Finding credit
How Artificial Intelligence is helping build the country’s credit profile
Note: This article was originally published in MoneyControl.
Rohit switched the call off forcibly, muttering curses at the loan officer at the other end who he had just cut off. It was clear there was no chance he was going to be approved for a loan. The entire conversation played out like a disaster in slow motion as the loan officer tried her best to explain why Rohit was not eligible for a loan from her bank.
“You’re young and have just started at your first company. You’ve only been there a year,” she said, trying to sound sympathetic. Yet all Rohit could think about was how hard it had been for his government employed parents to put him through a good college, and how he had worked hard to get through it to finally land a plum job at his dream company.
And now with his mother being admitted in hospital and diagnosed with a life threatening disease that needed an expensive treatment, all he wanted was to be able to be there for her and bear some of the expenses.
He felt crushed.
This story and variants of it play out every day in India, a rapidly evolving market where traditional players like Banks are struggling to keep pace with the changing landscape of their clientele. The loan officer would have given anything to be able to approve Rohit’s loan request. She felt just as crushed, shackled by the limitations of the existing tools in her hands.
“If only there was a way for her to be able to assess his creditworthiness without being dependent on CIBIL, which rated him a -1 — i.e. no credit history.”
There is now.
A number of new techno-financial companies are tackling exactly this problem. Their hypothesis — we live in a data engorged world, the era of Big Data. And to make sense of this large volume of data, we also have the serendipitous confluence of two technological advances — High Speed Utility Computing and Artificial Intelligence (AI).
With these advances we now have the tools to process large volumes of alternative data generated from our data rich lives (e.g. social media, mobile phone data etc.), and build sophisticated AI models that can among other things predict lending behaviors like propensity to pay on time or delay repayment, risk of default behavior, product-customer fitment, product yield analysis etc. to name a few.
These new age companies are building their own credit risk models that work either in conjunction with traditional credit scores like CIBIL or in some cases as a better alternative, as in the case of salaried millennials, where CIBIL has little to no predictive capability.
As a lending entity they have a simple value proposition when it comes to gathering alternative data —
“The more we know you, the more we can model our risk and the more you can access credit on the strength of your actual credit worthiness. The less we know you, the less credit is available to you.”
It’s that simple.
Of course, these companies have a responsibility to protect and prevent misuse of the data that they collect to determine the borrower’s credit worthiness. But that’s the grand bargain in a nutshell.
This should then, in turn result in lending (statistically at least) to the right person more often than not, which in turn means a lower default rate and a lower Non-Performing Asset (NPA) rate and thereby an overall improvement in the health of the credit market.
Artificial Intelligence applied to alternative Big Data sources is allowing the credit market to function sensibly by identifying the “true” credit worthiness of borrowers across the market, thus helping to improve and build the country’s credit profile.
And for people like Rohit, these new age companies are a godsend, as they have taken on the mantle to truly understand (using Data Analytics and Artificial Intelligence) that he is not a credit risk and thereby extend him the loan he so dearly needs to meet his personal needs.
