If FICO & Klout Had A Baby
Credit, though we take it for granted, is a revolutionary human invention. Because I trust you, I will take as trade-value for this item, a payment at some point in the future. Today, though, you only get a promise. It is as old as commerce itself, and it is the grease upon which the wheels of our economic engine have run forever.
When Bill Fair and Earl Isaac created Fair, Isaac and Company ( FICO) in 1956, they launched a product which had an extraordinary effect on commerce. Equifax was an O.G. big data company that had collected information on millions of Americans and Canadians. This data was used to assess risks for insurance providers, who were giving policies to consumers. FICO took data sources like Equifax to create a rating system not for insurance risk, but for any type of transaction, normalized across a set of behaviors: the credit score. Atop the credit score, companies like VISA, Diner’s Club, and others began launching credit cards, merchants around the country and world began accepting these credit cards, and consumer credit transformed. Originally, an individual’s credit-worthiness was limited to a local store owner’s comfort-level with that individual “keeping a tab open”. It was highly localized, and based on very relatable trust and reputation.
The credit score is outdated. Companies have launched since FICO, and the bureaus themselves have their own scores. But in the Information Era, where access to data about individuals is orders of magnitude better than at any time in human history, surely the big data that informs the credit score should evolve as well.
To date, measuring credit is limited to an individual’s credit history, which is Liabilities. It is repayment history, repayment percentages, and length of credit lines. But think about the store-owner who allowed customers to “keep a tab open” and you quickly realize that there are other things to measure, which are no less powerful indicators of an individual’s likelihood to keep the promise to pay, which I’ll list below.
Assets: Someone with $1,000,000 in savings today cannot buy a car using credit if she does not have a credit card. And even if she has a credit card, if she has limited credit, because she just got the card, she will pay a big penalty, with a high-interest rate. Measuring what an individual has solves that.
Behavior: Someone who has saved 30% of his paycheck for the last 10 years, but never opened a credit card, has no credit history. If that paycheck was only $50/month, that is clearly a very trustworthy individual. And there are other indicators that are also highly relevant, if less obvious. Say, for example, that he additionally never missed a class in college, has a 401K, and spends roughly the same amount every month?
Reputation: On the social web, there are signals about who an individual is that are understood by the collection of her network. Do her friends have stable behaviors? Are there people with data trails who can vouch for her? That local store-owner would want to know that the person they are opening a tab for isn’t a stranger to the community, and so measuring that activity is, itself, an indicator.
The credit score, and credit system more generally, is broken today. A system that strictly relies on liabilities, leaves out millions of trustworthy individuals who deserve access to credit. And as our financial system increasingly moves online, and credit becomes more and more central to access to bigger purchases, this is a social issue. At Collaborative Fund, we love discovering startups whose products are radically inclusive; it’s my favorite goal of technology. And one of the most effective ways to achieve that is through credit. We will announce some investments in this category soon, so stay tuned.
Parting thought: did you know that a big part of the popularity of payday lending isn’t the immediate cash, but the fact that the lenders develop warm, personal relationships with their customers in a local vernacular? It’s a more inclusive experience than a commercial bank. Loosening up credit does not have to mean making it riskier, nor does it have to be a matter of Fed policy. Just by being empathetic, and framing the data we are already capturing, we can provide risk-adjusted credit to the millions of Americans who don’t yet have it, but deserve it.
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