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Breaking New Ground for Self-Employed Borrowers

May 23, 2018

In the Spotlight

Hear from Chris Boyle, senior vice president of Single-Family Sales, Marketing and Relationship Management, on Freddie Mac’s partnership with LoanBeam to change the game for self-employed borrowers, and how real estate professionals and their clients can benefit.

In a nutshell, what is the LoanBeam technology, and how does it serve self-employed borrowers?

Chris Boyle: LoanBeam’s technology is changing the homebuying process for self-employed borrowers by automating the income validation process. It extracts and reads data from tax returns, and then calculates an income total at a 99.7 percent accuracy rate. Freddie Mac and lenders need this level of accuracy before entertaining the thought of using software to calculate an income total. We can’t take chances, given the complexity of deriving a monthly stable income figure for a loan. Lenders that choose to work with LoanBeam will know that they can use its income calculation to reliably underwrite loans that are saleable to Freddie Mac.

What do you see as an important opportunity in the mortgage market today?

44 million self employed

Chris Boyle: The economy is strong and wages are growing, so people are still well positioned to buy homes. One customer segment that is ripe for growth is nontraditional wage earners – or self-employed borrowers. Today, there are only about 14 million self-employed borrowers, but studies indicate sharp growth in the number of nontraditional wage earners in this country. LinkedIn recently published a study predicting that some 43 percent of U.S. workers will be freelancers by 2020. Even if this estimate is ambitious, it still highlights a trend that lenders and real estate professionals will want to note.

What are the common challenges that self-employed borrowers face when buying a home?

Chris Boyle: Self-employed borrowers are among the toughest customers to underwrite because of their unique income picture. Loan officers must manually reconcile dozens of pages of tax documents – including 1099s, Schedule C’s and other forms – to calculate income. The process can take days to unfold, only for the loan processor to discover that some essential information is missing, requiring more back and forth between processors, real estate professionals and homebuyers. These delays increase processing costs and, in some cases, can even lead to the denial of the mortgage application.

How can real estate professionals better help their self-employed clients?

Chris Boyle: Interestingly, many real estate professionals can personally relate to the income structure of self-employed borrowers. According to the 2017 National Association of REALTORS® Member Profile Report, over 95 percent of real estate professionals are self-employed or paid on some combination type of commission structure. They know, and understand this challenge, and as the trusted advisor, they should be aware of solutions that exist to help self-employed borrowers overcome home financing challenges. Real estate professionals can connect their client with a lender that uses LoanBeam’s technology. It all starts with a simple question to the lenders in their network, “Do you use LoanBeam?” Now real estate professionals can confidently refer their clients to lenders that have a solid solution for them. This is a real game changer.

How will the changing dynamics of self-employed borrowers impact real estate professionals’ business?

Chris Boyle: Nearly 30 percent of working Americans are self-employed – and that number will grow. This certainly will impact real estate professionals’ business. As the client base continues to change, making smart referrals will be key to success. It’s important that they know the lenders in their network that are experienced with financing self-employed borrowers. Ultimately, it will result in faster pre-qualifications and closings.

Visit to learn more about the collaboration between LoanBeam and Freddie Mac, and how LoanBeam works with lenders to automate the income validation process.

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