Big Data Underwriting for Payday Loans


Douglas Merrill, former chief information officer at Google, is now CEO of ZestFinance.Credit

ZestFinance has its roots in a phone call Douglas Merrill received one winter day from his sister-in-law, Victoria, who needed new snow tires to get to work and was running out of money. When asked by Mr. Merrill what she would have done if she had not been able to reach him, she replied that she would have taken out a “payday loan“.

Mr. Merrill, former chief information officer at Google and previously senior vice president at Charles Schwab, knows both finance and technology. His parent’s call prompted him to study the payday loan market. Payday loans are given to people who have a job but have bad or no credit rating.

The payday market is a niche compared to traditional consumer loans and credit cards, two markets where startups are now applying data science to loans, as I wrote in an article on Monday.

Still, the troubleshooting market is an important niche. At any given time, there are about 22 million payday loans outstanding, and the fees paid by payday borrowers are about $ 8 billion per year – a lot of money for those in the less active population. able to afford it. Mr. Merrill saw a market requiring greater efficiency, a business opportunity and the potential to lower costs for borrowers.

ZestFinance has been practicing Big Data type underwriting for longer than most other start-ups. Founded in 2009, ZestFinance granted its first loan at the end of 2010 and has continued to increase its loans since, having subscribed more than 100,000 loans. Its loans are called ZestCash, and the company is licensed as a direct lender in seven states, including Texas, Louisiana, and Missouri. ZestFinance also manages the underwriting of Spotloan, an online lender that is part of BlueChip Financial, which is owned by the Turtle Mountain Band of the Chippewa Indian Tribe of North Dakota.

Winning over state regulators has been a slow process. “We come up with a different kind of math,” said Mr. Merrill, who is now the CEO of ZestFinance. “And that’s going to make it more difficult from a regulatory point of view.”

A good dose of caution is in order, according to political analysts. A recent report from Robinson & Yu, a policy consulting firm, looked at new data methods as a way to make credit available to more Americans. In the report, backed by the Ford Foundation, ZestFinance was the star example of big data underwriting, which it called “marginal alternative scoring models”.

“I have no doubt that they have come up with sharp correlations that are predictive,” said Aaron Rieke, co-author of the report and former lawyer with the Federal Trade Commission. But the concern with ZestFinance and other start-up lenders using big data methods, Mr. Rieke said, is that “we have no idea how to speak or gauge the fairness of their forecasts.”

Mr Merrill believes such qualms will fade as data science lenders build up a track record of offering lower costs and greater convenience to borrowers.

The typical payday loan, says Merrill, is a few hundred dollars for two weeks and is renewable 10 times on average, or 22 weeks. In a traditional payday loan, all fees are prepaid with the principal paid at the end, in a “balloon” payment.

With ZestCash loans, borrowers repay the principal with each payment, which reduces the cost. It also charges lower fees. In a traditional payday loan, Merrill said, a person would typically pay $ 1,500 to borrow $ 500 for 22 weeks. Using ZestCash, he says, a borrower typically pays $ 920 to borrow $ 500 for 22 weeks – still a high fee, but far lower than a standard payday loan.

ZestFinance can charge less, Merrill said, in large part because its data filtering algorithms reduce the risk of default by more than 40% compared to a typical payday loan, and the software is constantly being modified for it. improve further.

Prospective borrowers are invited to complete an online form with their name, address, social security number, bank details and a few other questions. ZestFinance then combines that with information feeds from data brokers and online sources, and puts its algorithms to work.

Automated risk analysis, said Merrill, is done in seconds. The person is informed of the decision online. If approved, a customer service representative quickly calls to verify the identity of the borrower, verify numbers and review loan terms over the phone.

The data signals used to assess risk in the payday market are different from those of most consumer loans. “In our space,” observed Mr. Merrill, “virtually everyone has bankruptcy.” In payday underwriting, on the other hand, signs of financial stability would include how long a person has had their current cell phone number or how long a current job has been.

Angela Pyle, 47, single mother from Venus, Texas, worked for a large telecommunications company for 22 years, currently as a facilities coordinator. His annual income is over $ 60,000.

But 16 years ago, Ms Pyle declared personal bankruptcy. Credit card debt, she said, was her downfall. The minimum monthly payments on credit card balances were low, $ 50 or $ 100 in the beginning, but the balances kept going up and out of control.

The money, Ms. Pyle said, went to everything from restaurant meals to gambling debts. “It was for whatever I wanted,” she recalls, “I did it because I could. I learned a lesson in my life the hard way, and I’m not going to do it again.

Ms. Pyle is an occasional payday borrower. Three months ago, she took out a ZestCash loan of $ 700 to buy sand, concrete and other materials to build a tool shed in her garden, which she made herself. She found the online form easy to complete, approval arrived almost immediately, and a ZestFinance representative called within an hour. She also praised customer service, which included email or phone alerts three or four days before a payment was due.

Ms. Pyle is a disciplined borrower. She doesn’t borrow more than she can repay in a month or two pay days. The $ 700 ZestCash loan, she said, was paid off in six weeks. The total cost, she said, was around $ 975.

“If you leave it lying around for six or nine months, that’s crazy,” Ms. Pyle said. “This is how payday loans can cost you three or four times as much as the initial loan. “



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