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The Impact of AI on the Real Estate Market

Synergy, outsourcing, blockchain: all buzzwords and movements that businesses have navigated in the past—but the current thing everyone is talking about is Artificial Intelligence, better known as AI, and it is looking like big changes may be coming in the future if the trend continues rocketing up as it has been since the first AI bots have been released. 

According to STRATMOR, a mortgage consulting firm, there is no version of the future that does not include AI. In their words, “that genie is out the bottle, and the only thing that will determine whether it will be good or ill will be the wishes we make.” 

But AI does not only serve the good; fraudsters will instruct AI to do their bidding as well, which unfortunately will make them more effective and more of a problem. 

Knowing this, STRATMOR surveyed a group of experts on the trend, including the posterchild of AI—ChatGTP. What emerged offers a glimpse into what may be our best-case scenario for how we will share the future with these powerful new technologies. 

AI is a digital view into our future, according to STRATMOR. “At the risk of telling you something you’ve heard a few million times now ChatGPT is a ‘language model trained to produce text’ that helps the user compose content, from emails to essays, in response to questions you ask it.” 

“This AI is a result of OpenAI, a nonprofit organization funded by some of the wealthiest technology companies and leaders in the world, including Elon Musk and Microsoft. Together, they have spent billions on their digital child,” STRATMOR continued. “Their investments paid off, resulting in the fastest growing consumer app in history. Today, users everywhere are using it for everything from creating complete software apps to authoring complete novels and screenplays to writing breakup letters.” 

There are mountains to climb to implement AI in the mortgage industry. ChatGPT offered this shortlist: 

  • Data Quality and Availability: AI algorithms rely on high-quality and relevant data for training and accurate predictions. Ensuring data quality, integrity and accessibility can be a significant challenge when implementing AI. 
  • Regulatory Compliance: Integrated AI systems must navigate compliance with laws such as fair lending practices, privacy regulations and anti-discrimination laws. 
  • Explainability and Interpretability: Developing AI models that are interpretable and transparent is a challenge in the mortgage industry. 
  • Change Management and Workforce Adoption: Resistance to change, lack of AI literacy and potential job displacement concerns can hinder the adoption and implementation of AI technologies. 
  • Model Bias and Fairness: Ensuring fairness and mitigating biases in AI models used for mortgage originations is essential to avoid potential legal and ethical issues. Developing bias-free models and addressing biases in data sources pose significant challenges. 

“We talk about ‘automation’ and ‘AI’ as the same thing, which it is not,” says STRATMOR Principal Jennifer Fortier. “’Automation’ means taking the human out of routine repetitive tasks and ‘AI’ means simulating human thinking. So, when we talk about AI features, my mind goes to ‘what human-like thinking is it doing?’” 

No one can say how long it will take AI to move into the underwriter’s office, but we know that’s not where it will start. We know this because the AI takeover has already begun. 

“Today, the most appealing feature AI is offering us is document and data point recognition — finding data and figuring out what it is,” says Fortier. “Once data is identified, the system can then run a series of automated comparison checks or rules. When the rules fail, there is an exception task routed to a human user.” 

“We still need a human to do the thinking when the system cannot accommodate situations that are not a clean pass or fail,” says Fortier. “So, today, the most practical use of AI in the mortgage process is figuring out what the data is, which is a considerable benefit for efficiency, accuracy, and transaction speed.” 

STRATMOR Senior Advisor Brett McCracken adds that AI could eliminate the dreaded “stare and compare” that, despite current automation efforts, still plagues the industry. 

“AI can compare data fields across stored database values and information pulled from static documents uploaded from borrowers and third parties to run sophisticated rules from investor guidelines and internal overlays,” says McCracken. “AI should be powerful in the near-term at handling the most mundane tasks being assigned to lower cost resources inside of lending organizations especially for the work that follows a very predictable pattern.” 

The question now is when more lenders will embrace it. 

Click here to read the rest of the research from STRATMOR. 

About Author: Kyle G. Horst

Kyle G. Horst is a reporter for DS News and MReport. A graduate of the University of Texas at Tyler, he has worked for a number of daily, weekly, and monthly publications in South Dakota and Texas. With more than 10 years of experience in community journalism, he has won a number of state, national, and international awards for his writing and photography including best newspaper design by the Associated Press Managing Editors Group and the international iPhone photographer of the year by the iPhone Photography Awards. He most recently worked as editor of Community Impact Newspaper covering a number of Dallas-Ft. Worth communities on a hyperlocal level. Contact Kyle G. at [email protected].

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