Correction: An earlier version of this story stated that lawmakers were proposing a winding down of Ginnie Mae. This is not the case. This version of the story has been corrected.
Five years after the national housing bust, Freddie Mac — the McLean-based entity that backs one-quarter of the country’s mortgages — is hoping to become more transparent by standardizing its processes and making raw data more easily accessible to the public.
“The more data we have — on the borrower, the property and the loan — the less likely we are to have a blow up like we had in 2008,” said Rob Lux, chief information officer of Freddie Mac.
Now, as lawmakers discuss an eventual winding down of Freddie Mac and Fannie Mae , regulators say it’s becoming increasingly important that private investors have the wherewithal to take over the millions of mortgages that are currently guaranteed by the government-sponsored enterprises.
“We want to make sure we’re using our data to attract private capital to come back into mortgage securitization,” Lux said. “Between Fannie and Ginnie and us, we’ve got the lion’s share of the market. But everyone agrees, including us, that that’s not the future.”
In March, Freddie Mac released information on 15.7 million mortgages — all single-family, 30-year, fixed-rate loans — that the agency backed between 1999 and 2011.
(Washington-based Fannie Mae also released similar data the following month.)
The idea, regulators say, was to make it easier for the public — investors, analysts and others — to dissect the performance of existing mortgages, as well as the risks associated with them.
“These data releases pave the way for Freddie Mac and Fannie Mae to ... gradually contract their dominant presence in the marketplace,” the Federal Housing Finance Agency, which mandated the data releases, said in a statement.
At Freddie Mac, the data releases are part of a broader push within the enterprise to make better use of technology, as well the data it collects, Lux said. Over the past two years, the agency has begun moving more of its data onto its cloud, and has partnered with data visualization and data mining companies to make better use of the information it does have.
When Hurricane Sandy hit the eastern seaboard last fall, Lux says employees were able to quickly identify affected homes and hone in on borrowers who were under duress. In a matter of days, the agency had taken measures to stop possible foreclosure proceedings for those borrowers.
“Back with Katrina, it took a lot of effort to figure out where the properties were and which properties were impacted, and how badly,” Lux said. “With Sandy, we did all that in about a week.”
There have been other improvements, too. Up until a year ago, Lux says there was no systematic method for appraising homes that were on the market. Appraisers were left largely to their own devices.
“Something that would be called ‘average’ could also be ‘average plus,’ ‘good,’ ‘good minus,’ ” Lux said. “Appraisers were basically just throwing out those ratings without any uniform standards.”
Today, the FHFA has come up with an eight-rating system for measuring a home’s condition. And for the first time, appraisals are being submitted and processed electronically.
“It’s not paper forms with scribbles all over anymore,” Lux said. “That allows us to do modeling with that data and say, ‘Wait, this property in a neighborhood appraised very, very high compared to the others. Is there something wrong here?’ We can do a lot of different things with that data that we were never able to do before.”
Eventually, Freddie Mac — in conjunction with the FHFA and the Mortgage Bankers’ Association — hopes to apply that same uniformity to all types of data.
But Lux said it can be a time-consuming process. Standardizing something as simple as the submission process for loans can take upwards of two years, Lux said. Later phases of the project call for collecting more points of data and eliminating special codes.
“Prior to this, every bank had their own data standards,” Lux said. “One bank would say, here’s how we calculate loan-to-value ratio. Another bank might have a totally different way of doing it.”
Even Freddie Mac and Fannie Mae tended to communicate differently. One might, for example, have reported a number as a fraction while the other used decimals. The whole thing made it difficult to decipher and analyze data.
“We want to make sure everybody’s singing from the same book,” Lux said. “In the past, we were speaking different languages.”