Clearly the early users of social networking data were doing a lot of sentiment analysis on it to determine trends for companies, products, politics etc. Things have changed now - governments are interested in scouring billions of bytes of data generated daily in social networks for intelligence hints, Fin-Tech upstarts are starting to successfully use the same data to disrupt financial services - for example, the lending industry.
The sale of Troo.ly to Airbnb spiked my interest into this. Research revealed the existence of a whole bunch of companies and existing patents in the science of using social network data to determine a person's trust or risk score. Appears that lot of tricks have evolved in the last five years. However, this is quite scary as well! In the next few years, I can see a lot of people trying to use this score instead of just pulling the credit scores in business transactions. This could be landlords, people selling goods on craigslist (e.g cars etc), small business engaging in seasonal hiring to keep costs low. It could certainly replace simple background checks. While this is all great, the scary part is that this presents a Kafkian situation for people at the other end of it. Unlike their FICO scores, there is a lot less visibility into how the machine learning algorithms work. Imagine a customer service rep trying to explain why your social risk was considered too high when renting an apartment for a few days on AirBnB.
This led me to findings how the big Chinese payment companies (Ant Financial, Baidu) are now planning to use all the data that they collect from repeated payment transactions and the social networks they own to determine credit scores of people. This idea is definitely not new but it is breaking new ground in the last couple of years. For example, companies like HelloSoda, Guardian Analytics have been doing risk scoring for quite some time now. There are also a lot of banking and lending upstarts in U.S and EU - Kabbage, Simple, Moven, Fidor etc. However, FinTech has taken social networking data to a new level now and this time its not just to send marketing and sales offers (like the famous American Express examples show) or to make your banking very cool indeed.
There are multiple innovation areas - companies like Jumo have made a significant penetration in the underbanked markets of Africa to enable micro-lending based on social networking data that they collect. In China, Baidu already has more than 10% of its assets involved in some kind of lending, the biggest being in the education market. Now Alibaba and Tencent are also getting involved. Not only is the mobile payments market in China set to pass the transactions Visa and Mastercard process but it is also spinning out new uses of the data collected. In one way it looks like social networking companies may have an edge over managing risk and may have slowly started to disintermediate traditional lending companies. There are 800 million people using Tencent for payments that have no credit history with the central bank and the daily transaction patterns reflect a lot about their behavior and risk. Take a look at AutoGravity - users can not only select cars, schedule a test drive but once they connect it to their social networking account, the site also prefills the application, verifies identity and lines up four lending companies without having the user fill up scores of forms or go to an office. All on the mobile phone in minutes. Facebook, Google and Apple could be doing this next year. It all starts by focusing on an underserved market and there are enough in financial services - there are almost 64M Americans without sufficient credit history and almost 2B people around the world without a bank account.
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