Covering Disruptive Technology Powering Business in The Digital Age

It’s no overstatement to say that new technologies and Big Data are upending many traditional industries. Sure, there are multi-billion-dollar darlings such Uber, AirBNB, and Lyft that are seemingly in the news every day. Make no mistake, though: Many other types of mature industries that usually fly under the radar are finding themselves under siege.

For instance, let’s discuss insurance. Generally speaking, it may seem stodgy, stable, and even boring. As I write in Too Big to Ignore: The Business Case for Big Data, though, it is ripe for the very type of disruption that Big Data can quickly bring. Thanks to usage-based insurance programs such as Progressive’s Pay as You Drive, many consumers are paying less for annual premiums. And the Big-Data insurance revolution isn’t stopping with car-insurance premiums.

Not Your Father’s Lender
By way of background, traditional consumer lenders have historically relied heavily upon basic financial and demographic data (gender, zip code, age, etc.) as well as Fair Isaac Corporation (FICO) scores. While not horrible across the board, it’s folly to think that these basic calculations always led to intelligent credit decisions. (Exhibit A: the recent subprime mortgage crisis.)

In the words of personal-finance expert Dan Macklin, “A growing number of lenders think that a person’s FICO score doesn’t tell the whole story and can even be misleading under certain circumstances. It’s become clear that there are more accurate ways to measure financial wherewithal—no FICO score required.”

Equipped with greater access to consumer and social data than ever and more employees with analytics degrees, many data-driven startups are changing the face of consumer lending. Two of the most promising include Sofi and Earnest, but they are hardly alone. In the words of journalist Amy Cortese, “Rather than green-shaded bankers, online upstarts like Kabbage, OnDeck, and others employ data scientists who crunch hundreds or thousands of data sources to assess whether a person or a business is a good credit risk.”

In some cases, these new data sources represent vast improvements over current (antiquated) data-collection methods. For instance, Josh Mitchell and Andrea Fuller of The Wall Street Journal write that the “the Obama administration is unable to get basic details about student debt due to an archaic system of data collection on its $1.1 trillion student-loan portfolio, hampering the government’s ability to help distressed borrowers and protect taxpayers.”