Let’s face reality: It’s hard to predict homebuying trends right now. Higher interest rates are keeping many prospective homebuyers, both first-time and existing, from entering the market.
In fact, Zillow predicts rising mortgage rates will further decrease affordability on top of an already supply-constrained and high-priced housing market. In this environment, mortgage originators can’t afford to utilize antiquated practices to attract business, such as random marketing to select groups or even cold calling.
There’s a better way. Originators should employ robust data analytics to remain viable and secure more leads.
Marketing to prospective borrowers in a dynamic environment such as this can present a serious challenge for originators. Budgets are limited and marketing efforts must increasingly be tailored to the persons or demographics most likely to engage.
Consider this: Bank of America’s 2018 Fall Homebuyer Insights Report indicates 72 percent of millennials prioritize owning a home. Roughly 37 percent of millennials actually own homes, however.
Likewise, current homeowners are seeing their properties filled with more equity than ever, but Bank of America also predicts that originations of home equity lines of credit (HELOCs) will remain flat, citing rising rates and homeowner hesitancy toward this resource.
What does this mean? It means the desire to buy homes and the possibility of opening a HELOC is there for clients, but they are hesitating to act. In other words, an originator can invest a great deal of time talking to a prospective borrower about their desire to move, renovate, etc., but may ultimately fail in getting them to act due to this hesitancy.
To help avoid this trap, originators need to work smarter, not harder, meaning it’s vital to utilize aggregated data (either proprietarily sourced, or from a third-party provider) to identify the appropriate group to engage and which products they’re interested in.
Proper lead-generation modeling entails giving each lead a unique customer score. The higher the score, the more likely the lead will apply for a mortgage. By leveraging these insights, an originator better identifies a borrower with a stronger propensity to engage in the lending process.
Sounds great, but how does an originator do this? What data is used to make these determinations? For starters, originators must decide if they choose to model data to attract borrowers looking for first mortgages, second mortgages, refinances or HELOCs. Once selected, proper modeling aggregates data down to a trend-specific level.
During this process, patterns within a particular geographic area are examined and compounded with wealth and assets for further analysis. This data is then studied at the property level.
After the models are generated, leads are vetted using the unique customer score. Scores that range in the top 10, 15 or 20 percent are more likely to express interest in the modeled loan product.
If the best data is used, originators can see up to three times more mortgage applicants than they would through reaching out to a perceived group of prospects without data, or even cold calling previous borrowers who may be ready to move, refinance or renovate.
Of course, the data utilized in this process must be aggregated to omit factors in protected areas such as ancestry or lineage, age, gender, medical condition or military status. Leveraging this data may have regulatory concerns and an originator should exercise caution.
Lending is about marketing to and actively engaging with borrowers. As such, lenders and originators should strongly consider leveraging technology in smarter, more effective ways when it comes to their marketing processes.
Proper lead-generation data-analytics modeling has a capability to empower the originator’s experience in a similar manner to the technology that creates a positive borrower experience. Whether it’s for a first-time homebuyer, new homebuyer, or a homeowner looking to refinance or take out a HELOC, the appropriate modeling and continuous evaluation of the data is enough to make a substantial difference for an organization.
Overall, leveraging better data analytics helps lenders and originators better market their products and, ultimately, increase sales. Take note at the industry’s current trend toward creating a frictionless, streamlined approach for the borrower experience.
There’s so much excitement about enhancing the borrower’s lending experience through better “digital-first” technology, but the conversation is almost nonexistent when it comes to attracting these borrowers in the first place through better technology. If we don’t identify the most-qualified borrowers through greater data analysis, we lose the opportunity to ever facilitate the improved borrower experience.
The mortgage industry is in a dynamic state right now. Most agree that the housing market is flat and is failing to show any signs of improvement in the near term. Interest rates are expected to continue to rise in 2019, meaning lenders and originators need to continue to remain agile.
There are mixed conversations, however, relative to an increase in home equity lending, home pricing and more. One thing is certain: To remain viable in such a tepid environment, originators must have the foresight to understand each type of borrower and homeowner in order to engage — proactively and appropriately — and remain competitive.
To do this, originators will need to rely heavily on technology to better identify the homeowners they need to attract. Originators also need to engage the few new and first-time buyers looking at purchasing homes.
The good news is that there is a very strong appetite within the lending community for this type of technology. As originators turn to better leveraging this information to help target their key demographic, they stand a great chance of being successful in this lending environment.