Ever since Faircent.com started operations, we have facilitated lending for countless individuals and entrepreneurs. What has been deeply satisfying is the ability to help numerous small businesses across the country get access to funds at crucial times and ensuring their business continuity.

Fintech platforms thrive on its ability to use a plethora of data to help borrowers who may have hitherto remained outside the formal financial structure to raise funds at competitive rates. There are other sets of borrowers who have a credit history, but would want a better deal when it comes to their loans. By cutting away the middleman and connecting a borrower directly with lenders, P2P platforms have the ability to provide loans at significantly lower interest rates. However, the question remains- can the rate of interest be lowered further. The answer would be a yes.

Information asymmetry

Determining the rate of interest applicable on a loan is dependent on multiple things, the chief among which is the credit or risk profile of a borrower. This is judged basis the credit, financial and personal data provided by the borrower. The problem in most cases is that there is always a limited set of data and information available, which may not provide a comprehensive picture. There are credit rating agencies, but a large section of the population is not covered by these agencies. The problem is even more acute in the case of small businesses where official credit ratings are often almost absent. In any case the credit rating agencies also track a limited number of variables, which again cloud the true picture. Since an element of uncertainty remains, rates of interest tend to factor that in and rise.

One may argue that this maybe true for borrowers with poor or no records but if a borrower has already taken a loan from a bank and has a good credit profile, then he must be at an advantage when it comes to accessing loans at lower interest rates. Unfortunately, this is not necessarily the case because often beyond a snapshot of a borrower’s profile, bank refuse to provide data on their customers.

It is very important to understand that banks would never want to divulge the credit profile and information about some of their best borrowers. Banks want their customers to only bank with them especially when it comes to taking loans. By controlling access to financial data of HNIs and credit-worthy customers, banks effectively reduce the customer’s ability to get lower interest rates from other sources.

Monopoly never works and when all credit information is concentrated with one or few banks or FIs, they can choose to monopolize the same, seriously affecting the person’s ability to access cheap credit.

Most credit-worthy borrowers who pay their bills and EMI’s on time or maintain healthy balance in their savings accounts can actually get lower interest rates on their future credit requirements by not limiting their financial and banking transaction with only one or few players. By spreading their credit info across traditional banks, FIs and Fintech a person is able to break through the “data-ceiling” and force different FIs to compete with each other for the borrower’s business. A credit-worthy borrower is always much in demand and should not be made to suffer only due to lack of access to data.

Even the government realized the impact of this information asymmetry and is taking steps to correct the same. Public Credit Registries (PCRs) are a step in this direction. The PCR has been envisaged as a database of core credit information – an infrastructure of sorts on which users of credit data can build further analytics. It will strive to cover all regulated entities (i.e., financiers) in phases and in this way get a 360-degree view of borrowers. It will facilitate linkages with related ancillary information systems outside the banking system, including corporate filings, tax systems (including the Goods and Services Network or GSTN), and utility payments. Thus, the aim is to create a centralized pool of data which is accessible to all and not limited to only the institute where a person banks.

Currently credit information is scattered across multiple systems and institutions which operate in silos. They do not talk to each other, which in turn leads to deficiencies in decision making. Faircent.com’s fully automated credit evaluation mechanism spends a lot of time, effort and resources to evaluate a borrower profile by accessing 400+ data points evaluated across 120+ parameters. It is access to this data that allows our algorithm to provide access to cheap and fast credit to lakhs of individuals and small businesses across India.