‘Big Data’ Doesn’t Yield Better Loans; Consumer Group Says Crunching Such Numbers Doesn’t Make a Big Difference; Lenders Disagree

‘Big Data’ Doesn’t Yield Better Loans

Consumer Group Says Crunching Such Numbers Doesn’t Make a Big Difference; Lenders Disagree


Updated March 17, 2014 11:19 p.m. ET

Can “Big Data” really help write a better loan?

That is a timely question, as startups backed by big Silicon Valley names employ big-data techniques to offer short-term, small-dollar loans. The companies want to reach the 68 million Americans who the Federal Deposit Insurance Corp. says struggle to get loans because they have either no credit history or a poor credit history.

Crunching numbers on everything from an applicant’s number of Facebook FB +1.51%friends to how regularly consumers pay their cellphone bills to the number of minutes they spend completing a loan application, these companies say they can spot a good borrower without relying exclusively on information from conventional credit sources.

They say the data enable them to offer loans that are more affordable than payday loans, where annual interest rates average roughly 400%, according to the Pew Charitable Trusts.

Now, a consumer group has looked at the loans these startups offer—and concluded that big data doesn’t make a big difference.

The National Consumer Law Center found that the loans based on underwriting from LendUp, ZestFinance Inc., Think Finance Inc. and other big-data startups offered effective annual interest rates of 134% to 749%. Think Finance is both a lender and a data-cruncher; LendUp is a lender; ZestFinance crunches data for other lenders. LendUp and ZestFinance said they have made tens of thousands of loans in the past few years.

Persis Yu, an attorney for the center and author of the report, examined interest rates, loans terms and fees published on the companies’ websites, compared to payday-loan companies’.

“The big-data algorithms do not appear to lead to the development of better loan products,” she said.

LendUp is backed by Google Inc. GOOG +1.65% ‘s Google Ventures. ZestFinance is backed by PayPal founder Peter Thiel and led by former Google executive Douglas Merrill. Think Finance is backed by venture firm Sequoia Capital. Google Ventures, Mr. Thiel and Sequoia didn’t answer emails seeking comment.

Those companies and others use statistical modeling techniques to analyze large data sets, with the idea that weighing thousands of new variables will let them better predict creditworthiness. New variables include borrowers’ rent records and data from small credit bureaus, which can include information on prior payday loans, transactions with pawn shops, and collections.

Some criteria veer into the esoteric. Social-media posts about a car breakdown could indicate a risky borrower. So can filling out an application in capital letters, said ZestFinance.

LendUp looks at how quickly a user scrolls through the lender’s website. Users who jump to large loan amounts, without reading materials on the site, may be high-risk borrowers, said LendUp CEO Sasha Orloff. “It’s like walking into a bank and screaming, ‘I need money now!'”

The companies operate in a legal gray area. Some companies claim that a portion of their algorithms and data sources aren’t used to make credit decisions, merely to screen out fraud, and therefore don’t have to be shared with consumers. The Federal Trade Commission on Wednesday is set to discuss whether the algorithms are discriminatory or violate the privacy of borrowers.

Executives of LendUp, Think Finance and ZestFinance disputed the report’s findings, saying they are offering cheaper loans than were previously available to borrowers shut out of traditional credit. They said their companies protect consumers by offering flexible payment terms, financial education, requiring borrowers to pay some of the loan’s principal and not letting borrowers roll over unpaid balances into new loans.Payday lenders make a large portion of their income from rolling over loans, according to Pew Charitable Trusts.

The report lists LendUp’s maximum interest rate as 749%. But Mr. Orloff, the CEO, said that number is misleading because it applies only to loans of seven days. LendUp’s average annual interest rate is 220%, he said. He said the company’s effective rates are lower because borrowers get 30 days to repay and he doesn’t charge rollover fees.

ThinkFinance CEO Ken Rees said, on average, his customers pay annual interest rates of 240%. He said the company’s loans are “hands-down better alternatives than traditional payday loans” because they offer borrowers who repay loans more money at a lower rate, and other features.

ZestFinance CEO Douglas Merrill said his company also charges fewer fees than typical payday lenders.

But the executives acknowledged that even with more extensive statistical modeling and new data points, default rates were still high and that triple-digit interest rates are therefore necessary. The companies decline to disclose their default rates.

“The nature of the market makes it hard offer double-digit APRs,” meaning annual interest rates of less than 100%, said Mr. Merrill of ZestFinance. He said he employs more than 100 data scientists and data-mining techniques developed at Google to spot good borrowers.

“We hope to ultimately find a way to offer double-digit APRs,” he said. “The algorithms constantly get better. It takes time to get it all right.”

LendUp’s Mr. Orloff said he also hoped to lower overall interest rates over time. “You either believe that poor people should have access to credit, or you don’t. We do, and we have to create safe products for them,” he said.


About bambooinnovator
Kee Koon Boon (“KB”) is the co-founder and director of HERO Investment Management which provides specialized fund management and investment advisory services to the ARCHEA Asia HERO Innovators Fund (www.heroinnovator.com), the only Asian SMID-cap tech-focused fund in the industry. KB is an internationally featured investor rooted in the principles of value investing for over a decade as a fund manager and analyst in the Asian capital markets who started his career at a boutique hedge fund in Singapore where he was with the firm since 2002 and was also part of the core investment committee in significantly outperforming the index in the 10-year-plus-old flagship Asian fund. He was also the portfolio manager for Asia-Pacific equities at Korea’s largest mutual fund company. Prior to setting up the H.E.R.O. Innovators Fund, KB was the Chief Investment Officer & CEO of a Singapore Registered Fund Management Company (RFMC) where he is responsible for listed Asian equity investments. KB had taught accounting at the Singapore Management University (SMU) as a faculty member and also pioneered the 15-week course on Accounting Fraud in Asia as an official module at SMU. KB remains grateful and honored to be invited by Singapore’s financial regulator Monetary Authority of Singapore (MAS) to present to their top management team about implementing a world’s first fact-based forward-looking fraud detection framework to bring about benefits for the capital markets in Singapore and for the public and investment community. KB also served the community in sharing his insights in writing articles about value investing and corporate governance in the media that include Business Times, Straits Times, Jakarta Post, Manual of Ideas, Investopedia, TedXWallStreet. He had also presented in top investment, banking and finance conferences in America, Italy, Sydney, Cape Town, HK, China. He has trained CEOs, entrepreneurs, CFOs, management executives in business strategy & business model innovation in Singapore, HK and China.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

<span>%d</span> bloggers like this: