Residential Magazine

The Best Match Delivers Results

Artificial intelligence can identify the client-originator connections most likely to succeed

By Ethan Ewing

If you’ve ever worked any kind of sales job — as a loan originator or otherwise — you know the frustration that happens after spending hours with a customer, only for them to walk out without buying anything. Sometimes, the prospect seems like a good lead, right up until the moment they buy from someone else. Other times you can sense from the beginning that they’re not going to buy from you.

Salespeople are used to this state of affairs. Dealing with leads that don’t convert is just an inevitable part of the business. A salesperson may spend the better part of a day or week trying to get someone who they just can’t seem to connect with to buy because, after all, the only way to make a sale is to spend time on the leads you’re given.

While that statement is certainly true, the idea that these scenarios are unavoidable ignores the fact that what may be a waste of time for one mortgage originator actually may be a great lead for another. That’s where the initial lead assignment can make a critical difference in a sales organization’s overall success.

Developing rapport

There’s always going to be a percentage of prospects who will waste a business’s time regardless of who helps them. Many times, however, the failure point is that the loan originator who helped them wasn’t well-suited to the customer from the beginning.

To a certain degree, selling is about the product itself. Does it fit a client need? Is the price right? In that regard, all salespeople in an organization are equal. But everyone knows that sales are as much about feelings as they are about logic and reason. It’s as much an art as it is a hard skill.

Although salespeople are generally motivated to engage with anyone regardless of their personalities — this is easier when there’s a commission in it for you — studies show over and over that prospects are pickier. Eighty-one percent of buyers, for instance, say they’d rather talk to someone who shares their same mannerisms, according to the Harvard Business Review.

As experienced originators know, closing a deal is a lot easier once you’ve developed a rapport with someone, so they’ll often try to force a connection. If you wouldn’t be friends with someone otherwise, what makes you think that you’ll get along when you’re selling them something?

Removing randomness

The problem with traditional lead assignments is that they tend to be random. Against all the evidence, they assume that everyone has just as good of a chance to close a sale with a given customer, when that’s
manifestly untrue.  

At one time, it was arguably the fairest approach available. Even those who acknowledged that random lead assignments inevitably led to suboptimal interactions between originators and prospects had to admit there was simply no way to predict which employee was right for which customer.

With artificial intelligence (AI), however, that’s no longer the case. Today’s AI tools can pick up on aspects of an employee’s personality, habits and professional strengths that predict how he or she will fare with a given client. This can be as simple as detecting the employee’s energy levels and knowing that, for example, his or her cold calls in the afternoon don’t seem to generate results. Combine this kind of information with qualifying questions from prospects, and you can direct clients to the originator who is most likely to succeed with that customer, based on past results.

It’s an innovative solution to a problem as old as commerce itself. It really works. ProPair found that 65 percent of originators perform better when you stop randomly assigning them leads and start assigning them based on what the originator does well.

Supporting role

Anxiety about the role that automation is going to play in the global marketplace has run rampant for the last few years, fueled by fears that AI solutions are going to upend or replace traditional mortgage services. But as financial-technology (fintech) services continue to grow and develop, they’re establishing themselves as critical sources of support and optimization rather than one of disruption or substitution.

AI and machine learning are exciting new tools in a sales environment, not enemies of it. New financial-technology applications are enabling mortgage companies to use their vast stockpiles of data to replace fixed-rule and manual decisions with automated and predictive ones, using the resources on hand to become more effective and improve overall business performance.

A massive wave of fintech investment — almost $40 billion in 2018 — has made this one of the most potent sources of innovation for companies across the financial markets. As computing power continues to explode, predictive decisions are becoming the new normal. If you’re not looking to use them in your business, your competitors surely are.

• • •

Of course, AI is most welcomed — and most effective — when it actually helps employees. AI-powered lead assignments are thus a natural fit for sales organizations, because they’re not about taking over people’s jobs.

They’re about enabling humans to do what they’re best at, while leaving the boring stuff we’re not so good at to the machines. If you want to empower your employees to be the best originators they can be, then let them be themselves — and let AI pair them with prospects whom they actually have a shot with.


  • Ethan Ewing

    Ethan Ewing co-founded ProPair in 2017 to solve one of the biggest challenges he faced during his career as a loan-industry executive: lead assignments. ProPair is based in Silicon Valley, California, and its AI-driven platform is used by mortgage companies across the country to increase close rates and cut lead cost per close. 

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