By Ben Cukier
From Our Forbes Files: In The Battle Between Online Lenders And Banks, Data Wins
Online lenders arrived on scene at the perfect time for Silicon Valley. Coming out of the 2008 financial crisis, banks – the traditional lenders – were slow to understand the way that consumers wanted to access credit and were (understandably) reluctant to take on risk. Rather than focusing on consumers’ needs and demands, banks were focused on other issues: regulatory challenges, capital constraints, and core technology built in the 1960s – inadvertently opening themselves up to the rise of online lenders. It turns out that making a lot of loans is a relatively simple task – relax underwriting standards, pay a lot of money to acquire customers, and revenue goes through the roof. Venture capitalists, enamored by astronomical growth, poured millions of dollars into online lenders. And grow they did. But the hardest part remains: getting the economics of lending right.
To credit online lenders, they figured out how and when consumers want money, and more importantly, what consumers do not want: they don’t want to sit in a branch with a loan officer to get it; they don’t want to wait three days for the transfer to come into their account; and they certainly don’t want to be told ‘no.’ However, the problem with online lenders has been the economics of the loans they make. Loan profitability is driven by the spread (the cost difference between the interest charged on the loan, less the cost of funding those loans), the cost of acquiring the loan, and the default rates of those loans. Online lenders start at a large disadvantage – banks use inexpensive deposits to fund the loans while the online lenders are dependent on raising debt or even more expensive equity. Banks already had the brand name and customers, while the online lenders needed to spend money (a lot of money) to find and attract new customers.
While many mainstream banks turned away consumers (either due to process issues or because they were deemed not credit worthy), online lenders touted their big data platforms, which use disparate data to better underwrite credit risk in ways common credit scores did not. They developed proprietary algorithms that better predict defaults than a simple FICO score. They leveraged the same data to target specific consumers on social media, and this very data from mining consumer behavior on social media also dictated the borrowing terms.
Banks, too, woke up quickly to the idea that they had to improve how they interacted with consumers. Not long ago, the idea that middle-class consumers could say that Goldman Sachs “offered clear terms, sent money fast, and dealt with them politely” would border on absurd. But many Americans are now able to interact with their banks through apps and get approved for credit just as quickly as with the online lenders. They can also get multiple products from their bank, something that is not available through online lenders. The banks, in turn, have multiple data touch points on both deposit and lending products with consumers, creating data that even online lenders (with their “proprietary algorithms”) can’t possibly find. Thus far, the results belie this: the banks, using traditional underwriting methods, continued to be highly profitable in their consumer lending divisions, while the online lenders piled on losses. While JP Morgan is making billions in profit, and suggesting that the “healthy” US consumer is responsible for this, Lending Club and Prosper are seeing “waves of defaults” as they tighten their “proprietary algorithms” to trim losses. These losses are occurring in one of the most benign credit environments in recent history. (Of course, now banks are chasing those same consumers they once shunned, and making loans to those same risky consumers).
To level the playing field, a new group of companies has focused on helping large banks as well as online lenders and other enterprises sort through this data to drive value for their customers. While a whole host of companies have popped up offering unique data sets, Demyst Data provides institutions a compliant and efficient way to find and validate that data, as well as more traditional sources of data. “Fintech innovators demonstrated that a data focus matters, however banks can apply that insight at a far greater scale to know their customers and launch new products,” says Mark Hookey, CEO of Demyst Data. “One client bank harnessed our data platform to launch an entirely new lending product from concept to issuing loans in 4 months.” Another new company, Factor Trust, created an alternative credit bureau reporting on the unbanked, and was recently purchased by TransUnion. PeerIQ lets originators and investors use traditional and non-traditional data to analyze and risk manage their portfolios (and also received an investment from TransUnion). dv01’s data management, reporting, and analytics platform brings transparency and insight to lending markets. These perhaps lesser-known companies, not the online lenders, seem to be the ones bringing the true promise of revolutionizing lending.