Fannie and Freddie Setting Sights on a Data Overhaul

The work to update the data standards of Fannie’s DU and Freddie’s LP will coincide with an evaluation and possible update to the Uniform Residential Loan Application. Image: Fotolia.

Fannie Mae and Freddie Mac have begun the preliminary work to update the required data points and format that lenders submit to the government-sponsored enterprises’ respective automated underwriting systems.

The work to update the data standards of Fannie’s Desktop Underwriter and Freddie’s Loan Prospector will coincide with an evaluation and possible update to the Uniform Residential Loan Application, also known as Form 1003, according to representatives from the GSEs, who spoke on an April 15 panel at the Mortgage Bankers Association’s national technology conference in Hollywood, Fla.

“We’re going to revisit it and make sure we’re getting the right information…What you might see is very likely and very possibly a new uniform AUS dataset, since 1003 drives the data for DU and LP,” said Sam Oliver, Freddie Mac vice president of single-family business transformation management.

The GSEs’ AUS platforms have long conformed to data submission standards developed by the Mortgage Industry Standards Maintenance Organization, but have not been updated to align with advances in the MISMO reference model, notably the current Version 3.X architecture of the data standards. The incongruity between the legacy MISMO standards used in the AUS platforms and contemporary MISMO standards that the GSEs have leveraged in its Uniform Mortgage Data Program has at times required loan origination system vendors to develop workarounds to meet new data collection requirements.

For example, in order to automate the process of generating the Uniform Loan Delivery Dataset file for all loans sold to Fannie and Freddie, LOS vendors had to translate the AUS data into the new MISMO standards. Steve Pawlowski, Fannie Mae vice president of strategic initiatives, acknowledged that those extra steps could have been avoided by addressing how the data is first collected by lenders.

“If we could look at ULDD all over again, we went right to the delivery side of the house and what we should have done was go to the data collection,” he said. “We’re going to do this backwards, but we’re going to get it right this time.”

In addition to ongoing enhancements to the ULDD and the Uniform Appraisal Dataset (the form used to submit valuation reports), the GSEs continue to develop the new Uniform Mortgage Servicing Dataset announced in 2012 and will work with the Consumer Financial Protection Bureau to create a MISMO-based digital file of the “Closing Disclosure” form that will soon replace the HUD-1, which the GSEs will call the Uniform Mortgage Closing Disclosure, or UMCD. MISMO volunteers had previously begun working on developing a data map of the HUD-1 form, but the work was put on hold after the CFPB decided to replace the form. Now, the data mapping of the new form will happen as part of the UMDP.

“The reason we’re focused on the HUD-1 is the CFPB has been working really hard to standardize the form and before they push it out the industry we want to make sure that we have time to map it to the MISMO reference model,” Pawlowski said.

Oliver, who’s been a key participant in Freddie’s contributions to the Federal Housing Finance Agency-mandated data initiative, said both GSEs are applying lessons learned over the four years since the first UMDP-related efforts began—including relying on an incremental approach to phase-in new requirements, which he said helps lenders and vendors better manage process changes and implement new technology.

“Much of the industry thought of UMDP as an IT project, that we’re just changing the format to MISMO,” Oliver said. But what industry participants have learned through the process is that these changes go beyond file formats. Oliver said the harder part is thinking about where lenders need to make business process changes and how they collect the data at the right point in time, adding that the efforts are helping improve loan quality and risk in the mortgage industry.

“Good data equals good business,” he said. “Not knowing the details of the information of the loans moving around the market makes it harder for us to assess risk.”