Following my previous post (Part 1 - Traditional Credit Rating) you hopefully now know your credit score and you have mastered the art of managing your credit score. Now brace yourself — what if I tell you that you probably shouldn’t be too excited about it? Read on.
The traditional credit rating model has a fundamental problem – it tries to assess a borrower based on his / her financial history. What happens when someone doesn’t have a financial history? In many developing countries, a large section of the population still remains outside the formal financial system, without any financial history. It is hard to assign a credit score to such individuals. Note that income is not a factor in credit scoring so there is no correlation between their low income and their creditworthiness.
Consider another scenario. A fresh graduate with a new job is applying for a credit card and doesn’t have a financial history in the credit file. What is the likelihood that the person will be a good borrower and will pay back future debts? It is hard to predict with no existing financial precursor for the person, and it is a big risk for the lender. Will the lender refuse to lend outright? It may choose to, but then it would have the downside of losing out on potential new customers. Lenders want to offer their products to greenfield customers, but only to ‘good’ borrowers.
So how can lenders be sure?
In today’s digital world, information is abundant and all around us. Social media contain a vast source of information about individuals in modern society. Social information refers to data which is obtained from internet and mobile based services including social networking sites (Facebook, Twitter, LinkedIn etc.), blogs, wikis, online forums, discussion groups, and media-sharing sites. The information contained in these channels are easily accessible and can be easily analysed to derive opinions about consumers. Such information, outside the limited set of their available financial information, tells lenders more about their potential customers. This is a key trend which increasingly aids decisions about credit worthiness of a consumer during the underwriting process.
Over the last decade, global availability and improved speed of internet connections, improved software and penetration of handheld smart mobile devices have accelerated the penetration and usage of social media. They have continued to gain widespread acceptance from all demographics in varying degrees. Some widely available statistics (as of Jan 2018) below prove their popularity:
There are many more other popular social media. These eye-popping numbers go to prove the acceptance, popularity and penetration of social media in our social and economic lives.
A third of the world’s population interact through these channels, generating a vast amount of data daily about their lives, preferences, demographics, abilities, affiliations — almost everything! This information, in most cases, is free and shared voluntarily. The information trail left behind by netizens is easily accessed and processed using powerful data science tools, which help create a comprehensive profile about consumers.
Using this abundantly available data, financial institutions are discovering new ways of working. Globally we have started to see interesting examples of using social data like:
Researchers are now paying more attention to the use of social data for credit scoring. A few of these studies are highlighted below:
Aligned with the increasing popularity of using social data for credit scoring, there is a breed of emerging companies all around the globe. Some of the most popular companies who provide credit score using information available on the internet are:
https://www.lenddo.com
https://www.neoverify.com
http://www.friendlyscore.com
https://www.affirm.com
https://www.kabbage.com
https://www.kreditech.com
There are many more upcoming companies exploiting this emerging area of financial lending. Websites used by these companies are the popular social websites including Facebook, Twitter and LinkedIn. They apply different algorithms on the data to analyse them and to provide a rating. The algorithms are proprietary to the companies’ business models.
Although a popular and emerging area, social data mining also presents us with challenges, some of the most common ones are:
Using social data alone for predicting credit worthiness is still evolving as an alternative model, hence collection and application of social data must be used with caution. Although applying social data tells us much more than established formal, financial models alone – there are areas where more research is required to eliminate uncertainties.
Watch out for part 3 of this series which goes beyond financial credit rating.
Consumer Lending Using Social Media Data