Improve Your Mortgage Process by Making Data-Driven Business Decisions
If you speak with enough high-powered loan originators, you will uncover a thread of belief that is universal to all in the highest reaches of the industry. They have always believed in and thrived because of the idea that they own and operate their own business. In fact, they ARE their own business.
This ownership instills a sense of responsibility. It’s no longer about just the LO. They have staff, they have a brand, and they have a loyal base of clients that rely on them.
Duty can be heavier than a mountain. How do you make all of the important decisions necessary to run a flourishing business?
When do you hire? When do you fire? How do you identify bottlenecks or gaps in your process? Are the loans that you’re making profitable?
Far too many people “go with their gut”, a feeling that is easily manipulated by cognitive bias, and are left grasping for answers when things don’t work out. This is the beauty of utilizing key performance metrics/indicators to aid business decision making. Data is unemotional, data has no ego, and data doesn’t care if it’s “good” or “bad”.
To help you develop your data analytics engine, and identify the levers you can pull to change outcomes, we’ll explore both basic and advanced data points that will be invaluable to begin understanding what’s really going on under the curtain of your mortgage office.
What won’t you see here? Vanity metrics such as Total Loan Volume Originated. Does it really matter how much loan volume was originated if those loans weren’t profitable?
All of the KPIs listed below are purposeful and actionable.
After all: what gets measured, gets managed.
Basic Key Performance Indicators (KPIs) for Loan Officers
The KPIs that fall in this category are some of the most straightforward yet impactful metrics that a loan officer could track. They are broader-based in scope and can provide a great deal of information on the overall health of your operation.
• Average Cycle Time
Formula: (Sum of Days from Application to Funding for All Loans) / (# of Loans Funded in Same Period)
Purpose: Average cycle time is a basic, yet important, performance metric to track for its ability to benchmark overall efficiency. As you begin to pull levers within your processes and integrate improvements, you would expect to see average cycle time decrease on new loans.
A poor cycle time has been shown to correlate directly to pull-through rates and loan profitability metrics. Referral partners and borrowers have expectations that can quickly sour relationships when loans do not close on time, or efficiently.
• Pull-Through Rate
Formula: (# of Funded Loans) / (# of Applications Submitted in Same Period)
Purpose: Pull-through rate provides a high-level perspective on the overall health your mortgage operation. It’s a very foundational metric meant to speak generally to, among other things, the efficiency of your workflow, the quality of submitted applications, the level of customer service being provided, interest rate competitiveness, and how ideal the customer profile that you’re working with is.
Pull-through rate is not used to identify any single portion of your process that is failing, but instead to understand if there are problematic inefficiencies at all, or, conversely, if your process is ready to scale to take on more loan applications.
• Average Mortgage Loan Value
Formula: (Total Loan Volume Originated) / (# of Loans Funded in Same Period)
Purpose: Average mortgage loan volume is one basic indicator of loan profitability. The typical file workload for a conforming conventional loan does not change much whether that loan is for $200,000 or $453,000. However, the revenue generated differs greatly between those two originated units.
The closer your average mortgage loan volume is to the conforming limit, the more likely you are to generate strong profit from those revenues.
• Cost Per Unit Originated
Formula: (Total Business Expenses) / (# of Loans Funded in Same Period)
Purpose: Cost per unit originated measures the efficiency of your operation relative to factors such as staffing and office expense, cycle times, and pull-through rate. Excess overhead expenses can be attained through deficiencies in any of these areas, contributing to a high cost per unit and thus lower profitability on generated revenues.
This can be particularly exacerbated by a poor hiring plan, due to the high costs associated with salaried employees. Hire too soon and your cost per unit soars. Hire too late and your cycle time lags.
Keeping costs in line with expected performance is critical to maintaining profitability at scale.
• Application Approval Rate
Formula: (# of Approved Applications) / (# of Submitted Applications)
Purpose: Application approval rate provides a couple of important insights into your client acquisition and loan application workflow.
Typically, a low application approval rate is indicative of either a large problem in document gathering and application review processes or a disconnect in your ideal customer profile that is leading to increased submissions of unqualified borrower applications.
A low application approval rate is a red flag that your operation is burning valuable time and money on dead-end applications.
Advanced KPIs for Loan Officers
These metrics can be more difficult to calculate and generally require tracking more data points with varying scope. With one exception, they are designed to analyze deeper or more specific portions of the mortgage loan origination process.
• Cycle Stages
Formula: (Sum of Days in Stage for All Loans) / (# of Loans Funded in Same Period)
Purpose: Similar to the more holistic average cycle time KPI listed above, examining cycle stages seeks to dive deeper into the individual origination stages of each loan and measure effectiveness on a more granular level.
When a LOs average cycle time is high or is rising, being able to quickly identify negative changes across various segments makes it much easier to diagnose and resolve problematic processes. Common stages for measurement would include Application, Processing and Document Collection, Underwriting, and Closing/Funding.
• Fallout Rate
Formula: (# of Rate Locked Applications that Don’t Close) / (# of Rate Locked Applications in Same Period)
Purpose: Fallout rate is actually a metric that has been traditionally used by lenders as a component of their rate-hedging assumptions. For a loan officer, however, fall out rate acts as an indicator of not only the effectiveness of their own individual rate lock strategy but also their ability to get loans across the finish line.
• Profit Per Loan
Formula: ((Total Business Revenue) – (Total Business Expense)) / (# of Loans Funded in Same Period)
Purpose: As overhead costs have soared in recent years, profit per loan has become a hot-button topic in the mortgage industry. While total loan volume gets all of the headlines, profit per loan is the far more important value when assessing the health of your mortgage operation.
There are a number of reasons that you may be experiencing low profit per loan. Cost per unit originated may be very high, negating revenues. Or perhaps your average loan value is low, thus not creating enough revenues. There has been a big push recently amongst retail lenders to become more efficient in their processes in order to lower costs and increase their profit margins on loans being funded.
If there is one KPI that should always be considered during evaluation and decision making, it’s this one.
• Abandoned Loan Rate
Formula: (# of Approved Applications Not Funded) / (# of Approved Applications in Same Period)
Purpose: Abandoned loan rate can be indicative of a number of potential issues with your post-application processes. The question this KPI forces you to assess is why a qualified and approved borrower would choose to abandon their loan.
Possible explanations can include a change in interest rate competitiveness or issues with communication and next steps after approval.
• Incomplete Application Rate
Formula: (# of Applications Closed for Incompleteness) / (# of Applications Received)
Purpose: Measuring the percentage of applications that are closed for incompleteness, or missing documentation, provides valuable insight into the application and loan processing portions of your workflow.
A high rate of closed applications could be indicative of several issues. First, is your ideal customer profile targeting prospects who are at the right stage in their journey to be ready to submit an application? Second, does your office properly communicate next steps and needs during the loan processing phase? An inability to quickly and efficiently collect documentation from borrowers not only drives up the abandoned application rate but also can lead to increased costs per unit.
Is that it?
Not by a longshot! But it’s a good starting point for your mortgage business to begin integrating data points and KPIs such as these into the evaluation and decision-making process.
Metrics such as Yield Spread (brokers!), Average Number of Lock Extensions, First Submission Approval Rate, Average Number of Conditions Per Loan, and others are great to use once you’re ready to dig deep into individual processes. But for now, get measuring and get managing!