Big Data is one of the new new things in alternative financial services, but at this point the smart money says that it probably helps lenders more than it does borrowers.
best schools to develop new underwriting algorithms with the purpose of reducing their exposure to risk. In the ZestCash model, better underwriting makes for better profits but not for lower prices. ZestCash is not exceptional - in fact, they are probably the industry norm -
but there are other companies that want to use data to lower interest rates on their loans.
With the benefit of empirical data from its first few years in business, ZestCash now runs several parallel models from each application. They can extract thousands of data points from scores of different information sources in order to give a borrower a decision in just a few seconds.
The upshot, according to the company's COO, is that they can increase "net payback" by twenty percent. That's surely a boon for ZestCash and it might explain why it has attracted $73 million in VC money. Nonetheless, ZestCash loans still have APRs north of 300 percent. The company must not feel too good about what they are doing, because they've also pursued an innovative regulatory structure. They are now partnering with tribal lenders (think "protein coat").
A key failing in this approach is the disconnect between learning and lending. ZestCash loans default less frequently now because their machines have grown smarter. One of the justifications put forth by traditional payday lenders is that they use risk-based pricing. High APRs at the local payday shop reflect high loan losses. But ZestCash loans cost just as much today as they did eighteen months ago, even though loan losses are lower. Moreover, a repeat ZestCash borrower with a record of making his or her payments on time is still not going to be offered a better rate of interest.
ZestCash recently replicated into two parts: SpotLoans, where a person can pay $879 in interest to borrow $600 for six months; and ZestFinance, where other banks can buy Zest's analytical insights to enhance their own Alpha.
Tomorrow I will write about a company that is trying to share the gains from big data with their customers. Their prices are still fairly high - more than 200 percent to start - but they soon drop to the price of a typical sub-prime credit card. To be fair to those VC guys, they are also attracting early-stage investors.
Excuse my soap box, but here I go: I think it is a shame that some of our brightest minds seem to be thrilled and fascinated with finding ways to undermine the finances of the people at the bottom of the pyramid. ZestCash Douglas Merrill - the former CIO of a fairly intelligent company (Google) - is just one of an army of our best and brightest working for companies whose core product could arguably be thought of as predatory. Lately, I've been doing a lot of research into private for-profit universities. Is it surprising to find out that there are other firms hiring the "best and brightest" - Goldman Sachs being one - who are also the lead investors in some of these schools? Should MBAs from the Ivy League be billing the Department of Education as much as $90,000 to teach a student how to get a job as a line cook? To the extent that many of those best and brightest benefited from plenty of merit-based scholarship, is it appropriate when they extract this kind of profit from students who may never get out from under their culinary school debt?