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How data-driven insights improve profitability, productivity and efficiency

To have visibility into what is really happening and make quick proactive decisions it is imperative to have direct access to real time data

With interest rates on the rise, refis trending downwards and a significant decrease in purchase volume brought on by low inventory, mortgage lenders are looking for smart solutions to combat margin compressions in 2022 and beyond. HousingWire recently spoke with Maylin Casanueva, President of Teraverde, about the importance of data-driven decision making and the power insightful data can have on the overall health of a lender’s business.

HousingWire: What are some key challenges lenders will face this year when it comes to profitability and productivity?

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Maylin Casanueva: Rising interest rates have already resulted in large decreases in volume this year. Refinances fall as rates rise. Purchase volume is also affected by low inventory, increasing property values, and when coupled with rising rates can significantly reduce a borrowers’ ability to purchase a home. Making the process increasingly more difficult.

This quick reduction in volume has caused margin compression to become a major pain point. The competition for new hires to manage the refinance boom over the last 18 months has increased compensation costs as well. The result is a lot of painful decisions facing mortgage lenders. How does a lender manage declining volume, shrinking margins and potentially excess staff? Said another way, in late 2021 the key question for lenders was how to get all the loans in their pipeline to close. Now, the key question is how to cope with a much smaller pipeline, compressing margins and high compensation costs?

HW: How can lenders leverage data-driven insights to overcome these challenges?

MC: Data-driven decision making is and will continue to be a critical component needed to make important real time decisions moving forward. There is an enormous amount of data in the lending process, and lenders are still struggling to try to make sense of it all. Some lenders have made big investments in business intelligence tools and business analysts to provide reports, KPIs and dashboards. And many executives may say, “So what?”  Many executives have privately shared their frustration that KPIs, dashboards and reports show the summary of what we already know:  Volume is down, margins are down and compensation costs are too high given current volumes and margins.

These executives also confide that they are not receiving valuable, interesting and actionable insights from the investment in tools and staff. According to one bristling executive, “I do not need coders and analysts suggesting how I run my business”. These roles have not been successful in providing the information and critical insights that lead to action.  

Why have so few lenders been successful in getting their data to answer critical questions that tell the full story? KPIs are alerts that provide a snapshot at a point in time. Pull through percentage is a good example. The pull through KPI does not provide enough information to see the full picture of the final status of a loan application, and what action is necessary to reduce fallout right now. If a lender views fallout as a cost of doing business, they are missing the opportunity for increased funding from the pipeline. For instance, a lender was surprised when we analyzed fallout by category. The lender discovered certain producers had service level problems that contributed to heightened fallout. The lender discovered a way to recover loans that had a certain type of fallout. The adoption of a Point-of-Sale system by producers had a significant impact on certain types of fallout. Also, denials from certain underwriters were too low in some cases and too high in others when looking at the credit metrics of approvals and declinations.

What is the nature of fallout? Which employees are causing it? Are processes or origination methods causing it? If you know the questions to ask, one can navigate to success. In short, every issue in mortgage lending has a story, and an executive needs to see the story to generate the insights (or “aha!” moments that improve productivity, efficiency and profitability). The executive needs to explore their data with the executive’s domain knowledge to discover the answers that complete the story.

The combination of executive domain knowledge being applied to the data at hand in a creative way is one element of the effective implementation of data-driven decision making. Another element is to have direct access to the single source of truth. That is, accurate data from the original entry into the lender’s system of record.  If you want to get to the core issues, it is imperative to know the true factual data versus manipulated or transformed data.

An example: A lender noted that their dashboards had variations that did not seem to make sense. Closer examination found the dashboards were being served erroneous data. Some of the errors were bad data entry at the inception of the loan. Bad data, coupled with the inability to detect and correct these data entry errors results in rework, potentially incorrect decisions and unsalable loans.

A second set of errors can arise from incorrect coding of data source and/or transformation of data from the original system of record to a lender’s data warehouse. One CFO was shocked that the reports derived from the lender’s data warehouse contained data that differed from their original books of entry. Three issues were revealed:  mapping issues, data transformation issues and lack of error trapping.

The solution is to shorten the path from the original books of entry to the use of that data, as well as error detection/correction and proof of data provenance. Lenders working with the real time data extracted from the original system of record significantly reduced data issues. In short, the health of the data being used in decision making translated directly into the health of the lender. It is like unhealthy food making the human body ill. Bad data, when ingested, can make the lender ill.

HW: Where are areas that most lenders could improve their lending efficiency?

MC: Primarily, executives need to ask simple questions about every report, KPI, dashboard and BI tool they use. That question is, “If I didn’t have this report, KPI, dashboard or BI tool, would the quality of my decision making be impaired?”  If the answer is yes, the next question is, “Is the information worth the cost of producing it, and can I get it faster, cheaper or more conveniently another way?”  Insightful executives usually answer “yes” to the second question.

Executives know that “less is more.”  Getting directly to the key elements of data driving a decision is important. Sifting through the noise can be maddening. One executive noted, “I reviewed all these reports, but in the end, I looked at a few relationships between the data to make my decisions. The rest was non-value-added excess.” This executive also said, “When developing associations using a different solution, I discovered that many aspects of my reports were incorrect, sometimes significantly. And that resulted in erroneous decisions.”

Mortgage lending is complex, and many executives have discovered that accessing and exploring data directly instead of using an interpreter or analyst produces better, faster results. The analyst will never have the domain knowledge of the executive. And thus, the analysis often has missing associations and nuances that an executive intuitively knows. Most analysts will do their best to provide exactly what the executive requested, but the analyst may simply not know how to take it to the next level and explore for additional insights. To have visibility into what is really happening and make quick proactive decisions in these fast-changing times it is imperative to have direct access to real time data.

HW: How does Teraverde’s data solutions help lenders improve their lending processes?

MC: Teraverde combined the team’s mortgage domain knowledge with a proprietary user interface and a powerful associative data engine to provide unparalleled insights.  Teraverde’s data solution focuses on how to solve the challenges that lenders face today and get to the root cause of the issues. Coheus acts as a North Star to help an executive orient the lender’s data to the executive’s domain knowledge. One executive described Coheus as a ‘guiding light’ to insightful data-driven decisions that improve profit, efficiency, and productivity.

Teraverde collaborates closely with our clients to continuously enhance our solution based on real life use cases. We continue to build domain knowledge into Coheus so that when an executive sees the visual presentation of associated data, they instinctively know what to do. The Coheus playbook and North Start technology makes the insight jump out at the executive. Rather than being buried in reports and noise, the executive can quickly come to the decisions that make a business successful.

In short, Coheus is a different type of solution that makes it easier for executives and managers to access and explore the data on their own. The executive knows their own business is the best data storytelling person that will ask the right questions and explore the data for answers. Our domain knowledge of the business, built directly into Coheus, is what makes it unique.

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