One of the big stories in 2017 has revolved around the innovations at the front-end of the digital mortgage experience. New point of sale (POS) solutions have made significant headway in taking the pain and hassle out of applying for a mortgage. Lost in all the industry headlines, however, is the ongoing disconnect between the digital consumer experience and the cobbled together, often manual underwriting processes.
Unfortunately, many underwriters are still following inefficient, time-consuming tasks when analyzing and calculating a borrower’s income. Current processes require the underwriter to gather the disparate sets of data, manually enter that data into spreadsheets, do their calculations off-line and finally enter their calculated income into the LOS. In many cases, these calculations are submitted without an explanation for how they were determined, which can result in loan suspensions, redundant reviews and a poor borrower experience.
Although many borrowers earn their income from W2 sources, more often than not a unique circumstance of one sort or another will apply, complicating the underwriter’s analysis. The situation goes beyond self-employed borrowers. As baby boomers continue to get older and retire, their income sources may shift. More affluent and financially sophisticated borrowers may have passive or portfolio income streams, or may have to use the asset depletion method for calculating their monthly income. Even first-time homebuyers may have multiple non-traditional income sources. In these more complex situations, data accuracy and process consistency can pay big dividends in the mortgage production workflow.
So, how can the industry disrupt the current underwriting workflow for income verification and calculation? The solution is pretty simple on the surface - leverage the rich data that is available and transform the income analysis process into a digitized structure which is standardized, efficient, configurable and compliant. 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.
Such a solution would avoid time consuming tasks such as manually entering data into checklists and tabulating calculations in home-grown spreadsheets. Information (e.g. tax returns, pay stubs, W-2, bank statements, etc.) could be either submitted digitally or through paper forms that can be digitized. Whatever the format, standardizing a data model and providing the capabilities to transform the myriad of documents and data sets into a digital structure would unlock the ability to automate, standardize, and track all the processes that currently make underwriting such a difficult task today.
Lenders should also be able to layer their own criteria into the analysis so they trust the results. For example, while active income streams (e.g. salaries, wages, commissions, bonuses) are pretty straightforward, passive income streams (e.g. owned businesses, royalties, rental and multi-level marketing) and portfolio income (e.g. stocks, shares, capital gain, collectibles, currency exchange) must be able to be addressed in a similar fashion with full transparency as to the what and why of the source. But today that is not the case. In fact, if you gave the same loan file to ten underwriters it’s conceivable, even likely, that ten different income amounts could be calculated.
We envision the creation of a standardized income verification and calculation solution for lenders that leverages digitized data and technology to increase their efficiency and productivity while reducing their risk. With a solution like this, underwriters will be able to focus more time on getting borrowers qualified and less time wading through documents and transposing numbers.
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