Late last year Fannie Mae included questions in one of its National Housing Surveys about working in the "gig" economy.  About a fifth of respondents claimed they earned at least some of their income through such employment.  Gig-economy workers tend to have flexible work arrangements, working on single projects or tasks preforming on-demand services such as transportation (Uber, Lyft) lodging rental (Airbnb and VRBO) food/goods delivery, and personal tasks (TaskRabbit).

Because of its "on-demand" nature, the income stream from gigging can be less stable and its source less reliable.  With the numbers involved increasing, this is likely to become an issue in mortgage lending, so Fannie Mae's Economic and Strategic Research (ESR) group included some self-employment and gig-economy related questions in a recent Mortgage Lender Sentiment Survey®.

One set of questions sought to find out how lenders view the gig economy trend. Have they seen applications with such income over the past year? How much do they expect the gig economy to expand or decline in coming years, and how much will that income help consumers access mortgage credit?

A second set asked how lenders view current practices for accepting the income for mortgage qualification? What are the challenges, if any?

Lastly how do they view current practices for using self-employment income for mortgage qualification? What are their top risk factors? What options do they prefer in improving self-employed workers' access to mortgage credit?

The responses indicate that the gig economy may be becoming mainstream, but slowly. Seventy-one percent of lenders said they have had borrowers apply for a mortgage with such income over the last year, however, only 3 percent categorized the number of applications as "many" or "quite a lot." Eighty-nine percent expect these numbers to increase over the next few years, but although only 14 percent said the growth would be significant.

More than two-thirds (68 percent) say that accepting the income as valid for mortgage qualification will help low-to-moderate income consumers to access mortgage credit although 58 percent qualified that as helping "somewhat."  Among those who foresee it as helpful, it was generally because the extra income could push marginal applicants over the minimums.  Those who thought it would be unhelpful gave such reasons as the income being too difficult to track and verify and a lack of evidence the income would continue.

Some of these same reasons were voiced by the 95 percent of respondents who said it is difficult to use gig economy income to approve mortgage applications with today's lending practices. They also named the unpredictability and instability of the income, the wariness of investors, and the lack of standardized underwriting criteria regarding it.  One respondent, representing a smaller institution, said, "This type of income is still relatively new. I am not sure that the agencies have enough loan performance history for these borrowers to tell us if they present added risk." 

When asked specifically about self-employment income, 69 percent of lenders say current underwriting guidelines for income verification are about right, while 24 percent suggest easing existing standards.

Fannie Mae says the growth of this new type of employment and the effect on how the self-employed work and earn, including use of the resulting income in underwriting should not be overlooked.  Those applicants with a sufficient history of earning such income that fits within investors' guidelines are being served today, but the instability and unpredictability that is the very nature of gig economy income makes it difficult to meet investor requirements. Most lenders do think the current underwriting standards for more traditional self-employed borrowers are about right.

Fannie Mae concludes that there is a potential for new tools that could help lenders verify and assess gig economy income.  Emerging technologies could automate the verification of gig income from tax returns, payroll information, and bank statements, and help to assess income stability and predictability. Understanding how workers within the gig economy and others of the self-employed are paid and how they report their income could lead to streamlining the verification and risk assessment process and help improve the entirety of loan origination and minimize tedious manual processes.

Another survey respondent, this one representing a mid-sized lender said, agreed with Fannie Mae's assessment.  "Job stability and income stabilities are significant components of credit evaluation.  Our industry is based on traditional employment models and does not serve these consumers well.  We need flexibility to serve this growing employment group."