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Rocket Companies says it’s leaning heavily into artificial intelligence tools that will help it rapidly scale its business when mortgage lending rebounds — and which have already become a key to growing the company’s market share and profit margins.
The Detroit-based fintech’s Rocket Mortgage subsidiary boosted second-quarter mortgage originations by 10 percent from a year ago, to $24.7 billion, while also boosting gain on sale margins to 2.99 percent, up 32 basis points from a year ago.
That helped Rocket — which also provides real estate brokerage services through its Rocket Homes subsidiary, personal finance services through Rocket Money, and personal loans through Rocket Loans — post a $178 million Q2 profit, up 28 percent from a year ago. Revenue was up 5 percent, to $1.3 billion, while expenses were flat at $1.1 billion.
Varun Krishna
“We demonstrated growth despite industry challenges,” Rocket CEO Varun Krishna said on a call with investors. “Most importantly, we achieved profitable market share growth — our North Star metric — and expanded purchase share year-over-year by making numerous optimizations in our processes, teams, marketing and technology capabilities.”
Rocket said it expects Q3 adjusted revenue of between $1.15 billion to $1.3 billion.
Shares in Rocket, which in the past year have traded for as little as $7.17 and as much as $16.65, were down 5 percent to close at $15.36 Thursday before the release of earnings, in line with a broader market decline.
Krishna and Chief Financial Officer Brian Brown spent much of Thursday’s call detailing how Rocket’s investment in artificial intelligence is already transforming the company’s business and will enable it to grow while keeping expenses flat.
During Q2, Rocket expanded its AI-powered live chat interface “throughout the client journey,” Krishna said — including purchase mortgages, which launched two weeks ago.
“The beauty of chat lies in its scalability and versatility,” Krishna told investment analysts.
Rocket’s AI chat interface complements traditional phone interactions, allowing the company to not only respond faster but provide “an experience that is more personalized and tailored,” Krishna said.
By quickly gauging client intent, Rocket is able to direct customers “to the best solutions or deeper discussions with the right expert team member,” Krishna said, with conversion rates that are three times higher.
“By leveraging generative AI, we can deliver great client experiences at scale by handling more interactions and keeping more clients engaged,” he said.
Another new AI-powered tool, Rocket Logic Assistant, transcribes client calls and automatically completes mortgage applications in real time.
“We’re now generating 300,000 transcripts every week,” Krishna said. “That is a massive data set, and that data is actually automating 113 fields on a mortgage application that would [otherwise] have to be entered manually.”
Rocket has also automated much of the process of evaluating mortgage servicing rights (MSR) portfolios that the company wants to acquire from other lenders.
Some mortgage lenders sell servicing rights to the loans they originate to companies like Mr. Cooper that specialize in the business. But Rocket likes the fee revenue it can earn from mortgage investors by keeping servicing in-house, and the opportunity to do business down the line with a growing pool of customers.
Rocket claims MSR audit automation allows the company’s capital markets team to complete MSR audits in half the time, an essential capability as the company seeks to expand its servicing portfolio.
During Q2, Rocket acquired $20.8 billion in MSRs, bringing its total mortgage servicing portfolio to $534.6 billion as of June 30.
Rocket is now collecting monthly mortgage payments from 2.6 million borrowers on behalf of investors in mortgage-backed securities.
Not only does Rocket’s MSR portfolio generate about $1.4 billion in annual revenue in the form of servicing fees, but all of the borrowers it services are potential future customers for a new purchase mortgage, home equity loan, or rate-and-term refinance.
Brian Brown
“Our servicing and origination businesses work together, creating a powerful cycle of attracting new clients, organically creating new MSRs, and keeping them for their next mortgage,” Brown said. “This cycle creates lifelong clients, and multiplies future origination and profitability growth.”
Brown noted that many of the roughly 6 million purchase mortgages originated since 2022 at current rates or higher “will be highly motivated to pursue a refinance, even with a small drop in rates. In the past, consumers may have looked for a 60 to 75 basis point rate reduction to make the benefit worthwhile … We’re seeing clients refinance for less than a 50 basis point rate.”
Krishna noted that employment in the mortgage industry is down 36 percent from peaks seen during the pandemic-fueled refi boom. While mortgage lenders have traditionally needed to add employees during booms and shed them during busts, Rocket says AI will help it keep expenses flat as it continues to scale.
Rocket continues to “invest deeply in talent,” Krishna noted, including bringing AI innovator Shawn Malhotra on board in March as Rocket’s first chief technology officer.
“We’re making significant investments in data leadership and infrastructure,” Krishna said, while “being very deliberate in terms of being strategic in what we build and where we have strength — which is [to say], ‘How do we partner with the best in the industry?’ Whether that’s OpenAI, AWS and Anthropic, to name a few.”
Brown said Rocket is aiming to keep its fixed cost structure flat while continuing to grow capacity.
“When you think about these AI investments, this is where we’re deploying capital and resources,” he said. “So that means we have to be really diligent and tough on the other side, and looking for efficiencies and taking any slack out of the system so that we can continue to allocate capital to these very strategic initiatives … Everything we’re focused on right now is adding capacity to the system, and doing it through efficient means in keeping the cost structure relatively similar.”
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