AI and the Future of Mortgage Lending
Mortgages, and specifically the mortgage industry, have come a long way over the years.
What once was manual, is now digital.
What previously moved at the pace of 9-5 now moves at the speed of light.
What was once business as usual is now in the business of bold ideas.
In the last several years, a number of incredible technological innovations have helped reimagine the way a loan is processed— from initial application to underwriting to final approval. In the age of acceleration, Artificial Intelligence (AI) is the key ingredient, enabling the creation of new adaptive algorithms that are data sensitive and produce instant, automated, tailored, “smart” results—a breakthrough that is transforming the industry.
And the technology keeps advancing. Machine learning, a subset of AI, is potentially even more transformative, unleashing new possibilities for computers to learn and optimize without explicitly being programmed. The result? An increase in speed, efficiency and accuracy that measurably enhances customer experience, lowers costs, reduces compliance woes and automates a slew of tasks on the back end for mortgage companies.
This is clearly the future for the mortgage industry; one that smart lenders like Guaranteed Rate are leveraging to create a better user experience for you, the borrower.
Not your father's mortgage industry
Once upon a time (which is to say 10 years ago), the mortgage industry had an innovation problem. Brash fintechs were challenging incumbents, Silicon Valley was producing breakthrough technologies at scale but the vast array of lenders were still operating in the past, hesitant to abandon legacy systems, rote processes and an overreliance on manual labor. To capture the business of an increasingly sophisticated consumer and reduce turn times, mortgage providers would need to forge ahead and embrace a faster, more process-efficient and customer-centric business model whose engine was cutting-edge technology.
Digital Mortgage and the next chapter of innovation
Guaranteed Rate’s game-changing release of its industry-first Digital Mortgage went a long way in changing the narrative and delivering to customers the kind of seamless online approach to getting a loan that many had been seeking. Bold and transformative, Digital Mortgage was important in creating an elegant, modern, advanced user experience—but it wasn’t explicitly AI driven.
As a growing number of industries—from finance to aviation to health informatics began to leverage breakthroughs in AI to deliver a broad range of new solutions to their customers, a handful of innovative mortgage providers were increasingly curious if AI and similar technologies could be transformative within the approval and underwriting processes. The competitive advantages were clear, but so too was the opportunity to revolutionize and optimize the marketplace, bringing all aspects of mortgage lending into the 21st century.
Mortgage processing: Problem, meet solution
The mortgage process has historically been defined by paperwork—a dizzying amount of it. Plowing through required documentation and verifying data is not just laborious, but because it relies on manual processes it can potentially produce errors that result in additional delays and customer distress. By introducing smart technology into certain time-intensive processes, tasks can be automated, manual labor can be saved or directed elsewhere and turn times can be shortened—a result that will put a smile on your face and delight your lender as well.
But let’s be clear: These innovations are part and parcel of a larger quantum leap happening throughout the world of computing. Much of this can be attributed to advancements in internet speed, the expansion of memory and computational power and an exponential increase in data storage thanks to a number of innovations, including cloud-based file hosting.
Innovative solutions across the mortgagesphere
In reducing industry pain points, automation was heralded as the key optimizing factor—but you can’t automate simply by “going digital.” You need smarter technology. The inherent innovations in both AI and machine learning (and to a lesser degree, robotic process automation) allow for time-consuming activities to be completed largely without human involvement. This means the gathering, reviewing and verifying of critical mortgage-related documents can be effectively undertaken and resolved by leveraging AI and deploying it across the enterprise.
Rick Lang, COO of Gateless, an innovative mortgage technology company, offered his perspective, “Ultimately, it’s about automation. It’s about reducing friction for all parties throughout the lifecycle of the transaction—customer, lender, investor, everyone. Introducing automation into the mortgage process leads to a superior borrower experience and a cost reduction model available to all participants.“
Terms and tech: AI and similar advancements
Suffice it to say that no matter how hard we try to establish distinctions, “AI” will doubtlessly remain a catchall for any smart computer solution that simulates human behavior and automates tasks. That said, a few basic definitions can be helpful in better understanding AI, machine learning and robotic process automation (RPA).
Let’s take a closer look at the big 3:
- AI (artificial intelligence)* AI is typically defined as the ability of a machine to perform cognitive functions we associate with human minds, such as perceiving, reasoning, learning, interacting with the environment, problem solving, and even exercising creativity. “Reading” and extracting information from a mortgage-related document, for example, would be considered an AI function.
- Machine-learning* algorithms detect patterns and learn how to make predictions and recommendations by processing data and experiences, rather than by receiving explicit programming instruction. Working in predefined areas, machine learning yields results that are:
- Descriptive—it describes what happens
- Predictive—it anticipates what will happen
- Prescriptive—it can provide recommendations on what to do based on past experience (historical data)
- Robotic process automation (RPA) is a productivity tool that allows a user to create scripts (which some refer to as “bots”) to mimic or emulate selected tasks within an overall business or IT process. Unlike AI and machine learning, RPA tasks need to be explicitly programmed by a human. Chat bots are an example of RPA that you’re likely familiar with from a host of online retailers.
It’s worth noting that RPA is more transactionally driven and AI and machine learning are more data driven. We’re not just talking about the collection of data, but the interpretation of it. This is where machine learning is especially useful. Through countless observations, machine learning algorithms build models that essentially teach themselves what to look for and how to do it more effectively—learning, adapting and improving along the way.
Taken together, these advancements can provide measurable value to help automate mortgage processing—and bring more value to you and your lender by:
- Reducing costs for everyone involved
- Closing loans faster
- Eliminating mistakes throughout the process
- Enhancing customer experience
Applying AI to mortgage lending
From the outset, the potential of these innovations to automate tasks related to underwriting has been nothing less than astounding. However, not every lender is equally innovative. Creating bold solutions requires a high mortgage IQ and the unsparing determination to challenge the status quo of existing operations—and perhaps ruffling a few feathers along the way. The ideal solution should be both scalable and customizable, something that can evolve alongside the latest innovations in AI and the most pressing needs in mortgage processing.
Gateless, a new visionary mortgage technology company that provides the industry with efficient solutions to innovate the entire loan process, is one such example.
Gateless, AI and a laboratory for innovation
Upon acquiring artificial intelligence company AI Foundry in 2020, Gateless has emerged as a unique player in the mortgage industry with plans to leverage cutting edge tech to help measurably improve how data is extracted, read, understood and classified. Ultimately, this means bringing clarity, eliminating pain points, closing loans faster while serving more customers.
It’s the type of technology that can ultimately transform an industry. Leaders of Gateless are confident these next-level efficiencies will help all lenders accelerate growth, reduce turn times and improve their ability to scale, leading to lower costs and fewer errors.
By automating a slew of repetitive, manual tasks that are built into the mortgage origination process, lenders can accelerate certain loan-closing and post-closing processes more quickly and better scale their capacity.
At the same time, they can reassign experienced staff to more customer-centric operations, enhancing the quality of service you receive. And that’s important: Loan-processing teams can dispense with burdensome verification and indexing activities with the help of intelligent automation and pivot back to the more human-centric aspects of manufacturing a loan.
“We know the ability to process loans faster and more accurately improves customer satisfaction” said COO Lang. “In turn, a superior customer experience increases the likelihood of more referral business.“
Lang added, “Gateless has the right blend of technology, technologists and mortgage expertise. It’s a winning combination that enables us to create operational efficiencies that benefit both the customer and lender.”
Gateless: Frictionless efficiencies
As Lang has noted, borrowers want to have clear expectations for engagement established upfront—especially when it comes to document submission— and maintained throughout the mortgage process.
By harnessing the right combination of automated decision making and the digital brainpower of AI, lenders can not only better understand what documents to ask borrowers for, but they can automate the interpretation and underwriting of those documents as they are received.
This leads to faster processing, significant cost reductions and timely decisions on loan approval.
“For the borrower, it’s chiefly about a frictionless experience, informed by speed and precision,” said Lang.
Gateless’ AI underwriting platform is designed to:
- Identify and clear conditions needed to approve, close and sell mortgages to investors
- Automate the assessment of information an underwriter will use
- Eliminate task “queue time”
- Create “smart underwriting,” which means:
- Driving intelligent automation of critical underwriting and QC processes
- Enabling document recognition data extraction
- Leveraging automated indexing capabilities
- Working in a symbiotic, complementary way with the processing team.
Note: This summary is not intended to wholly describe the many components of underwriting and post-closing that Gateless’ intelligent automation addresses.
The future of AI and mortgage lending
Along with a faster, cheaper and more precise process, what other advancements can AI unleash in future decades?
Certainly the use of Big Data is only likely to increase, providing ample opportunity for AI and machine learning (and its offshoots, natural language processing and deep learning) to continue to mine digital highways for customer insights. By more aggressively leveraging behavioral analytics, lenders have an opportunity to increasingly personalize and optimize the loan acquisition process for borrowers everywhere. This means a better experience for you. Not only a new level of speed and seamlessness, but a smarter, more targeted way to interact with your lender.
“The AI capabilities available today already outstrip the willingness to adopt them in many corners of the industry,” said Lang. “When it comes to automation and its effect on mortgage processing, you’re only limited by your imagination.”
Will AI signal an end to all built-in biases?
While previous missteps in the mortgage industry—specifically those dealing with discrimination and bias—have been widely acknowledged and addressed by lenders in recent decades, the arrival of AI signals a new opportunity to make the approval process even more fair, inclusive and equitable. But only if handled correctly.
It all starts with the algorithms, who develops them and with what information. Across the industry, lenders typically rely on previous sets of loan data to inform AI systems how to conduct risk analyses. While advanced machine learning can do wonders, it can’t rise to a new level of fairness and inclusivity unless it is exposed to new data sets—equitable data sets freed from the institutional biases of the past.
Therein lies the current challenge within AI mortgage lending. And while the future is still unwritten, a wide array of voices are being brought into the conversation—consumer advocates, technologists, policy makers and regulators—to ensure a lending future that treats all applicants the same regardless of race, class, ethnicity or gender.
AI and lending: A partnership for the future
With fast and frictionless interactions increasingly prioritized in today’s homebuying climate, mortgage providers would do well to review existing processes and see how next-gen technology like AI can unlock new efficiencies, creating a better customer experience for borrowers like you.
While the role of the loan officer remains vitally important to both you and the lender—they serve as both ambassador and customer-facing expert—an increasing portion of the nitty gritty back-end work that helps move a mortgage from application to closing can now be performed by smart operations under the direction of AI and machine learning. That’s transformative.
At this point, it would be sheer folly to bet against the arrival of new technologies and innovations within the mortgage sector in the years ahead. AI is still in its infancy and the possibilities are endless. Gateless is mapping out a robust future and Guaranteed Rate remains equally committed to the promise of fusing technology and expertise to create an optimal customer experience for homebuyers everywhere.