Let’s do some math together, shall we?
Case 1: You have a prospective borrower (client). And you have his credit-history and credit-score. You can decide whether or not to lend to him.
∴ Borrower + Credit data = Lending decision.
Case 2: You have a prospective borrower (client). And you DO NOT have his credit-history and credit-score.Or the data that you have, is insufficient. You can’t decide whether or not, you should lend to him.
∴ Borrower + Insufficient/ Missing Credit data = Difficult lending decision.
Now, THIS, is a problem.
And you may be surprised to know that, more than 75% of our population does not have access to formal credit because the credit bureaus do not have sufficient credit-history about these individuals. Quantifying it- there are more than 500 million people in India who do not have a credit-score.
So how do lenders solve this problem? How do they get access to sufficient and reliable data? How would they make better lending decisions for these people? Because deciding to only lend to 25% of the population, doesn’t sound very prudent, right? And eliminating creditworthy first-time borrowers is going to be an opportunity loss, isn’t it?
So when sufficient credit-history (read “traditional data”) is unavailable…this is when the need for additional data comes in. This additional data about the prospective borrower, that helps lender to predict behaviour of the borrower with respect to money.
This additional data that is generated from non-traditional sources, is referred to as ‘Alternate Data’.
Alternate data can be generated from various sources- geographical, identity based, behavioural, transactional and social.
These data points, help lenders to build up a virtual risk model in terms of his monetary patterns and/or habbits. This risk model is then used as the basis on which the lending decision is made.
(And we, at CreditVidya, have identified 10,000+ data points for a single borrower!)
Alternate data, thus, gives unique and valuable insights about the borrower. As a result, loans become smarter, and risk assessment is easier. The portfolio of the lender expands, and he’s able to tap a new segment of consumers altogether. Also, dependence on traditional data reduces. Alternate data complements (and supports) the traditional data available.
The World Bank is also working on introducing legal framework for the use of alternate data. Economies of Africa and Philippines have benefitted by leveraging the use of alternate data to drive financial access to their unbanked and underbanked population. And adopting the use of alternate data in India, financial institutions can also turnaround their lending/credit processes.
Find out how alternate data-based products can help you turnaround your lending process…request for a LIVE demo of our products here.