What do we mean when we say we are working toward standardizing mortgage data?
Believe it or not, it’s not nearly as “techie” as it sounds. And its effect will create significant long-term benefits both for our company and the housing market as a whole.
Mortgage data covers a wide area, from basic loan-level information, such as a borrower's personal information or details about a property, to complex modeling and analysis data used to monitor loan performance. In the past, mortgage data usage throughout the financial industry could be characterized as unstructured, unorganized, inefficient, and overexposed. In some cases, we believe the entities involved in the loan life cycle – such as lenders, servicers, and the GSEs, to name a few – couldn't fully gauge their exposure at the financial instrument level. In other words, companies may not have known how intertwined they were when a direct contractual relationship didn't exist. This contributed to confusion in an already stressed housing finance system.
The financial sector has been making steady and meaningful progress in standardizing and simplifying its collective data. It began with the standards movement – essentially, ensuring that everyone was speaking the same language in terms of data. The movement to establish consistent standards began from the bottom up and has been led in part by Fannie Mae, under the guidance of the newly established Office of Financial Research – a creation of Dodd-Frank Wall Street Reform and Consumer Protection Act.
These efforts also align with the Federal Housing Finance Agency's (FHFA) Uniform Mortgage Data Program, part of the agency's overall strategy to strengthen America's housing finance system for the long term. Under the program, Fannie Mae and Freddie Mac are working with the FHFA to improve the consistency, quality, and uniformity of data collected at the beginning of the lending process.
This shift to standardization has many benefits. It may lower costs for originators and appraisers, help new companies to enter the market faster and more efficiently, and enable businesses to catch potential issues (such as delinquency rates) earlier in the mortgage process – helping them to react quickly and in a more collaborative way, which may ultimately help borrowers.
For any financial or mortgage company, data quality and enrichment has become crucial. The most unique and important part about how we’re approaching data at Fannie Mae is our enterprise perspective. We are building toward our ultimate goal of viewing data quality issues at the enterprise level and tracking data as it moves from one part of the company – or loan life cycle – to another. This is facilitating a strengthened quality control process, which should benefit all of our partners and customers.
It is important to note that data integrity cannot be approached alone. Financial institutions remain interconnected, so one company getting their data in order means nothing if its closest partners are lagging behind. That’s why Fannie Mae and other financial companies have placed a great emphasis on aligning our efforts and advancing like-minded data initiatives at a similar pace.
The financial industry is at the beginning stages of data reform, and it’s clear that the path to standardization will be a marathon, not a sprint. However, we’ve made tremendous progress in the past few years. We’re proud to have taken a leadership role on the enterprise data front, and we're hopeful this will lead to a stronger, more efficient mortgage industry that will benefit businesses and families alike.
Senior Vice President
Chief Technology Officer
March 1, 2012
The views expressed in these articles reflect the personal views of the authors, and do not necessarily reflect the views or policies of any other person, including Fannie Mae or its Conservator. Any figures or estimates included in an article are solely the responsibility of the author.