Data and analytics

How data technology helps take the squeeze out of margin compression


Mortgage profit margins have certainly been on a roller coaster in recent years. Following a spike in mid-2020, margins have steadily decreased. According to the most recent Fannie Mae Mortgage Lender Sentiment Survey, lenders reported that spreads had compressed to 55 basis points, far below the prior decade’s 170 basis point average. And, over 50% of lenders expect profit margins to continue to decline in the coming months. The primary reasons? Competition and a noted market shift from refinance to purchase.

So what are conscientious lenders to do? I recently had the pleasure of sharing the stage at Experience 2022 with Chris Smith of Mortgage Solutions, LLC and Olga Rosales of Waterstone Mortgage. During this session, we shared insights, opportunities and best practices related to the ways that robust data can drive operational efficiencies and informed business decisions.

Exploring the mortgage data and analytics journey

Many elements are driving the volatility of the current mortgage market, including geopolitical uncertainty, wide-scale inflation, interest rate increases, and low real estate inventory. As lenders look for solutions, in many cases the answers lay within their own data. As such, mining and understanding that data becomes a priority. This is what we refer to as the data journey.

The typical data journey has four stages:

Descriptive – i.e. what happened? Here you can review operational reports, spreadsheets, and data silos, along with more robust datapoints from technology solutions like Insights and Encompass DataConnect® by ICE Mortgage Technology®.

Analytical – i.e. why it happened? This stage includes the review of your data standards and tools, along with data consistency, integration, and overall insights.

Predictive – i.e. what will happen? Here you begin to become more sophisticated, as you evaluate user-driven tendencies, data democratization, forecasting, and other leading indicators based on focused analysis.

Prescriptive – i.e. what should we do? This is the step toward true automation, as you utilize AI and machine learning to take proactive, corrective action.

Data in the real world

Mortgage Solutions, LLC is a credit union service organization that does loans for other credit unions. They were an early adopter of Insights, as they wanted a tool that could take them to the next level and help them make data-driven decisions. According to Chris, Mortgage Solutions has used Insights to track margin compression, APRs, and closed loans, among other metrics. One particularly eye-opening statistic they uncovered was a dramatic spiking pattern of closed loans toward the end of each month, with low early-month activity. They used Insights to drill into the data points and identify trends. By doing so, they were able to create better efficiencies with less expenses, and normalize their closed loan activity throughout the month. These efficiencies helped them achieve time to close performance that was 7-10 business days quicker than competition.

Waterstone Mortgage is a national lender that has always believed in the power of technology. Their early use of Insights and Data Connect was part of a Business Intelligence strategy driven by the executive board. An extensive data audit indicated a vast amount of data requiring effective management and consolidation. This created an opportunity to build a single source of truth for all data, and allowed them to address and improve overall operational efficiencies. An example of this pertained to underwriter activity and the number of touches involved in each transaction. Olga’s team looked at their underwriting staffing model, gathered data per underwriter, evaluated the number of touches per loan type, developed a rate per hour of touches, and defined whether they were staffed correctly, and/or if existing underwriters needed additional training. This resulted in a repeatable process that could be used across the company, i.e. for closing, processing, etc.

People, processes, and technology drive results

In both of the cases noted above, early buy-in and ongoing support from executive leadership was key. This top-down communication helps to drive transparency and transformation. But it doesn’t come easy. Achieving this level of organizational transformation comes down close evaluation and action planning related to the following:

People – Is the organization optimized for success?

  • The right culture in place
  • Appropriate staffing
  • Team members with the right skills and qualifications

Process – Are processes aligned with business objectives?

  • Data governance framework in place
  • Best practices being followed
  • KPIs in place

Technology – Is technology appropriately leveraged?

  • Hardware
  • Software stack
  • Data integration

Our panelists agreed that reaching and maintaining this level of balance sets the stage for success:

“Every decision we make is based on people, process, and technology,” said Chris. “If you get those three together, your business will absolutely take off.”

“The more time you spend up front with your data, the better product you have,” echoed Olga. “You will gain rapport, learn a lot, and get buy-in for the future.”

So where is your organization on the data journey? To learn more about how to put your data to work through technology, please visit

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