Register for PaymentsJournal
Back to News
Big (Alternative) Data in Credit Decisioning
January 31, 2013
Slate Wednesday published a blog post profiling a number of companies involved in P2P lending and online short-term and payday lending which rely on social networking data from borrowers to help gauge credit risk. The post also examined the technologies available to the companies via vendors such as Kreditech.
Lenddo, LendUp, and Wonga all use such alternative data and scoring technologies to help screen applicants. Some of the elements involved in these types of alternative screening processes can include location data (GPS, micro-geographical), social graph (likes, friends, locations, posts), behavioral analytics (movement and duration on the webpage), people’s e-commerce shopping behavior and device dats (apps installed, operating systems). The core thesis of the piece:
All these efforts are premised on the sensible idea that current models of assessing creditworthiness focus on too few indicators, shutting off many potential borrowers who pay their bills on time but don't have good (or any) credit histories. “Big data” can separate the lazy slackers from those who truly deserve better loan terms. The goal, then, is to get as many data as possible, perhaps even nudging potential applicants to pre-emptively disclose as much information about themselves as possible.
The focus of the blogger’s argument is privacy. Even though new technologies may facilitate greater access to credit, what is the price in terms of personal privacy for those needing expanded access?
to read more from Slate.
Contact a Mercator Advisory Group Analyst
Search News Items
Advertise With Us
Recommend RSS Feed
Join Buyers Guide
Host a Strategy Session
List a Calendar Event
Give Us Feedback
Contact Mercator Advisory Group
© & ™ 2002 - 2015 | Mercator Advisory Group. All Rights Reserved
Terms and Conditions
Make Us Your Homepage