The future of credit scoring in India

How is credit scoring done currently? Will the new account aggregator framework redefine income assessment and credit scoring? We’re focusing on the retail consumer for the purpose of this blog post. Read on to explore.

Credit Scores are a key piece in the credit journey of the user. They help determine eligibility and rates for personal loans, home loans, other consumer durable purchases and more lending products. Let’s understand the score landscape in India.

Currently there are 4 credit bureaus in India – CIBIL, Experian, Equifax and CRIF. CIBIL and Experian are the most popular ones.

Firstly, what is a Credit score.

“A credit score is a number between 300-900 that depicts a consumer’s creditworthiness. The higher the score, the better a borrower looks to potential lenders. A credit score is based on credit history, number of open accounts, total levels of debt, repayment history and other factors. Lenders use credit score to evaluate the probability that an individual will repay loans in a timely manner”

As per investopedia

A credit score is built on top of what is a credit report. A credit report is simply an account of all your credit holdings. Consider you took a home loan from ICICI Bank. The lender(bank in this case) submits periodic information on your performance to a bureau. And the bureau manages this data to create a profile and maintain your history.

How data management works –

Based on the information submitted by lenders, a credit report is generated. Based on the credit report, each bureau uses their own algorithm to create a credit score. 

One must understand that the bureau has to use different identifiers to uniquely identify a customer. These include a combination of name, phone number, pan number and address. If some of you are wondering, why are you seeing someone else’s loans under your account, this could be one of the reasons other than misreporting. 

What are the factors important in a credit score? 

There are currently 5 factors taken into account to create a credit score. 

  1. Payment History
  2. Account Mix
  3. Account Utilization
  4. Age of Accounts
  5. Enquiries

The latest reports suggest that there are about 480m users with a credit score in India. This includes users with a longer tenure and ‘thin’ file customers. 

Credit scoring for New to Credit and ‘Thin’ file customers

Underwriting when there is sufficient information available in the bureau is solved to a certain extent. Banks, NBFCs, Fintechs have all spent considerable amount of time and money to address this base. However when it comes to underwriting users who don’t have a credit history or where the history is insufficient to complete an assessment of the customer, we run into problems. 

When underwriting customers, typically considers 2 things 

  1. Ability to pay 
  2. Intent to pay

The ability to pay looks at income, availability of capital, assets and such information to determine if the individual can pay the amount lent and thus decides whether the customer should be extended a loan. 

The intent to pay captures the willingness of the customer to pay back their credit. Currently this is based on past payment history as a determination of your future intent to pay. Are you regular on your credit card payments? Are you regular with your loan payments? What is the duration of regular payments? 

Innovation in ability to pay 

We’re seeing a lot of innovations in the ability of the customer to pay. Currently this is an unsolved problem for all groups of customers – salaries professionals, self employed and other segments as current methods like statement upload, netbanking access all fall woefully short. 

For salaried customers, currently lenders look at the frequency of month amount credited using statements. However the statement has several issues like incorrect account, corrupted pdfs and difficulty in accessing the statement from your banking provider. Netbanking faces issues like hesitancy from the end customer to provide information. 

  1. Account aggregator framework bringing access to multiple accounts – this is a very important development and one that everyone is most excited about.
  2. Statement processing improvements
  3. Income estimation using sms spend data
  4. Income estimation using balances and cash flow
  5. Using bank transaction and cash flow data to estimate income
  6. A more seamless process to process ITR returns. 

screenshot-2022-09-06-at-6.51.16-pmThe Account Aggregator network allows for sharing of transaction data or bank statements from savings/deposits/current accounts. This is interesting as it would make possible for reliable access to bank transaction data and allow lenders to quickly understand ability and intent to pay based on example – rent payments. The point to is as this gives visibility into multiple bank accounts, it could be a more reliable method than using ‘cut off’ scores for lending. And it would expand access beyond currently services salaries customers to a great extent. 

Understanding intent to pay – 

While figuring out a person’s ability to pay might be more straightforward, how does one understand the intent to pay? Typically the intent to pay is established based on – 

  1. Payment frequency – length and record of re-payment for different existing products. i.e is the user interested in maintaining their repayment and are they regular with their payments. 
  2. Type of product – Example a home loan customer is considered to be a more stable candidate compared to someone repaying a personal loan. 

But that brings us to the next interesting question. How do we determine the intent to pay when there isn’t sufficient repayment data? In the absence of this information, one tends to use information that can be a proxy for repayment behaviour. Which brings us to the next topic. 

Alternate data and its usage

Below are the different avenues to alternate scoring currently used by lenders- 

  1. Using contacts to understand networks and relationships
  2. Utility bill payments – phone, electricity, internet 
  3. Insurance payments 
  4. Rent payments – As it is a big value item, it can be suitable to be used 
  5. Financial assets – MF, Fixed deposit to estimate networth 

Rent payments – 

Rent payments are usually high value and comprise a sizeable portion of one’s income based on the location. Thus rent payments are useful to understand both ability to pay and intent to pay. Also they can enable new to credit customers to get substantially higher limits on credit cards and personal loans and better interest rates on home loans. However there are risks about verifying the validity of the renter. Companies like Boku Inc are enabling players to get access to this information and newer companies are starting to explore usage of this data to solve the cold start problem.

Postpaid and internet bill payments – 

Postpaid and internet bill payments are interesting as they enable to cover a new segment of users. The average postpaid bill is estimated to be Rs. 300 and the internet bill in similar range opens up possibilities for credit lines till 20k. 

What are some of the interesting approaches you’ve seen? 

The emergence of BNPL(Buy now, Pay later)

BNPL has been the rage in older markets like US, Australia. And for good reasons. BNPL is exposing a lot of new customers to credit and expanding the market. BNPL providers provide a starter limit like Rs. 2000 and then upgrade the user post several successful repayment cycles. Also with the new guidelines outlining reporting of BNPL lines to the credit bureau, this is also creating a new record of customers. Thus these users can move to more mature products like Credit Cards, Home loans etc. 

Some questions to think about: 

  1. Will the user be able to manage a significantly higher limit? 
  2. Will the user repayment behaviour continue to hold?
  3. Does the change in cycle from a 15 day cycle to 30 days affect the customer significantly.

As we’ve seen Credit score and scorecards are in the process of evolution as financial service providers seek to expand beyond the existing set of customers. Also scoring is moving towards a more real-time basis that seeks to understand the current financial situation rather than a few months old. However hurdles still exist and it will be interesting to see how it evolves. 

If you found this article useful, please feel free to share with your friends. I’m a product and business builder currently re-defining the future of credit in India. If you’re interested to work with us, please DM me here or on Twitter. I love all things consumer – fintech, social, video and music. And also invest and advise in startups in my free time. 

If you’re interested in learning about the future of QR payments, you’ll find this blog post useful. 



One response to “The future of credit scoring in India”

  1. Very insightful article.
    Would add, in my experience with thin customers telecom payments are a very good indicator of their intent to pay. Trusting social is doing a very good job for this segment.
    Also, would love to see more examples of startups working in alternative under writing data from India.


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