Despite the U.S. mortgage industry’s prominence — it serves more than $13 trillion in debt across about 86 million mortgages — it remains one of the most complex and inefficient financial sectors in the nation’s economy. This is largely because it hasn’t fully embraced the digital transformation that has made other sectors like banking, payments and insurance more structured and consumer-friendly.
As a result, the entire home lending process, from origination and servicing to closing, continues to rely on disconnected systems, manual data entry and outdated workflows. This results in higher costs and greater frustration for customers.
According to the Mortgage Bankers Association (MBA), lenders spend approximately $12,500 to originate a mortgage. These costs are often passed on to customers, making mortgages more expensive and putting homeownership out of reach for many Americans.
The current lending dynamic is also negative for mortgage companies. Even though new originations are estimated to be worth roughly $2 trillion per year, according to LoanLogics calculations on MBA data, lenders are only earning about $2.7 billion in net revenue on that amount — a roughly 4% profit margin.
A mortgage revolution is long overdue. Fortunately, the technology needed to make the industry more efficient and profitable already exists.
Disconnected and risky systems
The mortgage industry today is a complex web of participants across different systems, data standards and workflows. While much of the industry has already invested in sleek borrower-facing websites and apps, little movement has been made to improve the infrastructure underneath these platforms. There’s lots of style, but little substance.
In fact, mortgages mostly still rely on loan origination platforms that were built decades ago with limited application programming interface (API) capabilities, and integrations that are bolted on, not natively designed. It’s like buying a $250,000 sports car and driving it on a 30-year-old road riddled with potholes. It’s difficult to accelerate with bad infrastructure underneath, no matter how much horsepower you have.
Worse than the slowdown is the redundancy. These different systems are often incompatible with one another, meaning that information gets entered multiple times, converted into multiple formats and passed along from company to company. As a result, much of the mortgage process still revolves around document management rather than structured data exchange. The important data in a loan file is held captive in static formats: PDFs, emails, Word documents and even faxed forms. Every time the data changes hands or formats, it must be manually replicated across multiple systems.
This redundancy adds cost and complexity and increases the likelihood that mistakes will arise as data is ported from system to system in a long game of “mortgage telephone.” A single loan file is typically touched by dozens of hands, each of them rechecking or reentering the same information, which results in delays and opportunities for error. This ultimately reduces per-loan profitability.
Cloud-based future
The most important change that needs to happen for the industry is a full migration to cloud-based infrastructure, replacing siloed and gated systems with interoperable platforms that promise secure data, portable files, easy collaboration and simple updating.
On this new foundation, AI-powered automation can handle repetitive, error-prone tasks that take significant time and resources. These include document recognition, income verification, fraud detection and compliance checks, all of which can be automated with higher accuracy and lower cost.
Machine learning models training on millions of data points, sample documents and workflows can flag anomalies, assess borrower risk and even predict which loans are more likely to close. This helps lenders and brokers work more efficiently and close loans faster. Given the scale of the mortgage market, there is significant data to be gathered in all parts of the process. Analyzing this data can better train models and generate insights to further improve efficiency.
With a stronger foundation optimized by smart workflows, collaboration and transparency will become the industry’s new currency. Instead of exchanging static files and emails with partial or incorrect information, brokers, platforms and stakeholders will be able to share data in real time through secure APIs. File audits will be completed once and appended with a digital certificate that can follow the loan throughout its lifetime, eliminating the need for redundant checking activities. Individual loan aggregators, investors and servicers will be able to save countless hours of worktime, allowing individuals and teams to spend more time on higher-value activities or better customer service.
By investing in smart platforms, mortgage originators can save thousands of dollars in origination costs per loan. Across the entire U.S. mortgage market, this translates to billions in potential savings. These cost savings will in turn enable originators to scale up their lending efforts and pass along savings to consumers. Mortgage wholesalers, aggregators, diligence firms and investors can also save thousands of dollars per loan by avoiding the time and resources spent on duplicate audit review, and loan servicers can in turn save hundreds of dollars per loan by automating their workflows.
The mortgage industry is overdue for a foundational reinvention, but the good news is that the technology to make that possible is available right now. The convergence of cloud-based, AI-driven and collaborative platforms offers a path forward that is faster, more secure and more cost-effective. This will ultimately expand U.S. homeownership by making mortgages more accessible and affordable.
Some of the biggest mortgage players are already making moves, and those who embrace technology today will define the standards of efficiency, accuracy and trust that others must follow tomorrow. The mortgage process of the future won’t be measured by paperwork or processing days. It will be defined by data, intelligence and collaboration. The revolution is already underway.
