For the title industry, artificial intelligence (AI) is no longer just a futuristic concept to be discussed wistfully in conference breakout sessions. It’s here — and not a moment too soon. There are few general production processes in the housing and real estate industry more riddled with chokepoints, redundancies and opportunities for error. Until now, most title agencies have attacked those problem areas with staffing.
However, this was a costly challenge considering that the ebb and flow of the market generally dictated how much an agent could invest in ramping up (or down).
While the title and settlement services industry has done a fairly good job of automating what it could in recent years, much of that streamlining has been for simple but repetitive tasks. Production systems do a lot more than they used to. Doc prep is not quite the nightmare it once was — once all the data is gathered and entered into the production system. Scheduling and even to some degree the ability to scan documents without as much human attention have also been improved.
Where the industry still needs help, however, is exactly where AI excels. It’s the more complex, multi-step processes requiring judgement, discernment and more than one or two possible outcomes where title agencies have had to throw more bodies into the fray. That’s true even if those complex, multi-outcome tasks didn’t really require highly trained professionals.
Here are a few examples of typical title agency processes generally addressed by staff today, but which soon could be managed efficiently and cost-effectively by AI tools.
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The most difficult elements of an agency’s process to automate tend to be those requiring human-to-human interactions. Those include collaborative communications (Realtor to closing officer; loan officer to escrow assistant, etc.) for the exchange of information as well as simple, but common, client service communications. Things like: “How long until the closing? Can you please send your driver’s license and social security number?”
Although efforts — many efforts — have been made to create a “universal” channel for data exchange and communications, to date, few have really been 100% successful. Part of the reason for that is the wide variety of different communication channels preferred by all of the different people involved. One Realtor may prefer text while a loan officer might wish to use a technology integrated with her LOS and the buyer might only communicate via phone.
It’s highly likely that at least one of the people crucial to closing the transaction simply will not log onto a password-protected website that’s not otherwise a part of his daily routine. Nor will all of them download an app that applies to only a percentage of their clients or files. Generally, most of the communications solutions available on the market have required one or the other to work.
In fact, this example really highlights one of the title agent’s toughest challenges. One of the agency’s de facto “jobs” is to somehow take in all the information needed to bring about a closing — in all of the various forms all participants choose — standardize and then enter all of it into a single production system.
Many agents have shared with me their frustration at the lack of uniformity involved in retrieving the information needed for a title policy and closing. The loan officer might send something via encrypted email. The seller’s agent might provide something by way of an in-person office visit. And the appraiser may well be sending the report via U.S. mail.
But it’s someone at the title agency hunting down those various, different-sized buckets of information and inputting the data — often manually — into the same production system.
That’s where AI comes into play. Until recently, the above tasks required a system able to collect multiple types of information; briefly analyze them (“stare and compare”) and make a decision based upon multiple factors and with multiple possible outcomes. That’s where AI excels: data intake and sometimes, proactive collection; simple analysis; standardization of format and input into a central system.
The rise of conversational AI will allow title agents to offload some of the recurring communications to technology, allowing the human staffers more time to focus on their non-communications tasks.
So what’s the practical application of all this? The forms are many. It could be an AI system sending a text to buyers reminding them of the closing time and location. If that system is powered by conversational AI, it will even be able to answer questions from the same buyers. That simple task alone could save an agency staff hundreds of hours on email or their phones that would otherwise be spent actually producing a closing.
It could be a Realtor sending a text with the buyer’s mobile phone number or email address to the title agency after a short call with that buyer, and that text subsequently automatically leading to a non-human inputting of that cell phone number into the production system. All without an email. All without a human being having to decipher what the text was about, where the information belonged in the system and then opening a window on her monitor and typing it in.
That’s a simple task that’s repeated hundreds of times — all times when the agent staffer doing the work could be finishing off the CD or providing their preferred personal touch to enhance the overall closing experience.
Let’s be clear. AI is not coming to the title industry to replace the high touch, human relationship aspect of the mortgage transaction — far from it. After all, the home purchase is the biggest transaction of their lives for most. Who wants a “bot” or a phone tree helping them navigate that?
Title companies will continue to pride themselves on delivering customer service. However, by harnessing the power of AI to manage the mundane and routine, title agents will actually free their employees to focus on tasks and obligations closer to the agent’s primary objectives: sales, development, quality control and, above all, client service.
Hoyt Mann is the president and co-founder of Alanna.ai.
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