Authored By: Debleena Majumdar

Debleena has been a part of the corporate sector for 15 years now and has worked with firms like GE, Prudential, Fidelity, JP Morgan and HP while she was finding her own story. Over the last three years, as part of the Leadership team of BRIDGEi2i Analytics, one of the fastest growing datascience firms, and the Head of Sourcing and Marketing at Unitus Seed Fund, an Impact Venture Capital Fund, she was helping identify and build stories. Currently, she is the co-founder of Kahaniyah, where she uses storytelling to improve Strategy and Marketing outcomes in business. A keen writer, stories, music and numbers are her passion.

“Cat: Where are you going?

Alice: Which way should I go?

Cat: That depends on where you are going.

Alice: I don’t know.

Cat: Then it doesn’t matter which way you go.”

The quote above from Alice in Wonderland could have just been created just for the current wave of Fintech led digital disruption that is sweeping across India’s financial services system. Ubiquitous mobile access, increased advent of middle class, a slew of government measures and nimble Fintech firms as well adaptable banks; there seems to be as much buzz as there is, confusion. And in the midst of all of this, the stage seems to be set for a dramatic new entry.

From Fintech to Financial Inclusion

While the Fintech revolution has made consumer choice, access and customer experience easier for the consumers who can afford it, India’s unbanked and underbanked see a very different view of the market. The need for financial Inclusion is not new in India. Post-Independence, India had a plan for Financial Inclusion. And the last few years have seen quite a few government initiatives that have tried to address the problem: Pradhan Mantri JanDhan Yojana (PMJDY) in August 2014, the Jan Dhan Aadhaar Mobile (JAM) trinity articulated in the Government’s Economic Survey 2014-15 as well as the special thrust on financial inclusion by the Financial Stability and Development Council (FSDC). The push has definitely seen a change in the number of people who have basic access to banking system.

Figure 1:

Data for 2011 and 2014 were from World Bank’s Development Research Group ‘Global Financial Inclusion Database (Global Findex)’ report. 2016 data was the estimate number that has emerged from government updates.

Why is financial inclusion still a problem then?

Despite more customers having valid bank accounts, the banks find it difficult to service a large population of people who need money for their small businesses, farms, education. That in turn, makes this segment of people who are denied such loan access, turn to other alternatives:

– Money lenders

-Chit funds

-Microfinance Institutions

The following two graphs give a picture of the real problem:

1. Lack of creditworthiness: A CIBIL score of 750+ is considered a good creditworthy score for getting a loan. The real problem then is that rarely one fifth of India has a credit score and hence is not eligible for capital they need from individual expenses to growth of their small and medium enterprises. Banks and NBFCs find it difficult to service this market.

As Figure 2 shows below, the source of loans drastically depending on the person’s economic condition. The poorer the person, the more he/she relies on the informal lending channels such as money lenders, chit funds and the like.

Figure 2:

Data from Applied Research for Digital Finance Inclusion:

2. Even if they do lend, with the increased bad loan pressure on banks which stands at a staggering $180B, banks are obviously wary of entrenching deeper into these segments which might show a lower repayment rate and also increase the chances of fraud. The bad-loan pile-up (figure 3) is reaching an unsustainable level of more than 10% of total loans as of 2017.

Figure 3:

Data: Reserve Bank of India, Bloomberg

The spotlight falls on Alternative Lending, the dramatic new entrant to the stage. Are alternative lending firms today in a unique position to address this lending gap due to lack of traditional data and current risk assessment methodologies through their innovation in data and technology?

The alternate reality in India:

According to Tracxn, the alternate lending market, that seems to be knocking on the doors of the traditional banking system, consists of over 200 companies in India currently and is the 2nd highest funded segment, post payments. The market structure is as follows:

Figure 4:

Data: Tracxn

The companies are structured as:

  • Direct Lender Platforms that have a lending license and take the loans on their own books.
  • B2C Marketplace Platforms that tie up with third-party lenders for loan origination. Lenders include financial institutions and banks.
  • P2P Marketplace Platforms that allow individual investors – accredited as well as retail.

At the heart of these companies, is their often-proprietary data models, data that goes beyond traditional Credit Bureau data to find a glimpse of people who could be “Future Prime” (People who either do not yet have any credit score or do not have a strong credit score but will in future become the prime lendable segment.) Being able to identify this Future Prime segment would give the Alternative Lending firms an ability to address the financially excluded population in a very unique way. And once they prove creditworthy, other financial services options become available. While alternative lending could cover both the corporate lending (small and medium business lending) and personal lending, for the purpose of this article, we will discuss personal lending only.

So, who could be future prime for personal lending?

The graph below shows the quintile distribution of India’s income by households. Most Fintech firms are focusing on Quintiles 4 and 3 and to find their distribution of Future Primes. As they go to the lower income quintiles, savings are lower, disposable income is obviously lower and hence credit risk becomes potentially higher. This population can be further characterized by digital readiness, age, education, location of stay (metros, Tier II, Tier III cities, villages etc), occupation – all of which could give indicators of creditworthiness. And Fintech firms are using a variety of ways to do just that.

Figure 5:

Data: Household Survey on India’s Citizen Environment & Consumer Economy (ICE 360° survey)

Crediting data for what it’s worth

How can we figure out creditworthiness of a person if they do not have a bank account? Or how can we figure out a person’s intention to pay even their credit score is currently weak? And which segments of the entire financially excluded market, actually lead to the possible “Future Primes?”

Akshay Mehrotra, CEO of Early Salary, a company that provides short term loan advances to people says, “Future prime for us are the young salaried people, who are not yet creditworthy, just because of age. We are a data science company that also does on-book lending on the strength of our python based machine learning model.” While it’s still early days for Early Salary, they are witnessing an approval rate of 65% and repayment rates of 99% currently.

Could Future Prime for personal loans be looked at in ways other than age? ZestPay, a company that focuses on lending to individuals for specific purchases shares their story, “For us, future prime are freelancers, doctors, etc. who work independently, earn money but may not get access to credit since they are not part of a larger organization.” Their machine learning lending model uses non-traditional variables like time taken to complete application form, frequency of calls to call center, purchase intent etc.

Taking the idea of lending for specific purchases further, companies like CashCard provide short term loans at the point of sale, when customers are about to make a purchase. Their future prime target market involves people who are buying for Education or for travel. And they look at mobile and social data to figure out past behaviour patterns that can be modelled.

There are other firms such as Propelld who are focusing on student loans for short term vocational courses by bringing in a flexible lending model based on loans on student’s academic performance and lending schedules matched to income. And RuPie that lends to the urban, salaried, poor using a mobile based verification system, reinventing microfinance and chit fund lending methods.

All of these may not scale up. Education loans could be risky, so could be micro-loans. To some extent, loans at the point of purchase have achieved some scale with the efforts of Bajaj Finserv.

A bankable future?

These are just early examples of the way alternative lending companies in India are trying to assess the future prime market, with focus on strong use cases and with constant insights from data. Given the need to deeply understand the customer segment they are providing loans to, the companies should be wary of extending their loan book too fast and stay away from chasing targets rather than understanding the customers.

Banks are still waiting and watching their progress, in some cases partnering with them. As the segment grows and as more such “future primes” get unlocked, it would be interesting to see if the real financial inclusion happens when the unbanked and the underbanked of India no longer struggle for access to their capital needs.

Is Alternative Lending here to disrupt traditional lending and credits scoring methods? My assessment is the jury is still out on this. The companies need to scale up while keeping a watch on their repayment rates and ensuring that their fraud rates stay low. Only then they could really be counted as a real alternative. The bad-loan stressed banking system is not in a position to see another huge credit addition. And the cost of failure for such companies is much higher than the failure of a company that might just sell goods for luxury or entertainment. These firms are not just in the business of giving loans, they are in the business of funding dreams. And dreams can sour quickly if not nurtured well.

If Alice met the cat in the post Alternative Lending world, hopefully, it would be easier for her to find her way out of the rabbit hole.