CoreLogic announced its new Home Mortgage Disclosure Act (HMDA) Check solution, combining optical character recognition (OCR) data extraction with a rules engine that helps automate the HMDA auditing process.
This allows lenders to increase efficiencies, improve data accuracy, reduce costs and remain compliant with HMDA requirements.
“CoreLogic HMDA Check is designed to expedite the Loan Application Register (LAR) data collection and submission process by automating review and validation procedures before submitting to the Consumer Financial Protection Bureau (CFPB),” the company said in a press release. “The new solution inspects more than 30 different loan origination document types for more than 100 HMDA reportable fields, including loan features such as loan term, interest rate, and borrower information. Then HMDA Check validates the LAR data, immediately highlighting discrepancies for the lender to support his or her HMDA reporting needs.”
Visually reviewing loan source documents against a LAR submission, according to CoreLogic, can take hours and the process is prone to error, making it expensive for lenders. By automating this process, lenders can speed up the loan review process, increase consistency, and help identify discrepancies.
“Discrepancies between source loan documents and the LAR can potentially result in penalties from the CFPB, as well as set a more challenging examination process,” said Cres Hay, senior leader of product management at CoreLogic. “HMDA Check helps lenders meet regulatory industry requirements by integrating OCR and validation technologies into one place, revitalizing a once manual, labor-intensive process.
“The fully-automated solution ends the ‘stare-and-compare’ analysis method and helps lenders focus their resources more efficiently,” Hay added.