory field: Loan Number
Loan packages / images can be sent as physical copy to our office, store in a secure SFTP which we can access or sent over APIs
Output
Classified documents in the closing package will be provided as individual pdf's by number of instances
Consolidated closing package sorted to your requirement with bookmarks for each document
Data fields extracted for individual documents or as a consolidated document
Shipping of trailing documents to custodians
The output can be customized to any requirement. We can upload it to any SFTP location or integrate with your system through APIs.
Highlights
Document Recognition / Data Extraction platform for Origination and Post-Closing workflows
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
You pay based on the number of mortgage loans processed, so cost scales with volume. Two usage dimensions set the scope of work per loan. The Classification dimension charges per loan for sorting and identifying document types. The Classification and Data Extraction dimension charges per loan and adds pulling structured data from those documents. Both are billed by loan units, letting you choose the depth of document processing you need. This ML-powered document engine handles mortgage document types across the loan lifecycle.
Top-of-mind questions for buyers
What counts as one loan unit for billing?
Each mortgage loan you run through the platform counts as one unit, regardless of how many documents that loan contains. The engine processes all document types in the loan lifecycle. Your cost scales with the number of loans, not the page count or document count within each loan.
How do the Classification and the Classification and Data Extraction dimensions differ mechanically?
Classification sorts and identifies each loan's document types only. Classification and Data Extraction does that plus pulls structured data fields from those documents. Both bill per loan unit. You pick the depth you need per loan; the Data Extraction option covers more processing work in a single charge.
Do both dimensions bill together, or do I pick one per loan?
Each dimension bills independently by loan unit. You choose the scope of processing you need. The Classification and Data Extraction dimension already includes classification work, so you do not need to combine it with the standalone Classification dimension for the same loan.
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