Ralo, an AI-native mortgage brokerage that automates much of the traditional loan process, has funded more than $8 million in mortgages for Texas home buyers during the past six months as it looks to reduce borrowing costs by removing intermediaries and using artificial intelligence to shop across lenders.
The New York-based company said its Texas customers are saving an average of approximately $60,000 over the life of their mortgages, while Ralo is securing interest rates as much as 0.6 percentage points below the national average.
Ralo is building its business around the idea that the traditional mortgage process remains too expensive and labor-intensive.
The company cited industry data indicating that outdated mortgage processes can cost lenders nearly $11,800 per loan.
Those costs can ultimately be reflected in the rates and fees borrowers pay.
Ralo is attempting to change that structure by automating work traditionally handled by loan officers, loan processors, and underwriters while simultaneously shopping among multiple lenders for competitive financing.
The company said this allows it to operate at approximately one-quarter of the cost of traditional brokers.
Ralo also said it can close a mortgage in approximately 19 days on average, compared with an industry process that often takes 30 to 45 days.
That combination of lower operating costs and automated loan processing is central to Ralo’s strategy.
Rather than relying on a large human mortgage organization to coordinate applications, documents, lender communications and underwriting workflows, the company’s AI loan officer handles much of the repetitive work.
Ralo then passes some of the resulting cost savings to borrowers through lower mortgage rates and fees.
The company is currently focused on Texas, where it has originated more than $8 million of mortgage loans during the last six months.
Many of its customers are first-time home buyers navigating the mortgage process for the first time.
For those borrowers, even relatively small differences in interest rates can have substantial long-term consequences.
A reduction of half a percentage point or more can translate into tens of thousands of dollars in interest savings over the life of a 30-year mortgage, depending on the loan amount.
Ralo’s model attempts to create those savings by comparing available financing options across multiple lenders rather than relying on a single institution’s pricing.
The company’s technology also reduces the number of intermediaries involved in moving a mortgage from application to closing.
Traditional mortgages can involve separate sales, processing and underwriting teams as well as repeated communication between borrowers, lenders and third-party providers.
Ralo is attempting to consolidate and automate more of that work through AI.
The company describes itself as the first AI-native mortgage broker.
Its platform is designed not simply to add AI features to a conventional mortgage brokerage, but to structure the underlying operation around automation from the beginning.
That approach could become increasingly important as financial services companies seek to use AI to lower the cost of labor-intensive processes.
Mortgage lending is particularly well suited to automation because a significant portion of the workflow involves collecting documents, validating information, coordinating communications and comparing standardized financial products.
At the same time, mortgages remain highly consequential financial transactions, meaning borrowers still need transparency and support throughout the process.
Ralo says its use of automation allows it to provide more personalized service because employees can spend less time on administrative tasks.
The company also emphasizes transparency around rates and the status of a loan.
Ralo was founded by former Google employees Arjun Lalwani and Helly Shah after both experienced the complexity of obtaining mortgages themselves.
Lalwani previously worked as a Product Manager at Google.
Shah was a Google software engineer and previously worked as a quantitative professional at Goldman Sachs.
Their backgrounds combine consumer technology, software engineering and financial markets experience.
The founders saw an opportunity to redesign mortgage brokerage using AI rather than simply digitizing existing workflows.
Ralo’s model places significant emphasis on lender comparison.
Instead of a borrower individually requesting quotes from multiple mortgage companies, the platform is designed to shop across lenders and identify more attractive financing options.
That can reduce the effort required for consumers to compare offers while potentially increasing competition among lenders.
One Texas customer, Harish, said he entered the process skeptically because of his own background in the mortgage industry.
He said he compared Ralo’s offer with rates from five major mortgage lenders and was unable to find a better deal.
Another customer, Danika, said her mortgage was ready to close more than a week ahead of schedule.
She said Ralo provided a lower rate than competing providers and estimated that the difference saved her nearly $100,000 over the life of her loan.
The customer experiences illustrate the two areas where Ralo is trying to differentiate: pricing and speed.
The company believes automation can improve both simultaneously.
A faster closing can be particularly valuable in competitive housing markets, where sellers may prefer buyers who can complete financing quickly and reliably.
Lower rates have a much longer financial impact.
Because mortgage payments can continue for decades, even modest rate reductions can materially affect the total amount a household spends on housing.
Ralo’s broader opportunity comes as artificial intelligence begins reshaping consumer financial services.
Banks, fintech companies and other lenders are increasingly using AI for document processing, risk analysis, customer support and workflow automation.
Mortgage origination represents one of the more complicated consumer lending processes, creating potential for technology companies that can simplify the experience without sacrificing underwriting quality or regulatory compliance.
Ralo is betting that the brokerage layer is particularly ripe for change.
The company does not need to originate every mortgage from its own balance sheet.
Instead, it can use technology to match borrowers with lenders while automating much of the work that traditionally takes place between those parties.
That model could potentially give Ralo access to a broad selection of mortgage products without requiring the company itself to become a large mortgage lender.
The company is backed by Y Combinator, Manresa Ventures and Pack Ventures.
Its angel investors include Charles Ferguson, the Academy Award-winning director of financial crisis documentary “Inside Job,” and Ryan Frazier, co-founder and CEO of Arrived.
Ralo is headquartered in New York City.
For now, the company’s Texas performance provides an early indication of how its model could work at larger scale.
More than $8 million in funded loans remains small relative to the overall U.S. mortgage market, but Ralo is using the initial volume to demonstrate that an AI-driven brokerage can complete transactions while reducing costs and shortening closing times.
The company’s next challenge will be proving that the model can scale across larger mortgage volumes and additional markets while maintaining those claimed savings.
If it can, Ralo could offer an alternative to the traditional mortgage brokerage model where much of the value comes not from adding more salespeople or processors, but from automating the underlying workflow and using software to create greater competition among lenders.
KEY QUOTES:
“It’s exciting for us to work with Texas home buyers, many of them first time buyers, and pass on significant savings directly to them. By using AI, Ralo is more operationally efficient and can deliver personalized, white glove support for borrowers. We are eliminating the middlemen who take fees and make the process more costly and convoluted than necessary, and are delivering tens of thousands of dollars in savings to our customers.”
Arjun Lalwani, Co-Founder of Ralo
“Being from a mortgage industry myself, I went in skeptical, but Ralo proved me wrong. They offered the best rate I could find anywhere. I shopped around with the top 5 mortgage lenders, and no one could beat what Ralo offered.”
Harish, Ralo Customer
“With Ralo, my loan was ready to close more than a WEEK EARLY. None of the other mortgage providers I was considering could come close to the rate Ralo locked in for me. They saved me nearly 100K on my loan. They have cut out so many of the middleman expenses and they pass the savings on to borrowers.”
Danika, Ralo Customer
