Note: This Blog Originally Appeared at the UrLoan.com blog.
Would you sign up for a loan from your text message service or favourite social network?
That’s the question that China’s Tencent Inc, makers of the popular WeChat messaging app, are asking users with their introduction of a new feature called Weilidai — which literally means “a tiny bit of loan”— allowing users to borrow up to 200,000 yuan ($31,350) without guarantee or collateral. WeChat is used by an estimated 600 million or more people, making it one of the world’s most popular IM services.
Asian messaging apps often feature multipurpose functionality that you wouldn’t otherwise expect to see in a chat client, from cab-hailing to ticket-buying, and WeChat is no exception. Now, this multivalent approach will extend to the world of personal and peer-to-peer financing.
The Wall Street Journal notes that the credit assessment process, which reportedly includes assessing individual loan status information from the People’s Bank of China, could take less than a minute. Interest rates can vary depending on individual credit levels; the average daily rate is believed to be 0.05%, while the terms for loans could stretch up to 20 months.
One of the most interesting (or arresting) features of Weilidai is its reliance on at least some degree of social-network data mining to come up with algorithmically generated loan terms and rates. In an age when mobile data privacy has become a hot-button issue, especially in one of the most internet-restrictive countries in the world, this method of data collection will need to be closely scrutinized so as not to push past users’ privacy boundaries. Reportedly, simple payments such as how much you spend on taxis and restaurants will be taken into account as they feature in WeChat’s e-commerce functionality, as well as any number of micro-transactions and large payments alike.
While a number of online, peer to peer and emergent financial technology-driven lenders in North America are beginning to take such contextual information into account in their approvals process, effectively allowing customers the chance to be represented by more than their hard credit scores, this analysis is not often carried out in such a directly linked or automated manner. Fully automated approvals can indeed increase the speed with which borrowers can access funds, but come with the caveat that they may not be able to contextualize individual borrowers’ needs and personal situation with the clarity of a traditional application process.
So, can North American financial consumers expect a Bank of Facebook to pop up in their news feeds in the near future? Certainly, the monolithic status of such entities as Google, Facebook and others makes these corporations the butt of criticism for their efforts at expansion into nearly every conceivable facet of the tech-connected world. However, differences in the regulatory environments and legal precedents for financial corporations may stall the development of such services in much of the world.