It is a well-known fact that, banks, financial institutions and NBFCs constantly check credit scores and CIBIL scores, in order to gauge the creditworthiness of an individual. However, of late, the trend has registered a shift as this traditional process often leaves out a lot of individuals from the radar. At the same time, less than transparent methods and reference points used to calculate CIBIL scores, make many consumers ‘un-scorable’.
As a solution, alternate credit scoring models have emerged and they are more inclusive as compared to traditional methods of credit scoring. As far as the use of social media behaviour is concerned, the Fintech space leads the way. Most fintech companies focus on conducting a social media behavioural analysis in order to gauge the creditworthiness of an individual.
According to Shweta Jain, Financial planner and founder, Investography, “since the use of Internet has increased manifold, banks and financial institutions often track social media behaviour to check credit-worthiness of people.”
Fintech lenders are active in this aspect to a great extent. They collect non-traditional data from diverse sources and its volume is usually much larger than that of data from conventional sources. It could include several sources such as phone usage patterns, payments and transactions, payment history of utility bills and EMIs among others.
New age credit scoring methods include a host of activities such as collect data from a person’s digital activity connected to his or her phone number make it much easier for digital lending platforms and other marketplaces to access highly detailed and dense data sets.
Also, since these platforms have information about a consumer’s mobile phone usage, they can also access their social media usage and network to assess one’s creditworthiness. With information gathered from individual’s profile on various social channels such as Facebook, Twitter and LinkedIn among others, digital lenders have the opportunity to in fact create a more accurate credit profile of borrowers and also understand their personality to a great extent.
Insights and information derived from a person’s social networks are first used to verify the identity of the borrower and ensure whether the professional, personal and financial details provided by them are accurate. The technique used by them includes Artificial Intelligence (AI) and Machine Learning along with advanced analytics. AI algorithms are used to check the quality of connections with people who comprise a part of your social media network, which gives financiers a better insight as compared to traditional financial data, to help build a credit profile of borrowers.
It might come as a surprise, but along with the profile of borrowers, lending platforms also analyse Facebook profiles of their connections to see how stable and responsible they are, based on their work history and credit profiles. Some lenders even access the patterns of borrowers’ friends to check if any of them have already borrowed from the platform and then obtain that person’s payment history to use it as a predictive indicator of the repayment ability of the borrower in question.
Also, professional platforms like LinkedIn offer a look into the quality of borrowers professional network and their job history to verify their employment history along with their identity.
Your social media posts reflect your thought process. Choose your friends in the virtual world as carefully as you would choose friends in real life.
If you have a good employment history and enough stable connections in your professional network, highlight them enough to build your profile as a credible borrower.
Along with this, make sure to constantly review the history of your social media posts and get rid of posts, which may prove to have a negative impact on your overall profile.
Doing all this consistently and regularly before applying for a loan from a digital lending platform will improve your credit profile and increase your desirability and credibility as a borrower among lenders.