Mortgage lenders often refer to loan origination as “loan manufacturing.”
Like any assembly process, making a loan requires various components to be brought together to produce a final product. The quality of that product — its suitability, durability and availability — depends on the design of the factory process and access to a steady flow of quality components.
Think of a carmaker building a car. The inputs are metals and plastics, wiring looms and electronics, glass and rubber. The supply chain for these components is critical to manufacturing success.
Disruption to automotive supply chains during the pandemic revealed why a predictable flow of components is so important. When this flow was interrupted, the result was factory slowdowns and stoppages. Carmakers lost revenue as buyers sought alternatives or abandoned purchases altogether.
Supply chain problems similarly threaten mortgage providers. In lending, the components needed to manufacture a mortgage are documents: bank statements, paystubs, W-2s, tax statements, identification documents, and property appraisals. Poor document quality, mistakes, and information gaps hold up the manufacturing process. Origination takes longer or cannot be completed, wasting time and money while delivering poor customer experiences.
Taking Control of the Data Supply Chain
The quality of data that initiates loan origination processes is fundamental to everything that follows: operational productivity, time to close, risk in the lending decision, meeting the demands of the secondary market, profit margins.
And yet, compared with carmakers, mortgage lenders don’t enjoy anything approaching the level of control over their supply chain. Instead, lenders take whatever documents are provided and run quality checks. They must extract data about the borrower, assess the veracity of the documents, and verify the accuracy of the data extraction process itself.
Mortgage operations professionals know that conversion of documents into data and data verification are laborious, complex yet mission-critical tasks. The result is a data bottleneck as the need for quality is inevitably restricted by human capacity and accuracy. In addition to creating risk, inaccurate data raises costs further along the production line. When accuracy is off by just 5 percent, productivity decreases by 30 percent or more.
The data bottleneck has long frustrated operations leaders, but solutions have been hard to find. Expanding in-house teams was traditionally the best option for adding capacity without compromising quality, but this loads the business with highly salaried employees – not ideal at a time of volatile demand.
Outsourcing offers flexible capacity, but quality is harder to manage and labor costs are rarely reduced. Offshoring used to be a lower-cost option, but fees have risen as other economies have matured. Meanwhile, there’s increased concern about the risks of transferring customer data overseas.
Specialized Technology for Skilled Tasks
Returning to our manufacturing analogy, carmakers have successfully used automation —robotics — to boost productivity when human skills are unavailable or too costly. Many lenders have also invested in mortgage loan automation platforms with a goal of achieving touchless automation. But the docs-to-data and verification components of these systems have disappointed with poor accuracy. Human specialists are routinely needed to step in and figure things out.
Constant human monitoring of automation technology undermines its core value. Operations leaders are left to figure out some awkward combination of people and technology in the hopes of increasing productivity or else give up on automation altogether.
Some lenders have discovered a different option: TRUE.
TRUE provides task-focused artificial intelligence for docs-to-data conversion and verification. Like skilled human operatives, the TRUE technology is trained in the lifecycle and language of loans. It is uniquely able to review documents contextually, seeing the connections between the borrower and their data, and building a complete picture.
This allows TRUE products for docs-to-data conversion and data verification tasks to slot neatly into data supply chain processes and deliver fully automated performance, with no humans in the loop.
Task specialization means TRUE products consistently surpass human performance. The AI models have been trained on lending industry data, so they deliver at least 90 percent accuracy out of the box
The AI improves on this foundation, learning the specific needs of different lenders and loan manufacturing processes, so accuracy levels exceed 99 percent within a matter of months.
Soon enough, operations leaders see that they can trust the accuracy of automated data, allowing them to redeploy skilled human resources to where they can add more value.
With TRUE, lenders can efficiently scale up in busy times without the burden of high fixed costs in fallow periods. The result is a mortgage-making factory that’s in control of its data supply chain, ensuring consistent quality and readily adapting to demand.
5 Ways TRUE Helps Operations Teams
Operations professionals in the mortgage industry face a constant tension between speed and risk. Processing loan applications or reviewing portfolios rapidly while ensuring accuracy and compliance is an endless challenge.
The first stage of the loan manufacturing process — constructing a picture of the borrower — is often the most demanding. The information needed to build loans is buried in hundreds of documents. Extracting that data is a highly manual and error-prone task. It’s laborious and costly, but data quality is critical in making sound lending decisions.
With TRUE, lenders gain a reliable flow of clean data that improves both loan quality and the customer experience. Here are 5 ways that TRUE helps operations teams:
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Build an Elastic Business Model
Falling volumes and the need to reduce operating costs mean that many lenders have no option but to reduce headcount. This inevitably sets up the next challenge: rehiring as volumes rebound. While volumes are low, operations leaders have a window of opportunity to improve how their business accommodates fluctuating demand.
Enter TRUE, with AI that intentionally interrupts the link between loan demand and staffing. Unlike earlier document processing technologies, TRUE is built for lending and is proven to be 99-percent accurate. This allows lenders to scale up and down without hiring or firing — resulting in lower, more predictable costs and a more elastic business model.
Turn Mountains into Molehills
Operations professionals know that docs-to-data conversion is a bottleneck. When applications spike, lending professionals are swamped with all kinds of borrow documents.
Mortgage demand has been on a wild ride in recent years. The pace and scale of change increases the tension between loan manufacturing speed and quality. However, AI can automate the docs-to-data task in its entirety.
TRUE Data Intelligence was made for this challenge. What used to be hours of work per loan is performed in minutes. Since TRUE runs 24/7 without breaks, mountains of work are reduced to molehills.
Restore the Focus on Underwriting
A recent Accenture report found that the average underwriter spends 70 percent of their time on non-underwriting activities like admin and sales support. Inefficient, manual processes are largely to blame.
While underwriters will always need to devote some time to other functions, using TRUE Data Intelligence to capture data about borrowers ensures that operations teams can prioritize underwriting quality even as demand for loans shifts.
Quick and accurate document automation for underwriting, without humans in the loop, changes the game. The elimination of manual processes saves time and money while freeing underwriters to focus on quality. With the value of underwriting back in the forefront, the role becomes more rewarding and more effective. Profit margins rise as risk falls.
Holistic and Hidden Insights
When lending professionals process documents manually, they only have time to consider the data that’s essential to underwriting and the decision making process. Getting loans through the pipeline quickly and accurately means that lots of valuable information is routinely overlooked.
Using TRUE Data Intelligence for docs-to-data conversion allows richer data to be captured without any increase in time or expense. The AI scans every field of every document, building holistic borrower profiles that are the cornerstone of lending intelligence.
That intelligence has immediate and longer-term benefits. Holistic understanding of borrowers roots out errors and fraud, increasing confidence for every lending decision. The additional data is also a treasure trove for data scientists — creating new opportunities to identify trends, reduce risk, boost revenues, and surface hidden fraud. Lenders can optimize processes, enhance business outcomes, and find innovative ways to stay competitive.
Trust Data that is TRUE
TRUE is not the first technology promising to automate docs-to-data and verification tasks, but it is the only one that keeps its promises. Operations professionals have been underwhelmed by the tools that are packaged with loan automation platforms. Even AI-based solutions struggle to make an impact if they are not trained on documents and processes used in lending and mortgages.
TRUE offers the only AI solutions capable of full automation. TRUE Data Intelligence works throughout loan origination, ensuring the quality of the docs-to-data conversion while checking for any anomalies before manufacturing moves to the next stage. TRUE Data Verification is used by loan servicing businesses, allowing them to examine the quality of entire portfolios — not just limited samples — in hours rather than days.
Customer Perspectives: Real-World Experiences of Operations Teams
As interest rates rise and mortgage application volumes decline, operations costs can be stubbornly inflexible. Indeed, cost-per-loan can easily increase because you’re paying the same number of people to process fewer applications.
While this downturn in activity is certainly challenging, it’s also an opportunity for operations leaders to make smart investments in technology that can address these recurring issues and make the business fit for a return in volumes.
With that in mind, let’s examine 4 of the most common challenges we hear from the operations teams among our clients — and how TRUE solves each of them.
Minimizing cost per loan
Cost-per-loan is one of the most important metrics for any mortgage operations leader. But despite investments in technology — including loan origination systems and robotic process automation — mortgage manufacturing costs continue to increase. The core of the problem is not with these systems or processes but the data that feeds them.
This is the specific problem TRUE solves.
TRUE’s powerful AI engines enable operations teams to automate the extraction of data from PDFs and scanned physical documents with impressive accuracy. Contextual analytics avoids common OCR problems, allowing AI to correctly categorize unfamiliar document designs, cope with poor quality scans, and recognize the difference between B and 8 or 1 and l. This reduces the need for manual reviews by as much as 85 percent, allowing operations teams to make better lending decisions faster.
Optimizing headcount
Determining staffing levels is a persistent challenge for our clients. There are so many variables affecting both incoming volumes and employee availability. Many operations leaders build models to predict throughput and balance that against headcount, overtime, and outsourcing needs. When the models are wrong, the impact is seen on the bottom line.
TRUE takes this problem away entirely.
The speed and accuracy of our docs-to-data technology lets users scale to accommodate fluctuating volumes without adding people or incurring overtime expenses. When TRUE takes care of data extraction, the same number of underwriters can process more loans each day, bolstering the bottom line.
Decreasing defect rates
Even the best trained and most experienced loan professionals make mistakes extracting data from documents. Thanks to AI, TRUE achieves near-perfect accuracy in docs-to-data conversion, something that’s hard for customers to believe at first.
While there’s a lot of skepticism about automation and AI, TRUE prides itself on the consistent high performance of our machine learning models. They work out-of-the-box and continuously improve.
Recently, a client called us to an urgent meeting because TRUE had made 50 errors on one data field. Clearly, the machine was broken, the client thought. But was it?
It turned out that 50 errors were made across 75,000 documents, and our software predicted and identified these errors. In normal circumstances, the human error rate for the same volume hovered around 15 percent, or 11,250 errors. Since humans don’t always report on their errors, they would have likely gone unnoticed until much later in the manufacturing process. This side-by-side comparison helped our client to appreciate just how much accuracy had improved thanks to TRUE.
Managing seasonality
The mortgage industry is largely driven by seasonality, another elasticity challenge. On top of the usual annual cycle, the industry is experiencing an especially quiet period due to a cooling housing market and rising interest rates. Operations leaders need to determine when to staff up and by how much.
Our clients know that staffing can be the difference between profit or loss, the enabler or blocker to growth. Staffing also plays a huge role in shaping the customer experience and brand reputation. With cost-per-loan metrics rising — and hiring and outsourcing becoming more challenging — adapting to seasonal cycles is tougher than ever.
TRUE offers more than a short-term solution. It gives operations leaders a way to fundamentally change the elasticity of their operations, minimizing the impacts of seasonality and cycles.
Empowering Operations Teams with TRUE
Mortgage lenders are under pressure on multiple fronts. The economy is changing, housing markets are evolving, and customer expectations are rising. This makes it the right time to invest in technology that increases performance today and introduces efficient elasticity for the long-term.
Returning to our car manufacturing analogy, when a carmaker seeks to increase automation in its processes it selects machinery that is customized to the task and then carefully hones it to the specifics of its operations. The right selection and integration of technology transforms operational outcomes and makes them fit for the future.
Operations teams in mortgage lenders need to be similarly discerning when selecting technology designed to improve loan manufacturing process. Many lenders have made investments in loan origination systems and even robotic process automation that has potential to deliver transformative outcomes, but the time and cost bottlenecks in the data supply chain are hampering progress. Lenders need to pick a solution purpose-built for the challenges they face.
TRUE is the only vendor on the market with AI-powered data automation solutions designed for the mortgage industry that extract and analyze data with a 99-percent accuracy rate. TRUE offers two products that can help operations professionals:
TRUE Data Intelligence,
which automates the docs-to-data process and automatically checks for errors in the data before passing a loan application to the next stage.TRUE Data Verification,