Mortgage lenders are eager to tap into a market flooded with young, first-time buyers and high-income earners. Data from the National Association of Realtors reveals that statistically, the average US homebuyer is most likely to be married, a first-time purchaser, and under 36 years of age. In addition, buyers between the age of 37-51 averaged a six-figure income of $106,000.

With mortgage rates low, and buying power increasing across younger generations looking to acquire wealth-generating assets, lenders are searching for ways to efficiently close mortgages. To answer this need, new solutions are emerging which leverage artificial intelligence and machine learning to speed the loan process, perform comprehensive risk analyses and secure mortgages for borrowers. Lenders that effectively automate mortgage loan processes can expect to reap the following benefits:

Improved Data Entry

Processing a loan requires paging through piles of documents, reports and other paperwork, which costs valuable man hours. Automated services can upload and analyze documents, sparing the time and attention of workers, who can redirect their focus to vital tasks. Allowing machines to handle data entry also removes the possibility of human error causing mis-typed or incorrect information.

Faster Processing Time

The ability to supply expedited lending decisions is a definite advantage, especially when multiple firms are competing for borrowers’ business. Manually wading through a sea of information involved in the loan process can draw out turnaround times, which can be a deal-breaker for customers. By quickly pulling credit reports, transaction histories and other relevant info, automated systems dramatically reduce the amount of time it takes to approve a mortgage.

Lower Operating Costs

Costs associated with physically printing documents and training staff to manually input data can be significant. Relying on automated systems doesn’t just eliminate those expenses; it also saves on losses incurred due to human error. Using automated systems that integrate with lenders’ current software, the bulk of those savings can be passed to customers.

As the market continues to shift, lenders must evolve their practices to suit the needs of a new generation of borrowers. A prime expectation is that mortgages can be closed without excessive delay. Over time, increased investment will lower the overhead costs of automated lending systems. The amount of wait time that borrowers consider excessive will shift, as more lenders adopt AI-based solutions. Streamlining the loan process via automation won’t necessarily solve industry challenges such as maintaining compliance with federal and state regulations, however, startups such as Unisource are developing which offer AI-based systems that help mortgage lenders adapt to regulatory changes.