ZestCash has just raised considerable cash to fund its effort to lend money to individuals who don't have access to traditional credit.
The 18-month-old startup on Thursday plans to announce that it has just completed a $19 million found of financing: $11 million in Series A venture capital from Lightspeed Venture Partners, GRP Partners, and Flybridge Capital Partners to grow its business operations, and $8 million worth of venture debt financing from Lighthouse Capital Partners to fuel its loan business.
ZestCash was founded by Douglas Merrill, former CIO of Google, and Shawn Budde, former chief customer officer of Capital One, as a venture to provide short-term loans to borrowers excluded from the traditional credit market, borrowers who would otherwise have to resort to costly payday loans.
Payday loans are widely regarded as one of the most expensive forms of credit and are typically made to those with already constrained financial resources. A person taking out such a loan writes a check to a lender for the loan amount plus a fee, say $300 and a $60 fee. The lender holds the check until the borrower's next payday, at which point the borrower can pay off the loan and fee or rollover the loan principal for an additional fee. The result is that many payday borrowers end up paying rates equivalent to extremely high levels of interest, like 400%.
To borrow $500 through a payday loan with a $90 fee might cost something like $1,400 after nine rollovers, Merrill said in a phone interview. He cited figures from the Center for Responsible Lending that indicate 25% of payday borrowers have loans open 11 months of the year. With ZestCash, a $500 loan would cost less than $900, with $86 payments over five months that, unlike payday loans, actually pay down the loan principal in addition to the interest.
ZestCash isn't a charity or peer-to-peer loan venture where social ties can lead to below-market rates; it aims to undercut the current market for expensive credit. As such it's not a better deal than a traditional bank loan but it's far better than a payday loan.
The company's secret sauce is overlooked data and under-appreciated math, the basis of Google's recipe for success. Merrill said that the payday loan industry doesn't know how to underwrite its loans as effectively as it could and as a result has to charge fees that are too high, to make up for loans that go bad.
"The problem is the underbanked don't have much information in their credit bureau files," said Merrill. "So the FICO score for the underbanked is not a great predictor" of who is likely to repay a loan.
ZestCash is looking beyond traditional credit bureaus for the data it uses to calculate loan risk. One non-traditional signal among many that ZestCash considers, for example, is whether the borrower regularly pays for pre-paid mobile service. Cell service is usually a high-priority payment for those without strong financial resources, Merrill suggested, because it's often one's only communication service. Thus, missing such payments on a frequent basis is a signal of risk.
By measuring many such signals, Merrill said he believes ZestCash can profit while undercutting the competition, which doesn't have access to the same data.
"There's a tremendous amount of data about people, from various sources, crawls, or alternative data providers, and by using really big data math, we're able to come up with essentially a proprietary score that allows us to decide who to make loans to," said Merrill.
To handle its data and math, ZestCash relies on Amazon Web Services as its cloud service provider.
"I founded a company to try to change the lives of the underbanked, to change the lives of those who don't have any economic of political power," said Merrill.
Through underwriting informed by better risk data, Merrill said he believes ZestCash can change the entire payday loan industry and help put billions of dollars back in the pockets of the 60 million people without access to affordable credit.
"I feel like we're building a good business, doing good for the world, and doing it in a way that is in keeping with how we did things at Google where you use big math and big data," he said.
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