MortgageMortgage OriginationNon-QM Loans – The present, the future, and how document automation can play a key role in making it more sustainable

May 12, 2022

As margins thin out, lenders are faced with the task of reconfiguring their existing cost structures while looking for alternate revenue streams. The non-QM market is emerging as a lucrative and practical solution for many. COVID-19 halted the boom of non-QM due to the liquidity constraint, however, it regained its market share and finished 2021 with 25 billion worth of originations and is anticipated to double in 2022.

What is a Non-QM Loan?

A loan which has any one of the criteria below will be considered non-QM:

  1. Debt-to-Income greater than 43%
  2. Blemish on FICO credit due to unforeseen circumstances
  3. Self-employed for less than two years
  4. Low income on tax returns

A non-qualified mortgage doesn’t conform to the consumer protection provisions of the Dodd-Frank Act.

For example, if you have a DTI of more than 43% or have erratic income and don’t meet the income verification requirements set out in the Dodd-Frank Act or by most lenders, you are not eligible for a qualified mortgage and may be offered a non-qualified mortgage instead.

How Do Lenders Verify Income for Non-QM Loans?

Non-QM loans don’t adhere to the standards required for QM loans, but that doesn’t mean they are low-quality loans. A study conducted in 2018 shows that the differences in credit score and loan-to-value ratio between non-QM borrowers and QM borrowers are minimal. However, non-QM borrows on average do have a higher DTI ratio.

Non-QM loans provide flexibility for lenders to offer mortgages to people not eligible for QM loans. Nevertheless, lenders still need to substantiate the documents provided, including income sources. They may also want to verify assets or any other information that assures them the borrower will be able to repay the loan. Non-QM loans are not insured, guaranteed, or backed by FHA, VA, Fannie Mae, or Freddie Mac.

The Evolution of the Mortgage Market

The non-QM market shows promise for the future due to the below factors:

Stricter Regulations 

Regulatory bodies, Fannie Mae, and Freddie Mac have made stricter restrictions to reduce possible risks by limiting the percentage of qualified loans offered. This has resulted in a smaller government box, isolating a large section of borrowers who do not conform with the GSE. Moreover, with bank lending restrictions also becoming stricter, this aided non-QM loans to become a more accommodative alternative for loan seekers.

Evolving Borrower Profile 

There has been a radical change in employment profiles across the country triggered by the COVID-19 pandemic. Entrepreneurship is on the up with a significant percentage of salaried individuals starting their own business due to loss of jobs.

According to statistics, the growth of start-up businesses in the country has risen by 24% from 2019 to 2020. A Forbes report published in 2019 estimated that nearly 30% of Americans are self-employed. This opens the non-QM market to a large number of individuals who become natural candidates for non-QM loans as Fannie Mae and Freddie Mac primarily favor the salaried class.

Soaring Home Prices 

Home prices over the past few years have seen a gradual rise. The mortgage market is generally shifting away from refinances, which made up over 50% of the market in the last 12 months, to a purchase driven market. The demand for large-sized loans has increased – mostly in the form of Non-QM, as the GSE guidelines around investment properties have been disqualifying most candidates for agency loans.

Key Challenges Faced by Lenders in the Non-QM Space

While interest in the market is on the rise, there are challenges for Non-QM loans. Despite the growing interest, the sector does face some basic functional challenges that lenders are required to overcome. The key ones are detailed below-

Managing Error-Prone Manual Processes

Manual processing of Non-QM can lead to errors, longer timelines and higher costs. Non-QM products do tend to be a bit diverse. This makes the requirement of proper technology to streamline tasks and improve efficiency levels across the organization quite a pressing one.  Though there are many generic automation solutions available in the market, Non-QM loans require specialized solutions to get the domain intelligence into the system.

Mitigating Risks of Frauds

Mortgage fraud has been rising steadily in the last decade. Due to a relaxation in DTI ratio and other criteria, it becomes critical for Non-QM providers to have a robust risk and fraud mitigation mechanism.

Dealing with the Changing Cost Structures

When looking at the total number of mortgage units over the last 10 years, the market has fluctuated up or down by up to 50% each year. It’s clear that mortgage is an industry that is subject to high fluctuations. Due to this ambiguity, increasing fixed costs by investing in additional capacity can be a risk.

The pivotal role of specialized document automation technology in overcoming functional challenges

Specialized solutions can help to overcome functional challenges faced in disbursing Non-Qualified Mortgages. Document automation involves using advanced technology such as AI to simplify the lengthy tasks pertaining to disbursing a typical non-QM loan – right from onboarding, processing, underwriting, pricing, packaging, and closing in a cost-effective way.

DocVu.AI – the most innovative AI/ML solution for BFSI* is designed to be workflow-driven and follows the same set of rules that is adhered to when tasks are manually executed. With the use of intelligent algorithms, the solution significantly increases the pace of execution and reduces the probability of costly human errors.

As a result, Non-QM Mortgage lenders gain increased freedom to take on additional workload due to the automation introduced at several points without worrying about capacity constraints. This empowers the lenders to place their undivided focus on core areas for sustainable growth.

*As per IBS Intelligence 2021 ratings

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