Editor's note: This story was originally featured in the December issue of MReport, out now.
Just over 45 years ago, Intel introduced the first microprocessor. Ten years later, the personal computer was making its way into American households. Another decade gave us the first internet users, and in recent years the combination of faster processing power, cloud computing, and advanced analytics has changed everything from baseball to business, including the real estate and mortgage finance industries. At RoundPoint, we’ve seen remarkable changes in our ability to both gather and interpret data, which has improved every facet of our company—from adding new efficiencies to dramatically enhancing our ability to provide top-notch customer service/experience. But one thing that hasn’t changed is our belief that while technology and new analytical approaches are critical to the success of our business, the mortgage industry remains a “people” business.
Perhaps more than any other business/technology innovator, Apple Founder Steve Jobs understood the relationship between computers and people, and never lost sight that one could never succeed without the other—both would only realize their full potential by working together. “It’s not a faith in technology,” he said. “It’s a faith in people.” As we examine how new analytical approaches have revolutionized the origination/servicing industries, we would do well to keep Jobs’ words in mind.
No More Gut Feelings
First, let’s look at what kind of data mortgage servicers collect, and how that has changed in just the past 10 years. The data can be separated into two broad categories: loan level and operational data. Loan-level data is just that—detailed information that is key for servicers and subservicers that purchase loans and mortgage-servicing rights. That data is critical for helping companies make sense of their portfolios, utilizing modeling and projection systems to determine appropriate levels of risk and begin to understand and predict consumer behavior.
Operational data focuses on activity done by either employees or vendors, with an eye on improving efficiencies. By having a clear idea of how much it costs to originate a loan, lenders can spot and streamline any inefficiencies, passing the savings on to the consumer. At RoundPoint, it is vital that we know how successful our customer service representatives are with customers, so we track how quickly inbound calls are answered, how often calls are abandoned by customers, and how quickly we respond to phone calls and emails. We also keep a close eye on our vendors, and collect as much data as possible so we can ensure that standards are always maintained.
While those fairly new to the industry may not be impressed or surprised by this, those of us who have been in the industry for a while recognize the fundamental shift over the last decade. No longer does our industry rely on hunches, gut feelings, or scattered and antiquated tracking systems when it comes to delivering first-rate service and maximizing our efforts. Now it starts at the loan level: having centralized systems that monitor credit, income, and assets combined with prepayment or credit/default levels, is crucial to modeling events such as refinances or defaults accurately.
Additionally, modern data tracking and analysis extend well beyond origination. Today’s mortgage servicer is much more than just a bill collector. In order to be a trusted and valuable resource for the customer, servicers must track more information once the customer is in the system. What are their communication preferences? Do they prefer to be contacted via email or phone, and at what times of day? All of that goes to the customer experience and helps us reduce costs by letting our customers “self-service” their loan. Instead of a one-size-fits-all model that was the standard a generation ago, we can interact with customers according to how they prefer to be reached. That benefits the company by increasing efficiencies, but more importantly, makes good on a promise to put the customer first, and provide a truly tailored service that treats them as more than just a loan file.
One of the biggest benefits of loan level and operational data tracking and analysis is better portfolio management and loan predictability, crucial in today’s market, which is characterized by ever-tightening margins. Lenders and servicers also face tough scrutiny from regulators, and having a firm grasp on your portfolio isn’t a luxury—it’s a must. At RoundPoint, our data collection and analytics give us the ability to closely monitor our portfolio, identify troubled borrowers earlier, and spend our resources more effectively in contacting our customers. For a servicer, it is impossible to understate the importance of being able to know who to contact and when. By the time many borrowers reach default, their (and our) options are already limited.
In addition to better predicting the needs of our current customers, having actionable intelligence allows us to more accurately anticipate consumer behavior. That intelligence comes in several different forms of data, starting with traditional metrics like credit scores and payment history. Dig deeper and you’ll find what’s called “trended” data, giving lenders and servicers up to 30 months of payment histories, debt levels, and more. More recently, we are now seeing the value to both lender/servicer and borrower to including alternative data to gather a more complete picture of borrower and consumer behavior. That data could include club memberships, like Netflix, or tax/deed records, payday loans, and more. Now we truly have a 360-degree view of a borrower’s financial situation, and we’re able to proactively respond with products and services to meet their needs.
Finally, by acquiring and maintaining this data, mortgage companies like RoundPoint are able to maximize our resources, waste less time and effort, and pass savings onto customers while protecting our margins. That includes providing improved workflow—by better managing and understanding our portfolio, we can anticipate and take action on loans that might represent exceptions and require more man-hours to resolve. Prior to the advent of advanced analytics, mortgage companies would have to go to great (and expensive) lengths to gather similar data sets. Large-scale polling and complex escrow analysis are now replaced with instant and streaming analytics that help us with critical decision-making. We can zero in on small populations of troubled borrowers. It’s not just the large-scale polling and speed, however—the granular nature of this process is incredibly important, particularly as companies and their portfolios grow. Bottom line: you can’t look at every loan, so knowing the state of your portfolio at a glance is crucial to reducing the cost per loan to service, and to accomplishing more with the same amount of staff.
The Future of Analytics
Despite ongoing challenges with data security and cyber attacks, the biggest danger (to the company and your borrowers) is in not embracing advanced analytics. Like a baseball team clinging to simple metrics that don’t give a complete picture of the true value of a player, mortgage lenders and servicers must be willing to embrace new technologies, including artificial intelligence, which is rapidly changing how mortgages are marketed, originated, and even serviced. Many originators see the adoption of AI by the industry as a threat; however, both origination and servicing businesses will find that no computer will ever be able to serve customers (humans, that is) perfectly. It will continue to take the combined efforts of highly trained and committed staff and increasingly sophisticated technology to originate or service mortgages. Analytic systems will assist mortgage firms in knowing when to contact borrowers or prospective borrowers with what products or services. Staff will be key, however, in delivering that message, and in assisting customers with complex challenges. The mortgage business has always been, and will continue to be a “people” business. But we will continue to benefit from increasingly powerful programs to assist in data collection, interpretation, and analysis.