How Banks Can Use Data to Grow Home Loans with Existing Customers

Effective use of data is key to keeping customers from taking their mortgage business elsewhere. Technology that can track credit alerts or homes listed for sale, and then initiate a marketing response — including emails and calls — can lead to increased mortgage business, despite fierce competition.
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Banks and credit unions face brisk competition when it comes to capturing mortgage business from retail customers. Borrowers have plenty of options, from fintechs (Rocket Mortgage is the top U.S. mortgage lender by volume) and nonbank independent lenders.

And as consumers’ financial lives become more fragmented, the competitive challenges only intensify. As McKinsey has noted, a typical scenario is for a customer to have a mortgage with one lender, an unsecured loan with a different lender and separate deposit and investment accounts elsewhere.

Financial fragmentation is exacerbated because bank customers and credit union members typically conduct detailed research before purchasing a financial product or service such as a mortgage, and this process can lead them away from their primary financial institution, says J.J. Slygh, Principal Product Marketer at CRM company Total Expert. More than half of customers considering buying a new product seek out information prior to the time of purchase, according to a Gallup survey of financial services consumers.

Another factor impacting loyalty is that “most consumers don’t know the difference between a bank and a credit union,” Slygh states. “They also don’t know the difference between a bank and a multitude of other companies they consider to be financial providers.”

Don't Assume:

Few consumers understand the dynamics of the banking industry. In fact, few people understand the differences between banks and credit unions.

Better Marketing Engagement Leads to Higher Conversions

Most potential homeowners would prefer to get a mortgage from their primary institution, but many are not being engaged in the right marketing channels. Gallup found that while 45% of “satisfied” households would consider their primary institution for their next product or service, an institution’s chances rose significantly — to 83% — for households that were both “satisfied and fully engaged.”

However, “even when institutions are engaging customers, they’re doing it in high-cost, low-conversion-rate channels,” notes Slygh.

This is due to not leveraging data properly, he adds. According to a Total Expert study of 200 financial institutions, about 34% of bank and credit union leaders say they still manually leverage data for segmented messaging; 23% have limited access to data with which to send emails, and another 28% just send the same message to all customers.

Work Smarter, Not Harder:

Banks and credit unions too often put in time and money on low-conversion-rate channels. The key to better results lies with more effective use of data.

The reliance on manual processes shows that “institutions need tools that unlock their ability to develop insights about the mortgage needs of their customers or members,” Slygh observes.

“In a market where every mortgage counts,” he continues, “institutions need to identify and engage borrowers seeking cash-out refinances or looking to purchase a new home, and even the rare, rate-driven refinance.”

Slygh notes that there are two primary data tools that institutions have access to today. One is the Mortgage Credit Inquiry Alert, which provides alerts when a lender pulls credit for a mortgage on someone in an institution’s database. The second is Listing Insights, which gives information when a borrower’s home is put on the Multiple Listing Service (MLS).

“With Fannie Mae’s Economic and Strategic Research Group forecasting home price appreciation of 16% year-over-year in 2022, institutions need to know who within their database has home equity,” says Slygh.

Responding to Potential Home Buying Signals

When a potential alert is triggered from one of the above databases, what should a bank or credit union do then?

If an institution uses a platform designed to act on data like credit alerts or MLS listings, then intelligent automation can initiate a process — including emails and calls — to engage the customer, says Slygh. That process should be based on industry best practices that anticipate each step a lender must consider when talking to consumers about mortgages, he adds.

“For example, every bank has an address for their retail depositors’ home,” says Slygh. “But when does that matter? It’s central to selling a home; and it’s trackable because when a home goes up for sale, it is listed on MLS. Customers selling a home often buy a new one, or they need to safely invest their gain on the sale. An MLS listing is the customer vocalizing a set of possible needs.”

Catching that MLS signal in customer data can trigger a call from mortgage loan officer.

“Then, the loan officer can speak with the customer,” Slygh explains. “Or, if they can’t reach them, they can send nurture emails on ways the bank can help with homebuying.” If the emails don’t lead to a loan application, the loan officer can collaborate with the real estate agent if a relationship exists, or simply reach out again, says Slygh.

Such data-driven insights ultimately drive mortgage revenues and increase the bottom line.

Slygh notes that mortgage leads cost $800 to $1,200 per loan. Automated lending technology could save potentially hundreds of thousands of dollars.

“When that savings scales across a larger contact database — especially one that combines a bank’s mortgage and retail customers — revenue growth becomes highly efficient and translates to much more profitability,” Slygh states.

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