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Mortgage Lenders Turn to Automation and AI to Solve the New Challenges of Today’s Hot Housing Market

by | Nov 30, 2021

Mortgage Lenders Automation

Automated Mortgage Lending

This blog post is taken from the InRule report, Supercharged Lending. Download your complimentary copy today.

Mortgage lending is in the midst of a revolution—and it will be fought with machine learning algorithms and automated decisioning.

The housing market is hot right now. Not only are home prices up 20.6% year-over-year, but the average cost-per-home is up 24.8% over the same period. While those are amazing market conditions that mortgage lenders dream about, the fact is that this tremendous opportunity is coupled with fierce competition. And, with inflation rising and uncertainties created by the pandemic, no one knows how long this boom will last.

So, the goal for today’s lenders is clear: capture as much market share as possible right now and beat their rivals to every new mortgage. This requires speed—while maintaining accuracy to drive sound business decisions—at a level that legacy processes aren’t adequately built to handle.

How will they accelerate their operations? A growing number of lenders are discovering that artificial intelligence, including machine learning and automated decisioning, can be the answer.

Shifting consumer preferences are changing the game

Unfortunately, just as the mortgage industry is entering one of the most significant periods of opportunity in recent years, things are getting harder. New customer expectations, driven by the Digital Age, are creating disruption that lenders must navigate.

Today’s most prominent group of new home buyers, digital-native Millennials, have new preferences for what they want and expect from the mortgage lending process. As we’ve seen in other financial services in recent years (banking, investing, and insurance), customers desire more frictionless, self-service options rather than slow, in-person ways of doing things. They want to do business within apps—safely, securely, and when they’re ready to transact, whether it’s day or night. 

Next to price, home borrowers cite speed as the top requirement of their lender, so shortening mortgage approval time cycles are vital to winning in this ultra-competitive market. Lenders unable to align with these digital customers’ new needs will simply lose business to savvier, more nimble rivals.

While these new challenges are giant hurdles for lenders to overcome, there’s yet another problem the industry faces: there just aren’t enough loan officers to handle the influx of mortgage volume. 

“The mortgage business is feast or famine,” explains Cecilia Janson, a partner and Chief Delivery Officer for the mortgage industry consulting firm BlackFin Group, “and right now the market is red hot. Lenders are trying to take advantage of this and close all the business they can. But for their staffs, the increased loan volume is leading to burnout and underwriter exhaustion.”

Lenders are turning to automation-driven processes, including enhanced by machine learning, to meet these new customer expectations. They give customers the timing and convenience they desire while also freeing up staff time to focus on more important and meaningful strategic tasks.

The InRule Advantage: Powering half of all 2020 US mortgages

The approval processes for nearly 50% of U.S. mortgages originated in 2020 were powered by InRule. Lenders turn to the company for its software technology, which allows them to quickly respond to changing market conditions and jump on new opportunities while reducing risk. 

Mortgage Lending Powered by InRule

Mortgage Lending Powered by InRule

The InRule platform does this by automating decision logic and providing value across the

loan lifecycle, including:

  • Loan origination, documentation, and customer self-service.
  • Approval decisions related to income, key ratios, and credit rating, as well as other factors.
  • Part or all of the underwriting process, including consideration of credit reputation, debt capacity, and quality of collateral.
  • Closing procedures, such as the routing of documents and ensuring compliance with disclosure requirements.
  • Routine loan servicing tasks, such as determining payment status and delivering statements.
  • Cross-selling and upselling customers by automatically notifying them of rate changes, new products, and other money-saving opportunities.

Now is the time to upgrade your operations with automation-driven processes, enhanced by machine learning

Since 2002, leading firms have relied on InRule to empower technical and non-technical users to manage complex business decisions—without code.

Power up your lending operations with explainable, AI-powered​ end-to-end automation to take advantage of today’s golden opportunity in the mortgage industry.

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