Behavioral Data is Powering Lenders’ Recapture Rate Strategies
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Behavioral Data is Powering Lenders’ Recapture Rate Strategies

September 13, 2019
Photo credit: Getty Images/monsitj
The rate at which lenders recapture repeat business from existing customers is at a 12-year low, declining dramatically over the past eight years as reported by Black Knight. With the recent decrease in interest rates, one would expect to see an improvement in that statistic, even if just temporarily given the vast amount of information known about the customer. However, in the first quarter of 2019, the retention rate hit rock bottom at 18 percent. Retaining customers has become a huge challenge for lenders, even though most lenders’ post-closing customer surveys would show a substantially higher satisfaction rate and willingness to get their next loan from the lender. It’s a significant disconnect and one that many lenders are investing time and energy to identify why customers are choosing to get their next mortgage from another lender.
 
One significant finding that contributes to losing customers is a lack of leveraging relatively new third-party data sets to inform lenders when consumers are back in-market. Advancements have been made by data-as-a-service (DaaS) vendors who can deliver unique insights, providing a wider view of your customers’ mortgage shopping behaviors. These insights enable smarter engagements to the right consumer with the right message while they are most receptive to receiving it.
 
Nimble and innovative non-bank lenders primarily focused on new customer acquisition have been successfully experimenting with these behavioral data sets, and the impact has been noticeable for servicers in the form of declining retention rates.
 
Innovators leverage unique data
Over the past eight years, the industry has seen a surge in fintech focused lenders who have gained substantial market share. Lenders such as loanDepot, Quicken Loans’ Rocket Mortgage, Better.com, and others have grown by providing consumers with a digital mortgage experience at a time when banks decided to take a back seat to originations and lacked innovation. Four years ago, loanDepot was valued at an estimated $1 billion within six years of opening their doors and Better.com was more recently valued at $550 million within five years of funding their first loan. Consumers crave innovation in mortgage lending and lenders like these have gobbled up volume by leveraging technologies to satisfy consumers’ needs.
 
Fintech lenders built proprietary technologies to prove a digital mortgage process is better for consumers. This led to many of the banks racing to catch up and having the option to partner with newly emerging fintech solutions such as Blend, ClougVirga and Roostify to deploy a digital mortgage solution as quickly as possible. The benefits were obvious and is now table stakes for mortgage lenders in their effort to keep their customers happy and coming back.
 
However, the next wave of competition is coming from innovators who are leveraging unique data to identify consumers who are in-market for a mortgage allowing their marketers to influence shopping behaviors much sooner than was previously possible.
 
Standard models missed the mark
The models lenders relied on for years to power their efforts of identifying customers who are in-market, or will likely be in-market soon, have become less and less effective because many use the same data that most lenders use. If everybody knows the secret recipe, it’s no longer a secret and the competitive advantage is lost due to mass competition.
 
Basic models using data sets such as how long the consumer has been in the loan, how much equity is in the property, the current interest rate, and how much revolving debt the household owes is accessible to all lenders rendering the models less effective. Most models missed the mark in Q1 of this year when 80 percent of the refinance transactions were cash-out with two-thirds of those taking a higher interest rate. However, the lenders using behavior data sets picked up these consumers driving significant improvements to recapture rates.
 
Creating more robust models and gaining a clearer view of the consumer’s behaviors have become the new requirement for lenders wanting to stay ahead of the game. If we break down recapture rates by loan type, it will unveil a bigger problem for lenders trying to keep their customers from leaving them when they move to a new home as purchase recapture rates are in the low single-digits.
 
Purchase business went with referrals
On average, less than one in 20 of customers return to their previous lender to provide the mortgage on their next home. This is a startling statistic from what one would expect given consumers are generally happy with their previous lender’s service.
 
However, more and more real estate firms and online portals have formed relationships with exclusive mortgage partners or launched their own mortgage company to try and guide the consumer to their preferred lender. Keller Williams Realty has Keller Mortgage. Redfin has Redfin Mortgage, OpenDoor has partnerships with VIP Mortgage and Movement Mortgage, and Zillow recently launched Zillow Home Loans. It’s a growing trend to leverage big data to influence the consumer’s choice of lender; but a strategy that is no longer exclusive to companies with millions of monthly website visitors.
 
For example, it is possible for any lender to receive alerts when one of their customers are researching online for real estate agents, which is further up the funnel than when they list their house for sale. The data is niche, unique, and new to the industry which provides the current benefit of being a competitive edge to get in front of the customer before they become engaged with another lender.
 
Behavioral data has moved the top of the funnel
For many lenders, it’s standard practice to leverage credit triggers, MLS listing alerts, and in-the-money-models, to identify which of their customers were at risk of becoming a lost customer. Ellie Mae reports that 88 percent of the time, consumers will close with the first or second lender they speak with, which makes getting in front of your customers at the top of the funnel vital to keeping them as a customer.
 
Although credit triggers are important and a strong indication that a customer is at-risk, this is also informing the lender, and dozens of other lenders buying the same credit triggers, that they are already behind and needing to play catch up to win the business. MLS listing alerts are similar, as the consumer already has a realtor who listed their house for sale and is likely the agent for the subsequent purchase transaction...and every realtor has a great mortgage partner to refer their clients.
 
Access to behavioral data signaling where the consumer is in their shopping journey—especially those that inform you when your customers are actively shopping on mortgage comparison and lead generation Web sites—has moved the top of the funnel even higher. Lenders are now able to determine when their customers first start researching a mortgage, which is typically 100 days before they submit a quote request online, list their house for sale, and have their credit pulled.
 
This 100-day period, signals the consumers first point of thought to get a new mortgage and provides a strong competitive edge to the lenders that use these signals to influence the consumer’s shopping journey to their benefit.
 
Timing is everything
It’s been a common phrase used by many, but it doesn’t make it any less relevant today than it did years ago. Marketing to the right person, at the right time, with the right message is important. But many lenders today are using marketing automation strategies that worked in the past and have steadily declined in performance over the last couple of years due to their reactionary trigger events, such as when a consumer submits a lead request, or is based on audience segmentation with look-a-like models which are broad in nature creating the need to cast a wide marketing net.
 
The new wave of marketing strategies revolve around people-based marketing which is hyper-targeted to identifying the actual consumer and when they are beginning their research allowing lenders to be proactively marketing. People-based marketing strategies enable marketers to provide a greater focus on the exact people much more likely to get a new mortgage and influence their shopping behaviors to give themselves a much higher probability of winning their business for the long-term.

Mike Eshelman is head of consumer finance at JornayaMike Eshelman is head of consumer finance at Jornaya, a data-as-a-service platform that delivers consumer journey insights to publishers, marketers, analytics and compliance professionals with the highest-resolution view of the consumer buying journey. Mike can be reached by e-mail at MEshelman@Jornaya.com.

This article originally appeared in the July 2019 print edition of National Mortgage Professional Magazine.

 
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