This California based lender is one of the largest independent residential retail mortgage lenders in the United States. It is a leading lender offering a full range of quality home loans, including FHA and VA, conventional, jumbo and super jumbo, and renovation loans.
The client’s view
“Choosing Paradatec was a strategic decision for us. With their solution, we were able to complete high impact projects with a significantly improved level of accuracy and speed. We attribute our success on those projects to Paradatec’s commitment to customer service, attention to detail and ability to adapt to evolving customer needs.”
California based Top Lender, SVP
The mortgage lending industry presents a number of unique challenges for classifying and extracting data from key documents, due in part to the large volumes of disparate documents in most loan files.
Paradatec for Mortgages offered pre-built mortgage logic which “understands” the vast majority of the document types and variations this lender was required to recognize. This feature of the Paradatec offering allowed the customer to rapidly implement an ADR and data extraction solution for their specific needs.
- To compete in this extremely competitive market segment, organizations are looking for ways to reduce costs and streamline their processes.
- A typical mortgage loan file contains 250 to 600+ pages of various size documents, comprising more than 400 potential document types.
- Manually sorting each set of loan documents is a labor intensive and error prone effort, typically requiring the addition of document separator pages if the file is to be scanned.
The project was successfully implemented and released for production use in less than three weeks. For another quick turnaround audit, 75,000 mortgage files were processed (requiring the extraction of 25 total data points from three key documents in each loan file) in under four weeks.
Individual documents were automatically classified 95+% of the time, limiting the manual verification time to approximately one minute per loan file on average.