Artificial intelligence helps break barriers for Hispanic homeownership

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For many Hispanics the road to homeownership is filled with obstacles, including loan officers who don’t speak Spanish or aren't familiar with buyers who may not fit the boxes of a traditional mortgage applicant.

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Hey there, time traveller!
This article was published 04/09/2025 (322 days ago), so information in it may no longer be current.

For many Hispanics the road to homeownership is filled with obstacles, including loan officers who don’t speak Spanish or aren’t familiar with buyers who may not fit the boxes of a traditional mortgage applicant.

Some mortgage experts are turning to artificial intelligence to bridge the gap. They want AI to help loan officers find the best lender for a potential homeowner’s specific situation, while explaining the process clearly and navigating residency, visa or income requirements.

This new use of a bilingual AI has the potential to better serve homebuyers in Hispanic and other underrepresented communities. And it’s launching as federal housing agencies have begun to switch to English-only services, part of President Donald Trump’s push to make it the official language of the United States. His executive order in August called the change a way to “reinforce shared national values, and create a more cohesive and efficient society.”

Heribeto Blanco-Joya sits in his living room, Thursday, July 31, 2025, in Las Vegas. (AP Photo/John Locher)
Heribeto Blanco-Joya sits in his living room, Thursday, July 31, 2025, in Las Vegas. (AP Photo/John Locher)

The number of limited-English households tripled over the past four decades, according to the Urban Institute, a nonprofit research organization based in Washington, D.C. The institute says these households struggle to navigate the mortgage process, making it difficult for them to own a home, which is a key factor in building generational wealth.

Bilingual AI helps demystify home loans

The nonprofit Hispanic Organization of Mortgage Experts launched an AI platform built on ChatGPT last week, which lets loan officers and mortgage professionals quickly search the requirements of more than 150 lenders, instead of having to contact them individually.

The system, called Wholesale Search, uses an internal database that gives customized options for each buyer. HOME also offers a training program for loan officers called Home Certified with self-paced classes on topics like income and credit analysis, compliance rules and intercultural communication.

Cubie Hernandez, the organization’s chief technology and learning officer, said the goal is to help families have confidence during the mortgage process while pushing the industry to modernize. “Education is the gateway to opportunity,” he said.

HOME founder Rogelio Goertzen said the platform is designed to handle complicated cases like borrowers without a Social Security number, having little to no credit history, or being in the U.S. on a visa.

Faster applications for buyers

Loan officer Danny Velazquez of GFL Capital said the platform has changed his work. Before, he had to contact 70 lenders one by one, wait for answers and sometimes learn later that they wouldn’t accept the buyer’s situation.

The AI tool lets him see requirements in one place, narrow the list and streamline the application. “I am just able to make the process faster and get them the house,” Velazquez said.

A homebuyer’s experience

One of Velazquez’s recent clients was Heriberto Blanco-Joya, 38, who bought his first home this year in Las Vegas. Spanish is Blanco-Joya’s first language, so he and his wife expected the process to be confusing.

Velazquez told him exactly what paperwork he needed, explained whether his credit score was enough to buy a home, and answered questions quickly.

“He provided me all the information I needed to buy,” Blanco-Joya said. “The process was pleasant and simple.”

From their first meeting to closing day took about six weeks.

Safeguards for accuracy

Mortgage experts and the platform’s creators acknowledge that artificial intelligence creates new risks. Families rely on accurate answers about loans, immigration status and credit requirements. If AI gives wrong information, the consequences could be serious.

Goertzen, the CEO of HOME, said his organization works to reduce errors by having the AI pull information directly from lenders and loan officers. The platform’s database is updated whenever new loan products appear, and users can flag any problems to the developers.

“When there are things that are incorrect, we are constantly correcting it,” Goertzen said. “AI is a great tool, but it doesn’t replace that human element of professionalism, and that is why we are constantly tweaking and making sure it is correct.”

Loan officers welcome AI support

Jay Rodriguez, a mortgage broker at Arbor Financial Group, said figuring out the nuances of different investors’ requirements can mean the difference between turning a family away and getting them approved.

Rodriguez said HOME’s AI platform is especially helpful for training new loan officers and for coaching teams on how to better serve their communities.

Another company is testing similar AI tools

Better Home & Finance Holding Company, an AI-powered mortgage lender, has created an AI platform called Tinman. It helps loan officers find lenders for borrowers who have non-traditional income or documents, which is common among small business owners.

They also built a voice-based assistant called Betsy that manages more than 127,000 borrower interactions each month. A Spanish-language version is in development.

“Financial literacy can be challenging for Hispanic borrowers or borrowers in other underserved populations,” said Leah Price, vice president of Tinman platform. “Tools like Betsy can interact and engage with customers in a way that feels supportive and not judgmental.”

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