"In the USA for decades, the arbiters
of creditworthiness have been two powerful groups: the Big Three credit
bureaus, which keep files on roughly 200 million consumers, and score creators like FICO, which
turn that raw data into a three-digit key to credit cards, car loans, mortgages
and more.
But with tens of millions of consumers
left out of traditional credit scoring and the pandemic exposing potential
problems in the current system, established players and slick start-ups alike
are collecting and crunching all manner of other data to determine who ought to
get a loan and how much they should pay.
This so-called alternative credit
scoring could have profound effects for consumers, many of them minorities or
low-income individuals, who can be asked to hand over more intimate personal
information — like their spending habits and details of their college degree —
in hopes of getting a loan.
“The box for who gets a conventional credit score is
pretty small, and that box hasn’t been updated in a while,” said Silvio
Tavares, the chief executive officer of VantageScore, an established credit
scorer that is owned by the big bureaus and is working on adding alternative
data to its models. “Data is really a big equalizer.”
The efforts to better understand
potential borrowers increasingly take two forms, which sometimes overlap. The
first involves obtaining cash flow and transaction data from users’ bank
accounts, a practice that lenders including Kabbage have used. The second
involves applying artificial intelligence to broad swaths of information —
which may include items already in your credit report, new details such as the
mileage on the used car you’re buying or perhaps behavior gleaned from your
debit accounts — to assess applicants’ ability to pay.
Regulators have recently begun
discussing both issues,
considering and collecting input from the financial industry and others.
Officials at the Consumer Financial Protection Bureau have warned that artificial
intelligence could amplify risks, including by perpetuating biases against
certain borrowers, charging some of them too much or simply making inaccurate
predictions. The bureau’s director, Rohit Chopra, recently said the new
algorithms became “black boxes behind brick walls” when left unchecked.
A deeper understanding of potential
borrowers’ finances is valuable intelligence for lenders. The roughly 45
million people who have a thin or nonexistent credit history — more than 15
percent of the country’s adult population — are a lucrative untapped market.
“FICO is more than 30 years old,”
said Dave Girouard, chief executive of Upstart, which uses nonfinancial data
including the type of job you hold and your level of education to help make
credit decisions on personal and auto loans. “It leaves millions of people out
in the cold and millions more who pay more for credit than they should.”
Upstart’s platform is growing
rapidly. It has more than 30 lending partners, including Cross River Bank, which made more
than 360,000 new loans totaling $3.13 billion in the third quarter, up 244
percent from a year earlier. At least four of those lenders dropped their
minimum FICO score requirement altogether.
The company is also something of a
regulatory guinea pig: Upstart was the first business to receive a no-action
letter from the Consumer Financial Protection Bureau. The letter essentially
said the bureau had no plans to take any regulatory action against the company
in return for detailed information about its loans and operations.
Though the bureau didn’t recreate
Upstart’s results on its own, it said the company had approved 27 percent more
applicants than the traditional model, while the average interest rates they
paid were 16 percent lower. For example, “near prime” customers with FICO
scores from 620 to 660 were approved about twice as frequently, according to
company data. Younger and lower-income applicants also fared better.
Upstart, which also agreed to be monitored by two advocacy
groups and an independent auditor, takes into account more than
1,000 data points inside and outside a consumer’s credit report. It has tweaked
its modeling at times — it no longer uses the average incoming SAT and ACT
scores of a borrower’s college — but includes the person’s college, area of
study and employment history. (Nurses rank well, for example, because they’re
rarely unemployed, Mr. Girouard said.) The amount that borrowers are asking for
may also be a factor: If they are seeking more than Upstart’s algorithms
believe is appropriate, that may work against them.
Other companies work in a similar
way, although the methods and data they use vary.
TomoCredit, for example, will issue
a Mastercard credit card to applicants — even those with no credit score —
after receiving permission to peer at their financial accounts; it analyzes
more than 50,000 data points, such as monthly income and spending patterns,
savings accounts and stock portfolios. Within two minutes, consumers are
approved for anywhere from $100 to $10,000 in credit, to be paid off weekly.
On-time payments help build users’ traditional credit files and scores.
Zest AI, a Los Angeles company that
already works with banks, auto lenders and credit unions, is also working with Freddie Mac, which
recently began using the company’s tools to evaluate people who may not fit
squarely inside traditional scoring models.
Jay Budzik, Zest AI’s chief
technology officer, said the company went deep into applicants’ credit reports,
and might incorporate information from a loan application, such as the mileage
or potential resale value of a used car. It can also look at consumers’ checking
accounts.
“How frequently are they getting
close to zero?” Mr. Budzik said. “Those things are helpful in creating an
additional data point on a consumer that is not in the credit report.”
The same methods can also be applied
to those who already have a robust credit history, filling out their profiles
in real time. Such information became more valuable during the pandemic because
credit scores alone may not have picked up signs of stress when borrowers could
pause payments on student loans and mortgages.
It can take months for some
information to filter into credit scores, said Kelly Thompson Cochran, deputy
director of FinRegLab, a nonprofit that tests new technologies in the financial
industry. “This can make it particularly difficult for lenders to predict
default risk accurately both for applicants who have recently experienced
financial difficulties and for applicants who are rebounding from past income
or expense shocks,” she said.
Established credit scoring and
reporting companies are increasingly offering consumers ways to add additional
information. The credit bureau Experian’s Boost feature allows consumers to
pipe in payments on bills from a services like Netflix, Disney+ and their
mobile phone provider. The average customer’s FICO 8 score — the formula
currently used by most lenders — rises 13 points, executives said.
And FICO is piloting a new score, UltraFICO, which
augments its traditional model by taking into account — with users’ permission
— their cash on hand, history of positive balances, and recentness and
frequency of banking transactions. FICO estimated the new score can reach 15
million more people.
More information, such as income
data or whether you have a 401(k) plan, could be included in future iterations,
said FICO’s chief executive, Will Lansing. “I think the future of the industry
is the consumer taking more control of their data,” he said, “and deciding when
it will be used and what it will be used for and for what purpose.”
Consumer advocates say that’s a
crucial issue.
While the growing use of transaction
data could be a boon to many borrowers, checking and debit accounts contain all
sorts of revelatory information, and access to it must remain voluntary,
advocates said. Lenders may be looking largely at the broad strokes of your
cash flow now, but will they eventually glimpse at where you shop and what
types of doctors you visit?
“Credit invisibility is a problem,
but some of the solutions or cures can be worse than the disease,” said Chi Chi
Wu, a staff attorney at the National Consumer Law Center. “It’s a high-wire act
to make sure this helps more than it hurts.”"
As the Chinese authorities have already figured out in working with such a very successful firm, Ant, allowing these firms to work with lending partners, i.e. to use lending partners' money to give loans poses a risk to the country’s entire financial system, since the desire to make quick money without any material liability is disastrous, as the recent financial crisis over the distribution of mortgages without material responsibility for repaying those loans has shown. If these firms work with their own money, then there is no such problem.
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