Roby Robertson of LoanLogics: Ignoring Income Defects Could Spell Disaster
Roby Robertson is Head Product Owner, Origination Automation ,responsible for strategic direction and development of all LoanLogics’ mortgage origination automation technologies. As a founding employee of LoanBeam, acquired by LoanLogics in December 2021, he has spent the past six years as a leader in the mortgage industry, spearheading many technological firsts. He is best known for his contributions to the industry’s dual-GSE rep and warranted self-employed income calculation offering, which has assisted self-employed borrowers qualify for their dream home. He is also responsible for development of wage-earner platforms. He resides in Dallas.
Back in 2015, Tesla CEO Elon Musk famously promised that self-driving cars would be a common sight on American roadways within the next three years. He wasn’t alone—Nissan and other automakers thought fully autonomous vehicles would arrive by 2020.
Obviously, these predictions fell a little short. But then again, exaggerated optimism about new technology is nothing new. For years, we’ve been promised that fully digital mortgages are just around the corner, but that day never seems to come.
Of course, there are good reasons for this. Just like navigating a car on city streets carries a level of unpredictability, there is also variability in the mortgage process that lenders’ systems can’t handle. And nowhere is this more true than when it comes to qualifying a borrower’s income.
In fact, income defects have emerged as one of the highest causes of repurchase risk for mortgage lenders. According to the QC reviews performed by Freddie Mac, by August of last year, 8% of reviews resulted in a repurchase, up from 4% of reviews in 2019. Three of the top five most common defects were incorrectly calculated income, missing or insufficient income documentation, and unstable income.
It’s not too hard to understand why. The pandemic had a jarring effect on the U.S. labor market. Forced layoffs and furloughs, combined with a reimagining of work-from-home norms, have drastically changed Americans’ outlook on “work.” As a result, the number of people making their income – in part or all – from non-traditional sources has exploded. This means more complex income streams and complicated verification processes for mortgage lenders.
The bottom line is that underwriters are seeing fewer borrowers who receive the same paycheck every two weeks and more borrowers whose incomes vary from year to year, or even month to month. And it’s making income calculations very difficult.
Of course, tax documents are the common way most lenders calculate self-employed income. Yet they are hardly the easiest method, as deductions and write-offs often make these calculations infinitely more complex.
For wage earner income, lenders are gathering pay stubs and W2 forms manually for roughly 70% of all loan applications. The other 30% are leveraging some form of digital income verification, but the costs for these services are going up, eroding some of the benefit.
All of this is happening at a time when lenders are being pressured to reduce costs, in some cases by laying off people and potentially losing valuable institutional knowledge. Meanwhile the Consumer Financial Protection Bureau has increased its staff of enforcement attorneys and is turning up the heat on non-compliant origination processes.
For underwriters, there is also a learning curve involved when shifting from qualifying income for a refinance to qualifying income for a purchase. After one of the longest refi markets in our industry’s history, lenders are currently finding it difficult to recruit and train staff who understand how to verify borrower income correctly for complex purchase transactions. Further complicating matters is the fact that many lenders continue to operate remotely, and it’s simply harder to train people this way.
More than ever, lenders need to understand the personal story behind every borrower and consider a wider range of factors that determine whether a borrower qualifies for financing. In order to stay competitive—especially in a rising interest rate environment—they need better tools for calculating borrower income not only quickly, but consistently. And if they don’t have these tools, they need to find them fast.
At the end of the day, calculating income quickly and accurately means lenders should be looking toward technology that provides the underwriter with a calculation framework, along with greater flexibility to adjust calculations as circumstances require. Ideally, lenders need tools that are designed to understand paperwork and then organize, synthesize, and turn it into data, all while using an audit trail to maintain compliance.
The first major benefit of automated income calculation technology is that it allows lenders to do more work with less manual effort, allowing them to refocus staff on risk assessment and growing the business. Technology can complement any lenders’ workflow and minimize manual tasks, but more important, even if lenders can’t go fully digital, it can still reduce the paperwork and costs involved in determining whether a borrower qualifies for a mortgage.
The second advantage of automation is being able to turn payroll costs into a fixed cost associated with each loan file. Everyone knows that technology is more scalable than human resources, so it can help optimize the staff needed to qualify a mortgage – while accounting for volume volatility in the process. Better to shift the balance to a fixed cost per loan file that is predictable, rather than an $80 an hour resource that is sitting idle.
And finally, automated income technologies are designed to work around the clock. We all know that borrowers can fill out online applications whenever they want. Loan officers hungry for business want to get the process started when the opportunity strikes. So automated solutions, particularly when integrated with other digital technologies, can move the process along at any hour of the day.
These automation tools have also been shown to protect lenders from fair lending accusations, because technology has no bias in performing income calculations across a wide range of borrowers. Whether calculating self-employed or wage earner income, the extraction of data from loan documents and the automation of income calculation becomes consistent. It provides equitable treatment for borrowers during the loan approval process and gives underwriters the transparency into the data and the calculations to assess every deal on its financial merits. Automation has also seen growing acceptance from the GSEs when it comes to expanded rep and warranty relief, which should help further the adoption rate of these tools.
Just like driverless automobiles, digital mortgages are not going to be easy to achieve—but it’s still a target worth aspiring to. Ultimately, progress toward digital mortgages will be measured by overcoming variables and properly applying automated technologies to adjust to the most difficult and problematic aspects of approving borrowers, including income calculations. And there is no better time to start than now.
(Views expressed in this article do not necessarily reflect policy of the Mortgage Bankers Association, nor do they connote an MBA endorsement of a specific company, product or service. MBA NewsLink welcomes your submissions. Inquiries can be sent to NewsLink Editor Mike Sorohan at firstname.lastname@example.org or NewsLink Editorial Manager Michael Tucker at email@example.com.)