Point of View

Get inspiration on data monetization from Ellie Mae and Persistent’s innovative and client-focused mortgage initiative

July 30, 2020

HFS expects the US mortgage market to be worth nearly $3 trillion in 2020, the second-largest annual volume in US history. Over 43% of processed mortgages flow through Ellie Mae, a cloud-based mortgage technology company that serves lenders, and is focused on automating and streamlining, originating, and funding new mortgages while ensuring regulatory compliance. Ellie Mae’s success is rooted in a simple philosophy: Automate everything automatable in the residential mortgage industry. To do this, the firm needed a partner that was aligned with their mission and had the technical expertise to bring viable solutions to the table. Business, data, and analytics leaders will find great value in Ellie Mae’s example of data modernization.


Automating in the mortgage industry means coming to grips with complex processes and mining mountains of data


Ellie Mae’s mantra is straightforward enough, but behind it sits a profoundly complex world. Many of us don’t realize how these complicated financial instruments are processed from origination to funding. The average mortgage application, for example, can have over 20,000 fields in it that range from financial and property information to details on regulatory compliance. Regulatory compliance in the US has hundreds of variations, with different flavors by state, county, and city thrown into the mix. What is left for Ellie Mae is a very rich but complex data pool.


At HFS, our industry research has pointed to the biggest challenge in mortgage origination revolving around data and documents (see Exhibit 1). Loan applications have gone digital, and buyers submit most of the required documentation electronically. However, lenders must still move documentation through the origination process life cycle, which is fraught with complications, including the quality, validation, and verification of borrower-submitted documents. This document data challenge is an emerging opportunity for automation to improve services and different ecosystem partners to offer enhanced data and analytics-based services. Ellie Mae’s example is exactly where we see the industry going.


Exhibit 1: The mortgage data problem: Cycle times are impacted due to information processing

Source: Mortgage Lender Sentiment Survey, 2018, Fannie Mae



For Manish Garg, who runs the firm’s data and analytics group, the mortgage data and process present an opportunity. First, it helps drive greater automation, and second, it assists Ellie Mae with its broader goal of helping solve customer challenges. Its customers—the mortgage sellers, buyers, and financiers—have a long wish list, and Manish is determined to tick as much of it off as possible. With the help of Persistent Systems, the partners are teaming up to bring high-value solutions to market. Ellie Mae and Persistent have worked together for several years on a wide variety of solutions, and by now, according to Manish, they no longer feel like external partners but instead a natural extension of his team.


“When working with a partner, it’s essential to make sure our work culture melded. We have an open, innovative culture, and we want to work with partners that are similar. With the Persistent team, it doesn’t seem like a different company or team, but one fluid, natural fit for us.”

—Manish Garg, Vice President, Product Management, User Experience and Data Science, Ellie Mae


But that’s not to say the journey was smooth for Persistent and Ellie Mae. To get where they are today, the partners had to overcome a raft of challenges. Ellie Mae’s platform allows its clients to see the end-to-end journey of a loan; it brings customers into the pipeline, nurtures leads, and converts leads into applications before moving through the entire loan funding life cycle. The platform then closes loans out and sells them in secondary markets. As a result, Ellie Mae’s client base varies considerably; each has a different set of challenges to solve to drive more revenue, boost speed, and reduce costs. During our landscape assessment, it became clear that data’s importance is increasing, and while broader enterprise appetite for better analytics and data management is increasing, there are significant hurdles to overcome before businesses can derive real value.


According to Manish, the first challenge is building a robust data platform—reliable, scalable, and secure—which is a very complex undertaking. Once Persistent supports this platform’s development, the next challenge is a very human one. Having all of the data at your fingertips sounds like an advantage, but humans can only process finite amounts of information. Designing solutions that extract meaningful data insights is the next challenge. Ellie Mae tackles this gargantuan task by focusing on the core of what its clients want. With a wealth of experience in the industry and a collaborative technical partner in tow, Ellie Mae leverages its deep understanding of what customers might want and works with them to solve that challenge, in the process narrowing the scope so the team can focus on high-value solutions rather than trying to solve for every business problem.


Too many leaders try to solve every challenge at once, but success is prioritizing clients’ specific problems and then iteratively solving each one

After Ellie Mae and Persistent designed their approach, they created an ordered list of solutions for their clients. How did they build the solution? First, Manish maintains, there are some areas where it’s impossible to compromise. In this industry, regulatory compliance is non-negotiable, and Ellie Mae must both remain compliant and help its clients navigate myriad regulations and legalities. So, when Ellie Mae enlisted Persistent to support the project, the companies needed to bake-in that mindset from day one.


“For our customers, simplicity and usability are key. It needs to be the same as when plugging in an appliance at home. People just want to access the electricity; they don’t want to have to invest in and build their own grid.”


—Manish Garg, Vice President, Product Management, User Experience and Data Science, Ellie Mae


On that foundation, the team built infrastructure to tackle immediate challenges while offering flexibility and scalability to build new solutions when needed. The system’s foundational plumbing aggregates data from different systems into a growing data lake. The team can then quickly build value-add applications and surface the data in different ways based on client needs. Ellie Mae gained key capabilities by working with Persistent at this level.

Ellie Mae modernized its data stack using AWS


With the original on-prem architecture, lenders had no simple way to express data requirements, and there were severe performance and cost challenges with the data processing pipelines. Persistent helped Ellie Mae modernize its data stack by moving to AWS. The team set up a customer-centric relational database in the cloud, keeping data secure and compliant. Every request that comes in from clients now goes straight into the new data lake, and the process pulls need-based datasets each customer. Persistent brought in one of its technology partners, Snowflake, to help Ellie Mae separate each client’s cloud storage use, and it developed a pay-as-you-go model for its applications.


Value-added applications help surface meaningful data insights


With the foundational data infrastructure in place, Ellie Mae and Persistent then executed their vision to serve customers better. The first two products out of this partnership include


  • Encompass Data Connect: With its new data lake and digitization capabilities, the company can offer clients simple, cloud-based access to their curated and encrypted data. There is a strong emphasis on self-service, as lenders rely less on IT teams to process the data. With clean, curated datasets, report developers can use the information to make business decisions.


  • Ellie Mae Insights: The Encompass Data Connect product helps lenders get cleaner views into the loan applications they receive. Ellie Mae Insights goes a step further and allows lenders to benchmark themselves in different ways against their peers and find opportunities for improvement or competitive leverage. The Insights product aggregates data from all lenders, scrubs it for data privacy, and presents it to each client through a series of analytics, benchmarking, and peer insights targeted for end consumption by business leaders.

The benefits and success of Ellie Mae’s data initiative hinge on one simple truth it intrinsically understands its clients expressed and unexpressed needs

The project is ongoing, and it continues to focus on client challenges. Ellie Mae defined some metrics to gauge the success of its data monetization initiatives. The firm effectively measured success by looking at the platform through two lenses; both focused on their customers’ ability to derive value from the platform. The first is how much time, money, and effort customers save using the Ellie Mae Digital Lending Platform rather than building one of their own. Underpinning this measurement is a series of other metrics that calculate customer value, such as whether the platform helped lower the cost of origination or reduce loan closing time.


The second is the amount of data the platform processes, which, according to Manish, is increasing every day. One of the platform’s core values is that it provides access to real-time data by ingesting data at scale. It helps clients track loan lifecycles, and it also accesses rich insights about the broader industry to fuel decision making.


For Ellie Mae’s customers, the benefits are clear. Some who use their systems to glean insights have reported significant performance gains and greater system and data reliability—alongside the benefit of not needing to manage the complex plumbing and infrastructure. Others report much shorter time required to close loans, better visibility into loan status, and easier bottleneck identification—a boon for their customers, where the speed of funding is a differentiator for some mortgage applicants.


As a further example, the platform’s broader capability to offer valuable insights about the market became abundantly clear in the recent COVID-19 pandemic. As governments raced to mitigate damage to consumer confidence by driving down interest rates, there was a corresponding increase in the number of consumers wanting to refinance mortgages and make use of the more attractive lending rates. Lending clients had important questions: Are they getting a proportionate share of the refinancing applications? If not, why not?


The platform enabled them to view aggregated data about the mortgage industry to identify missed opportunities using the Insights product. For example, applications may be disproportionately reaching their rivals because they offered more competitive lending rates or perhaps just quicker application closing times. In the past, lenders would have seen this data in quarterly or annual reports—often far too late to make any meaningful changes. Now, Ellie Mae clients can see the same data in real-time, with exceptional detail.


The benefits for Ellie Mae clearly revolve around its biggest focus area—better customer satisfaction with its platform and better overall customer experience from its newly added capabilities. Additionally, cost takeout significantly benefitted from moving over to the AWS and Snowflake-based ecosystem; the company now saves 40% on its infrastructure costs. Rather than just taking out costs, the new data products provide an additional revenue stream. These investments position Ellie Mae well for a more digitized and data-driven future where it can add tremendous value for its clients through technology and data connectedness, meeting needs as they arise.


As the platform evolves, Ellie Mae and Persistent will continue to build fresh capabilities and solutions for clients

The journey isn’t over; the Ellie Mae and Persistent teams continue to solve more client challenges as they evolve the platform. As the offering matures, Ellie Mae will lean into its strong belief in building ecosystems. While the firm has a clear vision for the platform’s future, it recognizes it cannot build everything. Instead, it is bringing in reliable partners—including Persistent—to develop more features and applications that customers want. Crucially, future partners won’t be hemmed in by significant infrastructure hanks to the initial focus on reliability and scale. Instead, they are free to concentrate on real applications that make clients happy and that partners can monetize.


The Bottom Line: Data modernization and monetization needs to be closely linked to end customer outcomes to be successful.

In the competitive and highly complex mortgage industry, Ellie Mae has developed a vision that enables it to evolve and redefine client value. By moving beyond transactional support across the mortgage lifecycle and using the same data to empower clients with valuable insights, the firm can evolve services and open up new revenue streams—although Manish is quick to add that monetization of data using the platform is an inevitable side effect of delivering valuable solutions to clients, rather than the singular aim.

Nevertheless, to be successful on this journey, Ellie Mae needed a reliable partner that was culturally aligned and would understand the nuanced and subtle approach adopted by the firm. For them, Persistent is one of the few who could come into the engagement with the right technical skills and mindset needed to build out a robust and evolving data platform that is constantly finding new ways of adding customer value. That’s a win-win-win in our books.

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