Marietta, GA – A new trend is developing to combine traditional credit scoring with social network data. Lenddo (www.lenddo.com) is a startup that uses social network data, called open source intelligence (OSINT) to assign risk factors to lending money to customers. The upside for this use of technology is the ability to lend to people that do not have access to traditional banking or credit sources, especially in third world nations. Even first world countries like South Korea and China are beginning to use the open source databases that are available to assign worthiness.
Yanhoa Wei is a pioneer in the field of Social Network Data Credit Scoring. Working and teaching at the University of Pennsylvania, Wei has published a terrific article on using algorithms and data analytics to predict social credit behavior. Social networks tend to cluster around behavior and individuals typically associate with likeminded users. If you can predict who joins and participates in the networks that are trending up in social responsibility, then credit worthiness can be assigned a positive or negative value. Behavior among social networks drives scoring just like credit worthiness is scored by past payment history.
Here is where you can find Wei’s published work: http://ssm.com/abstract=2475265