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After a few months of a pandemic-driven hiatus, the excitement for non-QM loans is brewing again among originators and investors alike. This of course is also good news for the many borrowers that don’t fit into a traditional credit box but would like to take advantage of historically low interest rates. Among this happy crowd are self-employed borrowers, who represent roughly twenty to twenty five percent of mortgage loans.
Before anyone can truly capitalize on all this reemerging opportunity, old and new risk factors will need to be addressed. In addition to the general risk these types of products represent, today lenders must also deal with constantly changing loan guidelines being driven by the economic and jobs environment. Borrowers who may qualify for a loan one day might not qualify the next. Also, in the face of significant loan volumes, lenders are trying to originate loans as quickly as possible, increasing the risk of errors. The result of both may be a rise in eligibility defects.
Give these challenges, rest assured investors will be paying close attention when these loans come in the door. As such, minimizing controllable risk must become a front and center priority for lenders working with non-QM products. A comprehensive loan quality process is one way to ensure that mistakes and errors are minimized.
A key component of successful loan quality control begins with using technology and digital labor for the validation of loan file data to ensure its accuracy and consistency across all systems and mortgage documentation.
– Dave Parker, Chief Product Officer, LoanLogics
A key component of successful loan quality control begins with using technology and digital labor for the validation of loan file data to ensure its accuracy and consistency across all systems and mortgage documentation.
With automated doc processing that combines sophisticated rules and algorithms with machine learning tools, validated datasets can then drive even more automation for other tasks traditionally performed by processors, underwriters, and loan auditors. These can be completed in a fraction of the time and with much greater accuracy, making 100 percent pre-closing reviews possible. Having more opportunity to catch defects earlier in the manufacturing process helps lenders reduce risk and gain investor confidence.
This is crucial, not only for the accurate, timely completion of pre- and post-closing quality reviews but also for other types of reviews, such as TRID and HMDA compliance.
Digital labor technologies also help servicers and investors. When purchasing servicing rights and onboarding loans, or buying non-QM loan portfolios, automation can be used to eliminate the process of manual due diligence reviews. Instead, the audit tests required in pre-purchase reviews can mostly be done through automation using validated data with condition clearing orchestrated through portal technology. This combination can significantly decrease turn-around time and speed funding back to sellers.
Ultimately, more pervasive use of digital labor will remove the subjectivity from loan decisions and improve investor confidence. This becomes particularly important when it comes to the long term sustainably of non-QM products in the market.
Earlier this month, I went into greater detail on this topic for MBA Newslink in the article, “Rebounding Non-QM Market Requires Quality Reviews to Mitigate Risk.” To read my full article with more background on Non-QM loans in the context of today’s lending environment click here.
