Loan applications are increasingly submitted and approved via a cell phone and Fannie Mae, and Freddie Mac constantly refer in press releases to their respective automated systems. Therefore, it is startling to learn that, on the front lines of lending, underwriting remains far from what a jockey friend used to call a "push-button pony."
Eric Connors, Executive, CoreLogic Mortgage and Credit Analytics, writes in the company's Insights blog that 2017 was a good year for innovations at the front end or point of sale (POS) of mortgage lending. But those improvements also serve to highlight "the ongoing disconnect between the digital consumer experience and the cobbled together, often manual underwriting processes."
Connors says many underwriters are still analyzing and calculating a borrower's income in inefficient and time-consuming ways. This can involve gathering disparate sets of data, entering it into spreadsheets, and doing calculations off-line, all before finally entering the resulting income into the loan origination software. He says that these calculations are often submitted without any explanation of how they were determined, resulting in loan suspensions or multiple reviews.
This issue arises because income sources aren't always straightforward, Connors explains. While for many borrowers W2s adequately cover the situation, there are often complicating circumstances. With the population aging into retirement, income sources can shift toward passive or portfolio streams; some retirees even use the asset depletion method for calculating income. The growing gig economy means more first-time borrowers have multiple non-traditional income sources.
What is needed is a system to leverage available data and transform the income analysis process into a standardized, efficient, configurable and compliant digital structure. "By standardizing the workflow with a consistent and automated process, lenders (and their investors) could gain greater confidence in the quality of their loans and feel empowered to start driving costs out of the origination and underwriting processes," he says.
This would eliminate time-consuming tasks like manually entering data into checklists and calculating in home-grown spreadsheets. Connors envisions tax returns, pay stubs, bank statements, and other data sources submitted either digitally or on paper forms that can be digitized. Such a digital structure would unlock the ability to automate, standardize, and track all the processes that currently make underwriting difficult today.
If you gave the same loan file to ten underwriters today, Connors says, "It's conceivable, even likely, that ten different income amounts could be calculated." Lenders need to be able to plug their own criteria into the process, so they trust the results. Many income streams, like wages, commissions, bonuses, are straightforward, other sources such as business income, royalties, multi-level marketing, are not. Passive income streams such as stocks, collectibles, currency exchanges, likewise need to be addressed with full transparency regarding the source.
Such a system for standardized income verification and calculation using digitized data will increase underwriter efficiency and productivity while reducing risk. Underwriters would then be able to focus more time on getting borrowers qualified and less time wading through documents and transposing numbers.