[Aditya is the founder at Creditexchange (Qbera.com). He shares interesting perspective on the evolving online lending space in the country.]
This article is an open response to Anand Lunia’s aforementioned article which raises some interesting points (and concerns) about the online lending space in India.
While I agree with the ultimate conclusions which are drawn, I believe there are models which don’t suffer from many of the limitations alluded to in his article, and are therefore more well-positioned to attract funding & scale & in the future. Excerpts from his article are in quotes, with my responses below:
Anand Lunia: There are about 20 odd funded online lending companies in India, and the market that was supposed be the big find of 2016 is now facing a reality check. Many of the funded companies are already pivoting and many others are seeing serious slowdown of momentum. Demonetization has hit many of them as overall borrowing has reduced since November, but that only hides many other underlying challenges.
Aditya: Credit Card inquiry volumes at the end of December, as per data from CIBIL, are higher than they were pre-demonetisation. Personal loan are still down, but insignificantly. Public Sector Banks have seen the greatest decline in inquiries, with NBFCs and Private Banks having recovered well. Given the scale online lending companies are operating at (or lack thereof), they can’t be systematically affected by demonetisation.
In the medium-to-long run, the overall impact on demonetisation for both business & personal lending will be hugely positive are a greater share of transactions are banked.
The companies that are in the online lending space can be categorized in about 4 categories: 1. Get you the best deal- the lead generators like BankBazaar and Deal4loans. 2. Gets you a loan even if you don’t have any credit score- usually from their own balance sheet using some proprietary score. 3. Get you a new product altogether: Like a quick 15 day payday loan which you won’t get from your bank even if you have a good credit. 4. Get you a loan from a peer- bypass the whole banking system, where everyone can become a lender. 5. Get you the best deal and also the best experience- new age marketplaces that do a bit of credit scoring, processing etc but don’t lend from their own balance sheet
Aditya: there is a sixth model – get you a loan even if you have a credit score (or don’t), but banks aren’t giving you a loan for one of many reasons:
- You work for an employer which isn’t “listed” in their database (approval rates are abysmal for applicants from uncategorised employers – even those with good credit scores).
- Your score isn’t >740 (CIBIL v1).
- You earn less than 6 lakhs per annum.
In this model, uniquely, credit decisions are made by the on a jointly agreed policy (proposed by the platform), but loans are funded on the banks’ balance sheets. The platform will usually have some sort of first-loss or second-loss position, but has a risk & revenue-share with the Bank or NBFC to compensate.
A few debates that were raging in the market seem to have settled down now. One was the fascination with marketplaces. Most investors now accept that in the short run, lending-from-own-balance-sheet model is the best model to serve under-served markets.
Aditya: As above, the best way is to use a (or multiple) bank’s balance sheet, with the flexibility of using the platform’s credit model. Eventually, borrowers’ approvals should be agnostic to the balance sheet from which they are being funded.
The borrower coming online expects easy and quick money but this is not solved in a marketplace today for everybody. Usually, lenders themselves thrive on information and access asymmetry, and have no major advantage in helping the marketplaces remove the same.
Aditya: I believe this is untrue. Many banks & NBFCs are willing to work with startups – in a credit context – to uncover new segments through (1) non-traditional data (this could be traditional data employed in a non-traditional manner), (2) the availability of technology to leverage pull this data in a seamless manner in real-time, and (3) the use of this data in alternative scorecards which are aimed at lending to underserved (or even unserved) segments.
There may emerge marketplaces later in time as the newer and more tech savvy players provide enough depth to the supplier side of the marketplaces.So we find practically all the marketplaces founded recently now getting a lending license to lend from their own books. There remains a genuine concern about the balance-sheet lending model that inherently uses money as a raw material and hence leads to very frequent fund raises. But as plenty of other spaces have demonstrated- the Indian market is better served in the full stack model, even though it may not be theoretically the most capital efficient model.
Aditya: It is insanely capital in-efficient to try to use one’s own capital – especially in the early days. The hybrid model is the way to go.
Not sure the full-stack logic applies either – this would involve internalising tasks such as contact point verification (CPV) which could also lead to inefficiency. Platforms should focus on: customer acquisition, credit scoring & underwriting, and providing a great customer experience – all of which can be enhanced (i.e. made cheaper / better / faster) using technology.
Another myth that is also getting dispelled is the lure of great credit scoring algorithms. AI, Machine learning, robo credit etc. are fancy words and very very attractive. But after reaching acceptable default levels, any incremental improvement in credit scoring is bound to give diminishing returns. And a team of 3 data scientists, with all due regards, has become a commodity. So everybody with a budget might have some credit scoring ability, and will be able to bring the credit defaults within reasonable limits as long as the underlying segment is fundamentally viable.
Aditya: While this may be true, the question is – who can prove their credit model (by passing, say, 10,000 loans through it) without employing oodles of capital to do so.
Also, the bigger expense today, by a wide margin, for all online lending players is not the cost of default, it is the cost of acquisition.
Aditya: True, but capital is probably one of the largest costs for platforms looking to use their own balance-sheet to lend (if, indeed, they are able to raise this).
That brings us to some real issues facing the space, aka why the companies are not growing at their expected pace.
1. Reaching the customer at a viable cost
2. Processing and collecting the loan cheap enough
3. If you are using your balance-sheet to lend, being able to leverage your equity capital
4. Maintaining profitability while growing at venture pace
No surprise that the challenges that the online lending cos face are pretty much similar to what the ecommerce cos faced early on- but they had the liberty of burning cash and learning as they grew. If you try to grow fast, you acquire customers at a very high cost. If you try to build too much tech in your processing, you have to leave out a large number of eligible customers or channel partners. If you have to borrow, you need to be profitable. But then if you don’t grow fast enough by burning some money, you won’t qualify as a venture deal for investors. So the teams need to be very nimble as they manage these pulls in different directions.
On the flip side, the reward of solving these challenges is very lucrative. The market is big and the unmet demand so large that in almost all spaces save the marketplaces there is room for 5–10 large new players. It is clear to startups and the incumbents that there no winner takes all here and this has ensured that nobody is indulging in discounting. The NBFC and microfinance spaces have delivered good returns for investors and there is enough PE interest in profitable tech enabled lenders, many of which may want to come in very early in these lenders and that increases the available pool of money.
Aditya: Agreed! I hope that our team at Qbera.com will, someday, join the leagues of the alternative, large players in the online lending space.
