With an uptick in consumer lending, financial-technology companies see a chance to grow by filling gaps for underserved borrowers, online lenders and industry analysts say.
Rather than relying on traditional credit scores, many fintech lenders are feeding a wider range of data into platforms powered by artificial intelligence to present a broader picture of applicants who might otherwise be turned away by banks.
a 10-year-old fintech platform based in Chicago, targets U.S. households with an average of $50,000 in annual income that need extra cash for car repairs, medical bills, student loans and other expenses.
the company’s chief executive, said its customers are employed and have bank accounts but are otherwise “locked out of mainstream financial services.”
OppFi, which made its public-market debut last summer, uses an AI model, real-time data analytics and a proprietary scoring algorithm to automate the underwriting process. It generates a credit score by analyzing a loan applicant’s online shopping habits, income and employment information, among other data sources. The actual loans are handled by licensed banks and financial institutions.
The company recently reported a record $187 million in loan originations over the last three months of 2021, up 25% from the same period a year earlier. That momentum has carried into 2022, Mr. Schwartz said.
a research vice president at International Data Corp.’s financial insights unit, said fintech lenders—by their very nature—leverage digital capabilities that traditional lending institutions “are still moving to.” He said smaller online lenders are benefiting from a head start in the use of AI and machine-learning models, digital document management and customer services designed around mobile devices—though many banks are catching up, he added.
The global fintech lending market is expected to grow at a compound annual rate of 27.4% over the next eight years, reaching $4.9 trillion by 2030, according to research firm Allied Market Research. Many banks reported lending gains in the first quarter, after two years of tepid loan demand during the pandemic.
A joint study by Harvard Business School and
from Georgia State University, published in 2018, and updated last month, found that fintech borrowers are more likely to default than borrowers from traditional financial institutions—a risk fintechs offset in part by far lower overhead.
In a March conference call, Mr. Schwartz said OppFi tends to charge borrowers a higher cost of capital until they build a track record of paying off their loans. “If people are too high risk or they’re not using our system effectively, it’s not the right customer-company fit,” he said then.
Since most fintech lenders don’t take deposits, they’re not subject to many bank regulations that can bog down the lending process. Nearly every big fintech company has to rely on bank partners for regulated tasks such as holding customers’ deposits and issuing debit cards.
LoanSnap Inc., a five-year-old startup based in San Francisco, uses AI to scan financial information such as a prospective borrower’s student-loan interest or credit-card debt. It then packages the data into a mortgage-payment plan, based on the lending requirements of its banking partners, that is designed to help clients better manage their finances—a process that takes only a few seconds from start to finish, LoanSnap CEO
said. “An example of this would be paying off high interest credit cards with a lower interest rate home loan,” Mr. Jacob said.
LoanSnap’s goal is to close home loans within 15 days, compared with an industry average of more than 40 days. Its record is 24 hours, Mr. Jacob said.
“Anyone who’s ever gotten a home loan would agree that the process is still slow, manual, labor-intensive and fragmented,” he said. Mr. Jacob said rising interest rates are also bringing in more customers looking for both affordable mortgages and better financial planning.
chief executive of online student-loan platform Earnest LLC, said one of its advantages over traditional banks is customer service, which is “one of the biggest gaps we fill,” he said. Earnest uses AI-enabled software to match loan rates and terms based on how much a borrower can afford in monthly payments. “We service loans entirely in-house and our customers always deal with us directly,” he said.
“We’ve seen tremendous growth over the past two years, but more notable over the last few months,” said
president and CEO of Austin, Texas-based lending platform Billd LLC.
Billd offers specialty financing for construction contractors, a market segment that often is seen as risky by banks and other traditional lenders, especially during turbulent economic times, Mr. Doyle said.
More recently, he said, higher interest rates and ongoing supply-chain constraints are prompting many contractors to apply for lines of credit as a way to mitigate risks in advance. By leveraging AI and a richer pool of data, he said, Billd is able to turn around lending decisions in less than 24 hours.
“Banks are very slow, and we are fast,” Mr. Doyle said.
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