One of the four operational and licensed credit bureaus in the country, CRIF High Mark, recently announced a tie-up with CreditVidya, an alternative data-based credit assessment platform. Abhishek Agarwal, CEO and co-founder, CreditVidya said that over 40 lenders, including banks, NBFCs and fintech companies are currently using the company’s alternative data-based scoring model. “We have observed that our model enabled a 15% higher loan approval rate for applicants having a score from credit bureau, compared with traditional methods of underwriting. The scoring also ensures 33% lower delinquencies for the same level of risk," he said. Let us take a look at what this alternative data is and how is it being used.
Credit bureaus have predominantly relied on traditional data like repayment history of loans and credit cards. However, the digital footprints for consumers have gone up significantly over the past few years and fintech companies are mining that. “Digital footprints of an individual go far beyond social media data. A transactional SMS on your phone or your transactions to book a cab, order food or any other item online is also a digital footprint. Mining that data to give you a credit score is what we are doing," Agarwal said.
Not just specialised service providers like CreditVidya, even NBFCs are using the fintech model to expand their credit business using alternative data points to arrive at a credit decision. For instance, LoanTap, a fintech platform having an NBFC licence, does not consider traditional bureau scores to be sacrosanct. “We largely operate in urban geographies and most of the customers do have a credit score. But credit bureau scores are not sacrosanct for us; it is just a part of the decision-making process," said Amit Tewary, chief operating officer, LoanTap.
LoanTap also uses a bank account statement reader developed in-house, Tewary said. Traditionally, lenders used the bank statements to be sure about timely credit of salary in an account and to check if any other EMI is already in place. When a borrower shares his or her statement with LoanTap, the lender arrives at parameters like average inflow and outflow of the borrower in a month, average balance in the account, the dates with the highest average balance, and there is a score associated with each parameter. For instance, if someone has a very high salary but is a habitual online gambler, which will be reflected in the statement via repeated payments to online gambling websites, that person is considered to have a risky profile.
Though a lot of details emerge from the analysis of a banking statement, lenders are also looking at factors like stability of job or residential stability, and there is a score associated with each of these. “Someone staying in a regular residential accommodation is considered as someone who is more stable than a person who is staying in a bachelor accommodation where five to seven people stay together. Somebody hopping a job every four to six months, irrespective of how high that person’s salary is, says something about his stability and we will take it negatively," said Tewary.
For younger borrowers
The detailed analysis of bank statements, residential and job stability as well as transactional details are useful in arriving at a credit decision for people already working. However, some fintech companies are also trying to reach out to younger borrowers like college students.
One such platform, mPokket, gives loans as small as ₹500 to its customers. The platform gives loans only to students in undergraduate and postgraduate courses who are above 18 years of age. But how is the risk in these loans determined?
For every borrower, the platform only gives ₹500 as the first loan and the amount can go up depending upon the repayment history and other factors. Not only does the type of institution and level of course at which a student is studying impact the student’s profile, the behaviour of their peers on the platform also impacts their profile and credit limit, said Gaurav Jalan, founder and director, mPokket. A lot of data used for analysis is gathered from the borrower’s smartphone as the lending is only done through the company’s app. Typically, transactional SMS and contacts are used to check financial transactions and to determine if some of the app user’s contacts also use the app. The average loan size from mPokket is ₹1,000 at present and it charges an interest of 2-3% per month, which translates to 24-36% per annum.
With use of personalised non-financial data for arriving at credit decisions, borrowing money could become easy for consumers. However, borrow carefully and be sure to repay your dues on time so that it does not impact your credit profile.