5 Revenue Opportunities Hidden in Mortgage Bankers’ Data (and How to Tap into Them)

April 08, 2022

The refi boom is over, which means mortgage lenders are shifting their focus from keeping up with demand to attracting customers.

The good news: most mortgage lenders have plenty of revenue opportunities hiding in their data. In this post, I’ll highlight five of the most common opportunities I see and offer some high-level insight about how lenders can realize them by cleaning and leveraging raw data.

1. Add Yourself to the Mix when Customers Are Shopping Around for Mortgage Loans

It’s common practice for today’s mortgage borrowers to start their process with a Google search – even if they already have a loan with a trusted provider (like your company). When that happens, it’s often bad news for small and mid-sized lenders, who can’t compete with the giants in search.

But harnessing the power of the data you track can help you be part of the consideration process for these customers.

How? If you subscribe to data aggregators and data providers to augment the data you have on customers, you’ll know when there’s a credit inquiry on a customer’s account. That’s a strong indicator that the customer is shopping for a mortgage. If they’re comparing multiple quotes, you have an opportunity to get into the mix – and maybe win their business.

Here’s how: Set up an automated workflow: whenever a customer’s account registers a credit check, send them an automated email with the following information:

  • Borrowers who shop around for mortgage loans save an average of $1,500 to $3,000 over the life of their loan.
  • If you compare quotes within a 14-day period, it won’t have any additional impact on your credit.

Plus a call to action to get a quote from you.

Make sure your loan officers are aware of this workflow and prepared to prioritize any borrowers who come in from that point of contact.

(Not something you have the capability to do today? We can help. Get in touch to learn more about how our data and analytics practice can transform your data into valuable insights.)

2. Optimize Your Call Center Staffing

What’s the perfect number of employees to staff your call center? Getting this number right can have a big impact on revenue by minimizing abandon rates and preventing over-staffing.

But the calculations required to get the right number are complex. You have to look at incoming call volume, average handle time, time spent in after-call work, time spent queued, target abandonment rates, etc.

Satisfaction is a culmination measurement that is influenced by all those factors, and the ultimate goal of right-sizing your call center is driving the highest rates of customer satisfaction possible.

And if your current call center doesn’t include advanced lead scoring or any automation (e.g., prefilling customer information or automatically generating call transcriptions), you almost certainly have additional unrealized optimization opportunities.

The good news is that the data you currently have holds the answer to the ideal staffing for your call center. Unlocking it is a matter of cleaning and interrogating that data.

The takeaway: If call center staffing is a pain point in your organization, we can help.

Related: How to Make Sure Every Loan Officer Gets the Right Leads

3. Reduce Loan Processing Time

What would your organization look like if you could reduce loan processing time by, say 30 percent? What about 40 percent? Introducing automation and machine learning to your systems could power those kinds of efficiencies. 

Here’s how: by having AI-powered systems automatically read submitted documents and extract pertinent information into data fields so that agents only have to verify that the information is correct and update what isn’t.

This type of automation can not only save time in the short term, it can also reduce errors that get introduced during manual data transfer. This helps prevent downstream errors and quality issues and therefore helps improve customer satisfaction. What’s more, the AI / ML systems that power document automation can get better and better over time – that’s the nature of machine learning.

As you might have guessed, your organization already has the data necessary to fuel the algorithms that would power this kind of automation. And we can help you tap into it.

4. Proactively Prevent Nonperformance

Nonperforming loans are a part of life for mortgage lenders. But with appropriate data-powered insights fueling customer outreach, it’s possible to mitigate their impact on revenue.

For example: certain credit-scoring indicators like a rising credit-balance-to-credit-available ratio or a shift to making minimum account payments signal that a borrower may have had a change in financial circumstances. This could lead to difficulty making mortgage payments.

These changes also signal that it’s a great time for a lender to reach out and reconnect. Doing so can demonstrate that an agent is invested in the borrower’s well being, which in itself can help increase the likelihood that they’ll prioritize loan payments moving forward.

If it’s not possible for a borrower to keep paying, reaching out proactively can help ensure that borrowers understand their options, including a modified repayment schedule, should they need one. By being proactive, lenders can ensure that they continue receiving revenue even when borrowers’ circumstances change.

Again, the key to doing this lies in your data: revealing insights, identifying business processes for addressing those insights, and scaling those processes. 

5. Expand Your Promoter Network

Net Promoter Score (NPS) is a valuable metric for mortgage lenders interested in understanding customers’ perception of their services. Even more valuable: reverse engineering the components of your customers’ experience so that you can…

  • Perform root-cause analysis to determine how various components of experience affect satisfaction.
  • Map and analyze sub-attributes of experience (length of calls, documents missed during the process, etc.) to reengineer the customer experience.
  • Determine optimal activities for the best possible customer experience.
  • Segment customers by NPS status and migrate them upward: detractors to neutral customers, neutral customers to promoters, etc.

Besides making life better for your customers, this can help increase the positive word-of-mouth exposure your organization enjoys and reduce the negative, which can have a noticeable impact on your sales.

Don’t Let the Digital Transformation Boom Pass You By

Industry leaders have signaled in no uncertain terms that they’re taking advantage of the slower origination market to enhance their technological offerings.

To remain relevant among competitors and to meet consumers’ evolving expectations for digital mortgage experiences, mortgage brokers of all sizes can tap into their vast stores of data to extract insights that let them deliver meaningful, personalized experiences – at scale.

For information about how NTERSOL can help your organization leverage its data, get in touch. We’d love to chat.