Paradatec, Inc.’s new WriteUCD module was recently certified by Fannie Mae as meeting their requirements for producing valid Uniform Closing Dataset (UCD) files. This new module leverages Paradatec’s Optical Character Recognition (OCR) solution for the mortgage market to extract data from Closing Disclosure (CD) documents and then format that data in the MISMO standard required by Fannie Mae. The certification process required submitting test UCD files for multiple lending scenarios for Fannie Mae’s review, with all tests being passed successfully.
According to Neil Fraser, Paradatec’s Director of US Operations, “Developing this new module was an easy decision for us. Many clients are already using our solution to extract data from the TRID documents to support certain internal review and audit procedures, so since we have the logic to extract this data it made sense to create a module which formats this data per the UCD specification. Now that we’ve attained certification with Fannie Mae, our clients who work with them are assured of complying with their September 2017 UCD requirement with this new WriteUCD module.”
Paradatec also announces the release of their new AuditUCD module for auditing UCD file content against the Closing Disclosure contained in the UCD file. Fraser continues, “Again, developing this module was a logical extension to our mortgage solution. Since we’re able to build the UCD file from extracted Closing Disclosure data, it’s just as easy for us to unpack a UCD file’s content to compare the individual data elements against the values extracted from the submitted CD to verify the integrity of both components in the UCD file. Any elements that don’t match will be flagged in our XML output for further review and resolution. Given the volume of content that will be produced and need verification with this UCD initiative, our solution is uniquely positioned to offer a high degree of automation and operator efficiency.”
Paradatec’s OCR solutions offer significant efficiencies for classifying large quantities of differing document types and extracting key data elements from those documents. In the mortgage market, these capabilities allow for quick and accurate identification of over 500 unique documents in the typical mortgage file, along with the ability to capture nearly any data element from those documents that an organization requires.