Lending, Open Banking
How AI Is Helping Lenders Meet High Demand with Open Banking Data
While the chaos of 2020 wreaked havoc in many industries, the housing and mortgage markets boomed. Mortgage rates set 15 records in a single year as they dropped, encouraging equally record-breaking volume. In mid-December, mortgage applications were 26% higher than the previous year, while refinancing applications were up 105% from 2019. With rates still low, demand remains high, even with climbing costs and low inventory. On top of all the widespread adaptation required last year across the board, lenders have been sprinting to keep up with this high demand. The solution? Accelerated digitization of the lending process.
And artificial intelligence (AI) is opening the door to even more possibilities.
New Trends In The Mortgage Lending Market
Volume trends in the mortgage lending market are continuing in 2021. Bankrate reported that the slowdown usually experienced by the market in the winter was far less noticeable this year, which implies that the first quarters of ‘21 will continue to see high demand.
Low rates haven’t been the only factor driving high mortgage lending volume. As social distancing became the norm across much of the economy, employees worked from home. And even as coronavirus cases dropped in some areas, many companies announced a transition to long-term and even permanent work-from-home. This transformation has encouraged some employees, who were previously restrained by a daily commute, to move into a new home. As Bankrate puts it, “demand is especially high in neighborhoods outside of downtown city cores, as increasing work from home and virtual learning requirements have driven many homeowners to favor space over on-the-doorstep amenities.”
High demand, for all its reasons, is butting up against rising costs and low inventory. Low rates appear to be sufficient to encourage continued sales, despite median home prices now rising above $340,000. This combination of factors means that we’re likely to see a competitive housing market persist over the coming months.
On top of factors driving high demand, other trends in the mortgage lending market are fostering change. For example, social distancing, quarantines, and lockdowns increased consumer adoption of digital and remote solutions. US ecommerce sales jumped 37% by Q3 2020. Utilization of telemedicine and remote diagnostics increased. Remote education relied on digital learning solutions, as well as virtual communication tools like Zoom. Consumers, especially digital natives, were already expecting and becoming accustomed to digital solutions in many industries. Why wouldn’t they expect the same in mortgage lending?
The Digital Mortgage: How Mortgage Companies Are Adapting
With demand and market competition so hot, lenders are looking for ways to streamline their processes and keep up with consumers and potential homebuyers. The solution? Digital adoption.
In this high-demand mortgage lending market, mortgage companies may need one thing above all else: time. They need to cut cycle times, allowing for more loans to be processed. They need to save borrowers time to keep them satisfied. Traditional paper-based mortgage processes tend to take more time and involve more friction. Digital mortgages, on the other hand, streamline not only the mortgage application, but the entire lending process, removing high-friction back-and-forth with borrowers through digital verification solutions.
Digital verification solutions enable mortgage companies to adapt to high volumes and empower consumers along the way. Where paper-based verifications require borrowers to dig up old documents to verify creditworthiness, digital solutions powered by open banking, AI, and consumer-permissioned data, allow borrowers to quickly and securely share all the financial data necessary to get them a loan. Digital verifications enable mortgage lenders to automate and streamline workflows, all while delivering borrowers with a convenient, simple, digital-first experience.
In addition to challenges revolving around time, today’s mortgage lenders are facing another issue in a physically-distanced world: trust. Borrowers are frequently navigating the mortgage application process or refinancing remotely, without meeting agents, sellers, buyers, and loan originators. Lenders can empower borrowers with a consumer-centric experience that enables them to control and benefit from their financial data. Layer that with secure, consumer-centric data sharing principles and protocols and lenders can build with borrowers valuable relationships founded on trust.
Some mortgage companies implement a digital solution here and there, but there’s a difference between doing digital and being digital. Any digital solution will of course help streamline processes and update workflows, but a completely digital workflow informed by a company-wide digital-first strategy enhances mortgage companies with consumer-first experiences that accelerate growth and increase ROI.
Why High Demand For Mortgages Needs A Digital Mortgage Solution
Digital mortgage solutions streamline the verification process and, by extension, the entire origination process. That streamlining cuts time from the origination and leaves more time to process more loans. A necessity in today’s high-demand market. As Allen Taylor of Lending Times notes, leveraging digital solutions and AI models will “likely drive the greatest overall efficiencies, both reducing costs and boosting revenues. This enhanced efficiency can be used to drive competitive position and ultimately higher profits.”
As purchase volume and demand rises, so do chances of fraud and risk. Fortunately, digital mortgage solutions reduce fraud and overall risk by connecting directly to secure financial institutions and getting the most accurate data from the most reliable sources.
How Digital Verification Is Facilitated By AI
The digital verification enabling streamlined digital mortgage owes part of its efficiency to artificial intelligence. This doesn’t mean that Watson or Alexa are performing your digital income verification. Instead, artificial intelligence leverages machine learning, deep learning, and neural networks to mimic human intelligence and predict, optimize, and automate tasks that were once performed manually.
As IBM explains, “Perhaps the easiest way to think about artificial intelligence, machine learning, neural networks, and deep learning is to think of them like Russian nesting dolls. Each is essentially a component of the prior term.” In brief, fundamental terms, here’s more on each AI component:
- Neural network – Algorithms that mimic the neurons of a human brain. Consist of an input, weights (how correct or incorrect the input is relative to the task), a bias (or a threshold), and an output.
- Deep learning – A multi-layered neural network. With more layers, artificial intelligence can produce a more accurate output from data fed into the network’s input.
- Machine learning – Deep learning is a subset of machine learning, which is fundamentally the “practice of using algorithms to parse data, learn from it, and then make a determination or prediction about something in the world.” The machine learns to perform a task instead of being run through hand-coded software routines. “Classical” machine learning involves training the machine learning model to learn based on specific, labeled datasets fed in so the AI can distinguish between data inputs. This is also called “supervised learning.” “Deep” or “unsupervised” machine learning, on the other hand, involves AI learning without a labeled dataset by identifying patterns in data inputs.
In mortgage lending specifically, AI performs income, employment, and asset verification after a lender connects to a borrower’s bank accounts following a consumer permissioning experience. Once the consumer gives the borrower permission to access their financial data, that data enters the AI’s machine learning algorithm and the AI outputs information based on the task. For example, digital income verification involves the AI recognizing an income stream from financial transactions, and cleaning and categorizing data for a clear output that displays a borrower’s income situation.
Digital verification, powered by AI, automates what loan officers and underwriters once had to do manually. That automation enables lenders to, according to Forbes, “reduce underwriting overhead and delays, which increases profits per loan.” In fact, Fannie Mae has found that digital, AI solutions save up to 8 days for asset validation and up to 12 days for income and employment validation. Ultimately, AI-powered digital verification enhances the entire lending process, delivering a more streamlined experience for customers, and reducing risk while increasing ROI for lenders.
Finicity Can Help Your Mortgage Company Improve Their Process: Here’s How
Through our Finicity Lend solution set, we leverage AI capabilities to help lenders meet high demand. Our open banking platform, powered in part by artificial intelligence, identifies tradestreams in consumer-permissioned financial data and delivers cleaned data, ranked by confidence, in easy-to-read reports to lenders. Finicity Lend delivers valuable real-time data insights on:
- Cash Flow
- Scoring Attributes
These data solutions not only streamline the lending process and better enable lenders to meet high demand, but they also reduce risk and improve loans by enhancing decisioning. Finicity’s real-time data connections ensure high accuracy so that you get the clearest picture of a borrower’s financial situation.
And in addition to the standard verification of income, employment, and assets, lenders can also get a more comprehensive view of a borrower with Cash Flow analytics. Cash Flow leverages artificial intelligence to identify tradestreams not traditionally considered in risk assessment, but that enhance a lender’s understanding of a borrower’s financial habits with a clear view of how money moves in and out of borrower accounts.
We want to make sure you get the most out of Finicity Lend and that your mortgage company can help its lending process reach its greatest potential. To that end, we offer best practices training to facilitate a smooth integration of Finicity solutions into mortgage platforms and an effective transition to a fully-digital mortgage process. We’re not just here to offer products; we’re here to be a resource so you can get the best results.
Artificial intelligence is helping lenders integrate digital mortgage solutions that don’t just meet high demand, but dominate it. With the all-star team-up of AI and open banking platforms, consumers can benefit from their financial data and increase their chances of getting a home loan, and lenders can enjoy enhanced decisioning and ROI, as well as an innovative workflow that hones their competitive edge. Don’t take our word for it. Check out Finicity Lend and see for yourself what AI can do for you.