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Rocket Companies said it is developing artificial intelligence tools that will help it quickly scale its business as mortgage lending rebounds, which has become key to increasing market share and profit margins.
The Detroit-based fintech company’s Rocket Mortgage unit saw second-quarter mortgage loan originations increase 10% from the same period last year to $24.7 billion, while sales margins also improved to 2.99%, a 32 basis point increase from the same period last year. .
Rocket also provides real estate brokerage services through its subsidiary Rocket Homes, personal finance services through Rocket Money, and personal loans through Rocket Loans, which helped Rocket post a second-quarter profit of $178 million, up 28% from a year ago. %. Revenue rose 5% to $1.3 billion, while expenses were flat at $1.1 billion.
Varun Krishna
“We have grown despite industry challenges,” Rocket CEO Varun Krishna said on a call with investors. “Most importantly, we have achieved profitable market Share growth (our north star metric) and expanding share of purchases year over year through extensive optimization of our process, team, marketing and technology capabilities.”
Rocket said it expects adjusted revenue in the third quarter to be between $1.15 billion and $1.3 billion.
Rocket’s shares, which have traded as low as $7.17 and as high as $16.65 over the past year, fell 5% Thursday before the earnings release to close at $15.36, in line with the broader market’s decline.
Krishna and Chief Financial Officer Brian Brown spent much of Thursday’s conference call detailing how Rocket’s investment in artificial intelligence has transformed the company’s business and will allow it to grow while keeping spending flat.
During the second quarter, Krishna said Rocket expanded its AI-powered live chat interface “across the entire customer journey,” including for mortgage purchases, which it launched two weeks ago.
“The beauty of chat is its scalability and versatility,” Krishna told investment analysts.
Krishna said Rocket’s AI chat interface complements traditional phone interactions, allowing the company to not only respond faster but also provide “a more personalized and tailored experience.”
By quickly gauging customer intent, Rocket is able to guide customers “to the best solution or a more in-depth discussion with the right expert team member,” Krishna said, tripling conversion rates.
“By leveraging generative AI, we can deliver great customer experiences at scale by handling more interactions and keeping more customers engaged,” he said.
Another new AI tool, Rocket Logic Assistant, can transcribe customer calls and automate mortgage loan applications instantly.
“We now generate 300,000 report cards a week,” Krishna said. “This is a huge data set that actually automates 113 fields in a mortgage application, [otherwise] Must be entered manually.
Rocket has also automated much of the process for evaluating a portfolio of mortgage servicing rights (MSRs) that the company hopes to acquire from other lenders.
Some mortgage lenders sell the servicing rights for the loans they originate to companies like Mr. Cooper’s that specialize in that business. But Rocket likes the opportunity to earn fee revenue from mortgage investors and do business with a growing customer base by keeping services in-house.
Rocket claims that MSR audit automation enables the company’s capital markets team to complete MSR audits in half the time, an important capability as the company seeks to expand its service portfolio.
In the second quarter, Rocket acquired $20.8 billion in MSRs, bringing its total mortgage servicing portfolio to $534.6 billion as of June 30.
Rocket now collects monthly mortgage payments from 2.6 million borrowers on behalf of investors in mortgage-backed securities.
Not only does Rocket’s MSR portfolio generate approximately $1.4 billion in annual revenue in the form of service fees, but all of the borrowers it serves are potential future customers for new purchase mortgages, home equity loans or rate and term refinances.
Brian Brown
“Our servicing and origination businesses work together to create a powerful cycle that attracts new customers, organically creates new MSRs and retains them for their next mortgage,” Brown said. “This cycle creates customers for life and enables future ones. Origins and profits grew exponentially.”
Brown noted that of the approximately 6 million purchase mortgages issued since 2022 at current rates or higher, many “will be very aggressive in seeking to refinance even if rates fall slightly.” In the past, consumers might have looked for 60 to 75 basis points lower rates to get worthwhile benefits… We’ve seen clients refinance at rates below 50 basis points.
Krishna noted that employment in the mortgage industry is down 36% from its peak during the pandemic-induced refinancing boom. Mortgage lenders have traditionally needed to add staff in good times and lay off employees in bad times, but Rocket said artificial intelligence will help it keep expenses steady as it scales.
Krishna noted that Rocket continues to “invest deeply in talent,” including hiring artificial intelligence innovator Shawn Malhotra as Rocket’s first chief technology officer in March.
“We are making significant investments in data leadership and infrastructure,” Krishna said, while “strategizing very carefully in terms of what we build and the advantages we have — that’s [to say]”How do we partner with the best companies in the industry?” Whether it’s OpenAI, AWS, or Anthropic, just to name a few.
Brown said Rocket’s goal is to keep its fixed cost structure unchanged while continuing to expand production capacity.
“When you think about these investments in artificial intelligence, that’s where we deploy capital and resources,” he said. “So what that means is that we have to be very diligent and tough on the other side and look for efficiencies and remove any slack in the system so that we can continue to allocate funding to these very strategic initiatives…Everything we focus on It is right now to increase the capacity of the system and keep the cost structure relatively similar through efficient means.
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