The Future Is Now: How Lenders Can Turn More Self-Employed Americans Into Homeowners
March 1, 2019 - originally published March 26, 2018
How people earn money today is shaking up the mortgage industry. The U.S. workforce is made up of more nontraditional income earners – contractors, freelancers and on-demand workers – than it was a decade ago. And, many of them are looking to buy a home. But underwriting mortgages for these self-employed borrowers is complex and time consuming, a reality that discourages lenders from marketing to this group of prospective homebuyers.
With rising interest rates set to increase competition for borrowers, lenders cannot afford to overlook the self-employed customer. The good news is that technology has reached a point whereby it can automate and accelerate the income validation process for nontraditional wage earners, offering lenders an opportunity to innovate their approach to this customer segment.
Evolving U.S. Workforce Trends
Nontraditional income earners are becoming increasingly mainstream, particularly among Generation X and Millennials, who, compared to their parents and grandparents, move from job to job a lot more, and are more likely to be independent contractors.
Status tracking employment trends indicate a shift in the U.S. workforce. For example:
- About 30% or 44 million working Americans are either self-employed or working for the self-employed, according to a study by The Pew Research Center. The McKinsey Global Institute (MGI) estimates the number of self-employed workers to be higher, between 54 million and 68 million.
- Most self-employed Americans actively decide to work for themselves. A study by the Freelancers Union indicates that 60% of freelancers become independent contractors by choice. Answering the MGI survey, freelancers reported higher satisfaction than those with traditional jobs on 12 out of 14 aspects of their work life.
- The "gig economy" has a lot of room to grow, and that means more people will make a living this way. While the JPMorgan Chase Institute estimates that 4% of the working-age population has earned income through "sharing economy" platforms, McKinsey says that some 15% of independent workers have used them to make money.
So, what does higher work satisfaction, the burgeoning on-demand economy and the growing reliance of companies on contractors mean for lenders? The bottom line is that they'll be confronted with more loan applications from self-employed homebuyers and, with them, the challenge to work smarter.
The Challenge in Lending to the Self-Employed Borrower
Today, some 14 million borrowers are self-employed. And if experts prove correct, this number is bound to increase in coming years. It's a trend that will exacerbate an existing problem for lenders – how to speedily and efficiently process mortgage applications for nontraditional wage earners.
To underwrite self-employed borrowers, lenders must dissect a customer's tax returns – versus a W2 – to validate his or her income. Complicating matters is the fact that the self-employed are incentivized to reduce their taxable income through deductions and write-offs. Loan officers and processors often must then manually reconcile dozens of pages of tax documents – including 1099s, Schedule C's and other forms – to arrive at a reliable income total.
The income-validation process can take days to unfold. Loan processors often discover that essential information is missing from a file, requiring more back-and-forth between borrower and loan officer. Processing these mortgage applications translates into higher operational costs for lenders, who need to beef up staff and training to handle these customers.
Technology Solutions for Lenders
While lenders can't change their practices overnight, they can incorporate new technology into them – in ways that strengthen their current capabilities. They can speed up mortgage application processing and, in this specific case, validate income more smoothly and quickly for the self-employed borrower.
The technology that stands to change the game is based on optical character recognition, or OCR. Built into software programs that integrates into lenders' systems, OCR offers them a way to automate further and, in doing so, to compete more effectively for self-employed borrowers.
OCR programs extract and ingest information from tax returns and other mortgage application documents, and then they generate a total income figure. Software programs predicated on OCR then automatically populate relevant data into a pre-formatted workbook. The workbook can be customized to incorporate government-sponsored enterprise (GSE) income guidelines and lender-specific requirements.
The reality of increasing interest rates only makes it more incumbent upon lenders to seek innovative solutions in casting a wider net for borrowers. The upside is that the necessary technology exists. Lenders can take advantage of it to free up their employees to cultivate client relationships and measure risk more accurately, leading to a faster turnaround time for borrower and lender. At the same time, they can leverage these solutions to scale their business and improve operational efficiency, giving them an edge against competitors.