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The Rising Data Tide Lifting Loan Quality

Editor's note: This story originally appeared in the December edition of MReport.

 

Ever since President Kennedy borrowed it for a 1963 speech, the phrase “ a rising tide lifts all boats” has usually been applied to economic plans or ideas that claim to advance everyone’s interests. Next year, however, the mortgage industry is about to experience its own “rising tide,” one that promises to benefit all mortgage participants—thanks to the culmination of data standardization efforts by the Federal Housing Finance Agency (FHFA) and the coming sea change in the loan application process.

That sea change is the new Uniform Residential Loan Application (URLA), which will begin its year-long transition toward becoming the new standard for mortgage loans sold to Fannie Mae and Freddie Mac beginning in February 2021. The good news? With the likelihood that lower rates and a tighter credit box will be with us for some time, lenders may find the new application more comprehensively supports the application process. Borrowers should be pleased too, as the new URLA will almost certainly provide consumers with a more modern experience.

However, there’s much more to rave about than meets the eye. The new URLA will also make it easier for lenders to capture data for evolving lending scenarios that may present themselves in the coming year. More importantly, the new application will also eliminate many data ambiguities, which will lead to improvements in loan quality and reduced cycle times across the mortgage lifecycle. Time will tell, of course, but the advantages of more uniformity in data capture for all “boats”—including lenders, servicers, and the secondary market—cannot be overstated.

Why Standardized Data Is Key

The difference in appearance between the new URLA and the current, which has for years served as the de facto standard for mortgage applications, is striking. Yet the new design also looks familiar—which shouldn’t be a surprise, considering the GSEs selected the same designer that created the Loan Estimate and Closing Statement disclosures for the Consumer Financial Protection Bureau that went into effect five years ago.

A more substantial difference with the new URLA is how it will be used. Although relatively few borrowers fill loan applications by hand anymore, the current application was designed for borrowers to do just that. The new URLA, on the other hand, was designed specifically to collect and display information digitally. While the new application still requires certain key information to be provided, it’s also a dynamic form, meaning it expands to account for additional borrowers and data needed for the case at hand.

To truly understand the real “sea change” the new URLA rep-resents, however, a bit of history is in order. While the new URLA is the first major change in the standard loan application in more than 20 years, it actually represents the fifth initiative under the FHFA’s Uniform Mortgage Data Program (UMDP), which directed Fannie Mae and Freddie Mac (GSEs) to collaborate on common standards when doing business with their authorized sellers/servicers. Other UMDP initiatives included the Uniform Loan Delivery Dataset (ULDD, implemented in 2010 using MISMO version 3.0); the Uniform Appraisal Dataset (UAD, implemented in 2011 on MISMO 2.6 Valuation/GSE2.6 and is being upgraded to UAD2 using a future MISMO release 3.6 or higher); the Uniform Mortgage Servicing Dataset (UMSD, announced in 2012 and halted in 2013 using MISMO version 3.3); and the Uniform Closing Disclosure (UCD using MISMO version 3.3, implemented in 2017).

The fifth initiative, the Uniform Loan Application Dataset (ULAD), is the data companion to the redesigned URLA. Both documents share a common design palate that features a modern look and feel. In the case of the URLA, new data elements have also been introduced that provide borrower details in a more complete fashion for non-joint credit applicants. Due to heightened credit risk, this is a scenario that could be more prevalent in the coming year. ULAD was designed to convey data from a lender’s loan origination system (LOS) to the lender’s document preparation company. Interestingly, the GSEs each independently implemented upgraded message requirements for their respective automated underwriting systems using MISMO 3.4 data standards, but they did not publish them as a “U” program. The message requirements do, however, include ULAD data.

Until now, the industry had relied on the old FNM 3.2 flat file for both Fannie Mae and Freddie Mac automated underwriting, as well as for information exchange across multiple systems. With the introduction of ULAD, the 3.2 file is being retired. However, MISMO has issued a new specification known as the Industry Loan Application Dataset (iLAD), which incorporates ULAD, the automated underwriting requirements for both GSEs, and importantly, additional details needed by the industry that either were in the old 3.2 file or are items that are required to support other needs for the collection and conveyance of the application amongst trading partners.

Improving Data Quality

Overall, the use of standardized data for interacting with the GSEs has an overall effect of improving data quality industrywide, a phenomenon that evolves as each new data specification comes online. The base of each of these requirements as issued by the GSEs are XML message specifications that provide strict instructions on what data is to be provided, how it is to be formatted, and what is required or optional. This type of specification then is implemented by software providers to convey the datasets through electronic integration for conveyance from seller/servicers (or their agents) to the GSEs’ respective portals.

Merging data collection and presentation at the start of the loan process will also make it easier for lenders to use more detailed information for determining borrower eligibility, which will speed up originations—a key benefit at a time when lenders are struggling with capacity. It also enhances back end processes as well. Gathering all key data digitally in a standardized way opens up new possibilities for automation to shorten days to originate and get to closing much faster.

Standardization has already led and will continue to lead to the rise of new services and technologies that can capitalize on defined data and offer new and improved capabilities. Ultimately, this makes the quest for the elusive digital mortgage closer to a reality, and not just a futuristic pipe dream. I suspect that by 2021, kick-started by 2020 technology adoption trends, we will see new platforms that enable even greater automation in mortgage origination, servicing and loan commerce.

For example, there are some MISMO exploratory commit-tees that are considering reviving the work started on the now-abandoned Uniform Mortgage Servicing Dataset (UMSD). At minimum, this would mean moving the UMSD up to at least the MISMO 3.4 release for congruency to ULAD. Reviving an industry standard for mortgage servicing would benefit both new loan setup on servicing platforms as well as smoothing servicing transfers. Simultaneously, there are discussions taking place on formulating a standard for evaluating mortgage servicing rights (MSRs).

No doubt, the industry will continue to look for ways to move the benefits of data quality forward from the origination channel. The advent of the GSE Uniform Security Instruments and FHFA’s Uniform Mortgage-Backed Security Rules are other examples of standardization that are intended to facilitate faster delivery of mortgage loans into the secondary market.

All this being said, our industry is constantly evolving to new ways of doing business. Making such a significant change in the application process will be a challenge for many as they train their staff and ready their systems to support the new requirements.

The key, however, is not to look at the URLA as an obstacle, but as an opportunity that is truly unparalleled in recent history. Thanks to ongoing, complementary data standardization initiatives, the new application will undoubtedly lead to a more efficient origination process, lower loan processing costs, higher quality loans, and a smoother, more enjoyable consumer experience.

Ultimately, clean, reliable, machine-ready data made possible by the adoption of data standards will be the lifeblood of technology improvements in the mortgage industry, as well as advancements in big data analytics and artificial intelligence aimed at improving profits and reducing risk. Clean data is indeed our industry’s own rising tide that will lift all boats, setting them up for a journey that promises even more exciting innovations to come.

About Author: Elizabeth Green

Elizabeth Green is the Chief Data and Product Solutions Officer at LoanLogics, where she is responsible for the development of the company’s solutions and data strategy as well as the expansion of its products, including in the area of collateral risk assessment. Green is a strategist, solutions architect, speaker, and valuation advocate. As a recognized mortgage technology veteran in software product leadership for solutions in residential property valuation, loan origination, mortgage servicing, and secondary marketing, she has helped to foster a new level of understanding in credit and collateral risk assessment through the application of digital intelligence.
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