UGRO Capital Limited (511742) Earnings Call Transcript & Summary

Ladies and gentlemen, good afternoon, and welcome. Emkay Global Financial Services takes great pleasure in hosting the Q1 FY '23 Results Conference call for UGRO Capital Limited. We have with us from the management, Mr. Shachindra Nath, who is Vice Chairman and Managing Director; Mr. Amit Mande, Chief Revenue Officer; Mr. Anuj Pandey, Chief Risk Officer; Mr. Amit Gupta, Chief Financial Officer; Mr. Nirav Shah, Chief Strategy Officer and Head of Investor Relations; Mr. Rishabh Garg, Chief Technology Officer; Mr. Subrata Das, Chief Innovation Officer. So without further any further delay, I would now like to hand over the floor to the management for their opening comments. Thank you, and over to you, sir.

Good evening, everyone. I'm Shachindra Nath. Thank you all for joining our Q1 results presentation. So in fact, this -- we have -- we started this in our last quarter as well. Our belief is that our light consumer credit business in India, the small business financing is also rapidly embracing the data-driven underwriting. Since the start of demonetization and advent of GST and creation of 3 layer of data -- [ 3-tier stack ] is ensuring that over the next 2 to 3 years, the entire SME credit space would move to a data-driven underwriting. The idea is to lay the payment layer and the retail layer combined with the power of multiple alternative sources of data would move the credit to 3 different forms of credit, which we call embedded credit flow, base credit and buy now pay later. And this is also massively supported by the now which is fully implemented the OCEN network. And once the ONDC would come, the merchant financing business would also become very, very prominent. This also, we said, we have been saying this over a period of last many quarters, that there is a transformation of NBFC lending space is happening. The NBFC lending space is getting divided between some very large capitalized owner-driven NBFCs and the larger ecosystem, which has to converge to lending as a service. We have seen the last companies across Europe, U.K. and U.S., but India is now seeing the evolution of lending as a service. What basically it means? It means that unlike conventionally -- all of you have seen that lending outside the bank through NBFC is a business of leverage versus now it is making business of service. On one side of the spectrum, where we specialize is being able to find or what we call source, filter, underwrite the customer. On the other side of the spectrum, we have the owners of the liability of liquidity, which is banks and large financial institutions. The way we design ourselves that while we are a principal lender, we have a highly capitalized balance sheet, and we borrow on our balance sheet. But our eventual goal is being able to service the large ecosystem of small businesses in India, being able to filter them, use our data-driven underwriting and clear them through our score. And finally, the balance sheet belongs to the large banks. And that creates a very large fee-generating model for businesses like NBFCs or fintech, whatever you may want to call it. Over the next few slides, we'll explain that how we are evolving from a leveraged business to [ layers ] as a business. But over this Q1, we have been able to prove that this is happening. We have been able to cumulatively disburse INR 6,000 plus crores over a period of last 4 years, of which roughly around 2 years were lost. We have an asset under management of INR 3,650 crores, which is a growth of almost INR 700-plus crores over a period of 1 quarter. And we have an off-book AUM, which is INR 780-odd crores. So from a 16% of our balance sheet, which was off our books, now we have moved to 21%. We are now servicing 25,000-plus customers. We have a physical footprint of 95-plus location. Beside our, roughly around 1,300 to 1,400 people, we have around 1,000-plus partners who services our customer base. And for our supply chain business, we have a very strong base of 75-plus OEMs and anchors in our ecosystem version. And last but not least, I think, to UGRO has over a period of last 5, 6 quarters have become a company which services the need of an SME or MSME customer right from a small INR 1 lakh loan to INR 5 crore of credit in different format of what we call the product through multiple distribution. So we have ability to do a secured business flow on machinery, unsecured business loan and micro enterprises loan, supply chain financing and merchant financing, which is a digital platform which we will be coming soon. I hand it over to Anuj to talk to you about how the data ecosystem in UGRO has evolved, and what data would be doing to the MSME financing ecosystem in India. Anuj?

Sure. Thank you, Shachin. So I mean, for the next couple of slides, I will just take you all through how the digital ecosystem has evolved and how we seem to be in the right place at the right time with the right set of design and execution capabilities to have a meaningful impact on the very large lending opportunity, which is present across SME lending in India. And first things first, a very quick review on how we have evolved in the last 3, 4 years. How we have been able to apply data analytics and technology, not only in the very core area of underwriting, which I will explain in detail in later slides, but also in other aspects of our institution. In fact, we have been readily using comprehensively data -- our data-led insights in early warning systems. We have applied the same approach in our operations and collections team or at the origination level right from day one we have been using it to a very large extent. In fact, to open our new branches in micro locations, we have used data science extensively. So overall, not only in underwriting, we have seen and found a lot of advantages in using technology and data platforms across. So we would probably be one of the first large-scale NBFCs to do that. Nirav, if you can move on. And at the very heart of what we have done is what we call a Gro Score. When we had started in January 2019 with our first loan, we had -- we were using the first version of our Gro Score, which was based on a simple hypothesis and design that when you look at the customer via the lens of the sector in which it operates, one is able to understand his cash flow in a much better way. And hence, one is able to predict the portfolio performance much better. And this got severely tested. And we passed that test successfully during both pandemic 1 and pandemic 2. Our portfolio has remained intact and in much better shape vis-a-vis competition, but -- and also during that impact, we learned that the banking behavior also is a very key contributor in predicting future portfolio performance for SMEs. So we launched our Gro Score 2.0 version, which made use of not only the repayment behavior analyzed through the lens of ecosystem, but also the banking behavior. And it became a very, very powerful tool. We implemented that in July of 2021. And as of March 2022, data is now sufficiently analyzed. And we can see that directionally we have found a way to template and standardize and scale an underwriting methodology for all across SMEs in India. Our ambition now is to include the GST data as well. And internally, we call this Gro Score 3.0. The target is to launch it by third quarter -- end of third quarter in this year. And once we do that, then it becomes a real tripod and one of the most powerful tools in underwriting to SMEs. We have already -- and this has been done by our own portfolio-generated data has been very, very thoroughly tested. Statistically, we have analyzed more than 45,000 bank statements, more than 21,000 applications have been processed post our Gro Score 2.2 application. So from -- as far as statistical rigor is concerned, we have left no stone unturned. And we really want our Gro Score to become the benchmark as far as underwriting to SMEs is concerned. Just a little more on how the Gro Score works and it works -- the basis of that of how what we are able to do is actually a very, very extensive library of about 25,000-plus data features, which we have been collecting methodologically since day 1 of launch. So for all customers, whether we approve them or we reject them, we collect last 12 months of banking data in a machine learning format and last 24 months of GST returns. And from that, the machine learning tool keeps extracting data features, which can eventually be used to correlate with portfolio performance. And now a third layer of GST is planned to being added there. This we had referred to in our last call as well, but this is a very, very important slide because it is telling us that directionally it is possible to completely templatize the way SMEs are underwritten. Very simply, our new Gro Score 2.0, which is live since July of 2021, classifies all customers, which we underwrite in 5 risk bands. And depending on that respect, there is a probability of default, which is assigned. And now we are already seeing data for customers who are now more than 6 months and up to 12 months, where the risk stacking, where a Gro Score A customer, which is the least risky versus a Gro Score E customer, which is the most risky -- their performance, both on our books and both off books where we have been tracking their performance with other financiers is stacking up the way it should be. In the longer run, we would bond it -- we would want to reach a situation where physical underwriting inference and input becomes as low as possible. The underwriters role would be to do a quality reference check and apply his mind to improve the scorecard and the machine taking over. And in that direction, this is a very, very important step. Nirav, you can move on. And all this was made possible, if you recall, people who have been listening to our story, because we are focused on our customers via the lens of the sectors in which they operate. So when we started -- and the endeavor was to look at sectors which are large, where the macro and microeconomic parameters were favorable in short to medium term. And also there was enough data available to make use of. So we had done a very large exercise with CRISIL, and we had chosen 8 sectors in which our target segments where smaller SMEs where we can give loans up to INR 5 crores. And these 8 sectors were health care, hospitality, light engineering, auto components, education, electrical equipment, chemicals and food processing. We also, during our journey about 1.5 years back, introduced a new sector, which we call micro enterprises because we realized, and industry data was telling us, that this differentiation basis sector was not really applicable if the size of the enterprise is very small. The size itself was a differentiator. So we included a new sector called Micro Enterprises, where the focus was to focus on very, very small businesses with loans up to INR 25 lakhs. So today, we are focused on these 9 sectors, 8 of our original, plus ninth, which came about last year. Now I'll ask Amit to take over, and he can take you through how we are designed in terms of technology, our product structure and the financial numbers. Over to you, Amit.

Very thank you, Anuj. And like you rightly said, this is to all. Our Gro Score, our proprietary Gro Score, we call it the magic sauce, sometimes we call it the Arco formula, remains at the heart of everything that we do. So around this Gro Score is what we've really built the -- a very robust tech platform. There was a need for a strong and -- strong platform. There was a need for differentiated platforms to harness the power [Audio Gap]

Anuj, would you like to take this?

I will take it up in the meanwhile he'll join back.

No. Can you hear me, Anuj? Can you hear me?

Yes. Now we can hear you.

There were some disconnection. So anyway -- so I was saying this remains at the heart of our robust technology platform. It was -- there was a need to have customized differentiated platforms to harness every ecosystem. And what this slide really shows is our different platforms. Our GRO-Plus platforms looks at intermediary distribution in the prime branches. Our GRO Direct is where we go direct to the customer. GRO chain is a very, very interesting, very high-end platform that allows us to harness the ecosystems of the anchors and the suppliers on our supply chain business. And the most important, and Shachin did -- Mr. Nath did touch upon this as our route to becoming a lending-as-a-service entity, an extremely important platform. Our GRO-Xstream actually connects the fintechs and the NBFCs on 1 side, the public sector banks on the other side, making us a truly loan against -- making us a truly lending-as-a-service platform. All these really revolve around this 1 thing that we are very proud of, which we have done a proof of concept and as to the test of time is our Gro Score 2.0. With this, Nirav, can you move on? With this, we really -- what are we doing is, we are servicing every credit need of every MSME. So we've designed products starting from INR 50,000 to INR 5 crores, products that have tenors from 30 days to around 15 years and all kinds of needs being serviced. What really this Gro Score does is, Gro Score really credit evaluates customer. And then if he is worth delivering credit to, depending upon what kind of product he wants is the customer price -- the customer is priced depending upon what kind of security he brings on the table. And so we are able to do multiple products like loan against property. We do our productive asset financing, unsecured loans, supply chain and our micro enterprise loans, all of these revolve around this 1 simple concept of Gro Score and supported by our platform. More importantly, on the distribution side, we are now at about 96 locations.

Amit, we can't hear you.

Can you hear me now?

Yes. Yes.

Okay. So I was talking that our distribution strength continues to improve quarter-on-quarter. We have about 96 -- we are now in 96 locations, more than 1,000 GRO partners. Our ecosystem of anchors and OEMs who power our supply chain and the productive asset financing machinery finance business, again, has been growing quarter-on-quarter. And of course, our employee strength at the front end now has more than 700 people that bring in -- that work on all these platforms. If we were to look at how we -- how our distribution is -- Nirav, can you go to the next slide? Yes. How our distribution is? We have a very -- we've realized that there are multiple customer cohorts that we want to reach to. And we have very different distribution models, a branchlet channel looks at the prime branches and the micro branches. They service the intermediary distribution. They take to the customers, a loan against property, our affordable lab, our unsecured loans business. Our ecosystem business -- distribution model actually harnesses ecosystems of the anchors for the supply chain, both on the vendor and the distribution side. It harnesses the ecosystem of the OEMs for the machinery finance business. There's a large -- like I said, on the growth -- GRO-Xstream platform on one side, there are large number of partnership and alliances, NBFCs and fintechs where we do very, very differentiated products with them to reach to the last mile, and most importantly, our digital direct-to-customer digital channel that is -- that will now get enhanced in -- by end of August to really step up our customer acquisition engine, and this will be one of its kind direct-to-customer channel that we will launch in August. We will, of course, see the launch that will be a visible launch, and we will be able to divest a lot of more information possibly in the next quarter. But as we continue to build our distribution as we continue to build our asset book, 1 important thing, Nirav, I wanted to talk about the lending as a Service platform. So if you could go to the next slide. As we continue to build this our partnerships with the PSU banks and the NBFCs for core lending and SFCs continue to increase. In last quarter, we had about 5%. We're now increasing this. We've got Punjab & Sind Bank on board. We've signed with Punjab & Sind Bank for all products. By next quarter, we will have another 2 banks having signed up. So that takes care not only of just our liability position, but our ability to off-book our AUM. Look at how beautifully the off booking of AUM continues to grow quarter-on-quarter. So last quarter, we were at about 16%. This quarter, we are at 21% of our AUM -- off book. And this is thanks to all our partnerships with the PSU Bank and some large leading NBFCs, where we do co-lending and co-origination. Nirav, can you go to the next slide?

Amit, I turn out the next slide.

Okay. I don't know if the slide has changed, Anuj, for you.

Yes. It has changed.

Okay. So I'll continue. So we kept saying that we wanted to do lending as a service. We wanted to build a large -- when we spoke last time after our annual results, we said that we wanted to build a INR 7,000 crore AUM by end of the year. And this is really where we are saying that we are absolutely on track to deliver. After the end of great first quarter, our AUM stands at about INR 3,656 crores. Off-book AUM is at 21%. Our net total income remains healthy at 10.5%. Importantly, our credit cost is very much under control, and so it's at about 1.4%. So overall, I think the real message here is that, we have started this year to get to a INR 7,000 crore AUM or 35% off book out of that and a 2% ROA -- more than 2% ROA. And I think we are completely on track to get to those numbers. First quarter has been a testimonial of that. So with that, thank you, and I open this for discussion.

[ Nath ], I think we will take some questions one by one.

Sir, anonymous attendee question. What percentage of sourcing is done through the BSA channel?

So at this point of time, 55% of our business comes from the prime branches and -- in which there is also machinery finance business. So amongst our book, about 48% to 50% of our book will be generated by the intermediaries. The rest 50% is through direct and through other partnerships.

Do we have any other questions in the chat?

Can people ask questions or they have to only do it through chat?

Okay. We have had some message sent by [ Gaurav ]. Nirav, if you could please unmute his line?

Nice to see you all, and congratulations on the numbers this quarter. I have about 3 questions in the business. So let's get started. The first question is on our Gro Score. And we spent a lot of time explaining this, but I have a few more basic questions with the Gro Score itself. So we have 25,000 data points as you've said, right? But the more data points we add to a model, the more complex the relationship becomes between the data and the more noise and contradictions you'll have between different data points. So what framework do we use to choose which data amongst that huge set to prioritize? And could you tell me if we're using like a bayesian framework or a stochastic framework? How are we using our probability models? And more basically, if we take a case study, right, like if we discuss nursing homes, for example, can you tell me how our understanding of this single business has changed from GRO 1 to GRO 3 where we are now?

Subrata, do you want to take this?

You're on mute, Subrata.

Yes, I can take the question. The first part of the question, which says, there are 25,000 actives and the method used. So first of all, these are -- first of all, it's a feature library. It is the total universe of parameters, which could be potentially used to predict the probability of default. And you're right in saying that not all of them could be used without a loss of significance. We use -- the approach that we take is we make as many parameters as possible based on our functional and business expertise. And that maximizes our chances of getting a very powerful model, which holds the test of back testing. Having said that, there is a scientific and elaborate method of reducing those dimensions into eventually a set of around 35% to 40%. The approach that we use, you mentioned, bayesian and stochastic processes, what we use is basically supervised learning technique because we are predicting 0 or 1 outcome, or a good or bad outcome, on a trading data set. And we follow a very well-defined objective framework to gradually reduce the 25,000 to the set of 35% or 40%. Most important significant parameters, which have eased correlation with each other. However, in conjunction or most powerful in predicting the default. The exact formula or the system of waste, which is used to arrive at the probability of default, that is a part which we keep as proprietary to ourselves.

Okay. That makes sense. Could you just tell me a little bit about the -- how our understanding has changed from GRO 1 to GRO 3?

So when we did GRO 1, we have very little data of our own and we were working in conjunction with the large credit bureau and developing models on something that we call look-alike population, one that best resembles our target segment. However, they will not do our data sets. From there, we moved on to 2.0, which is currently in book since July 1, which has 2 major components, one that's being developed on our own incoming data and with all in-house models, it predicts much more sharply. Second, it combines the credit bureau history of the borrowers, both the commercial NTP as well as the individual applicants as well as the bank statement into 1 consolidated scoring model. And 3.0 is more to incorporate the GST records of the entity. And thereby, it is going to be first of its kind of a very robust predictive model, which captures the intensity of business in real times GST. The financial discipline of the intent to pay through the bureau record and the ability to pay through, let's say, the current cash situation and the credits and debits visible in the bank statement. That's how we [indiscernible].

All right. Yes. Two follow-ups there. So one, the recent push from the RBI to onboard the PSU banks to the account aggregators. Do you think that's a significant data point for us to improve our model?

Yes.

Definitely. Yes it is. I think it just depends on how much of participation we see in what span of time. But in a destination state where account segregated has the participation of the entire banking sector, and that it can really definitely change things.

Okay. The second question is...

I can just add on that. So currently, the problem is of friction. So today, banking, which is one of the most important component to us is the cash flow of a customer. So what we say ability to pay come from a physical bank statement, and the conversion and the friction from physical to a data and being able to analyze that requires multiple level of curing and intervention. But when the same data set would come from account aggregation, it become very efficient. And second, one of the big constraint for a nonbank lender is that our ability to refresh this data on a periodic basis. So account aggregation, not just for the bank, but also GST being part of that, would allow us to fetch the same data on a periodic basis and update our model and look at the -- not the -- at the point of lending, what is the risk associated, but it improves our AWS model, only 1 in [indiscernible] model. Anuj, if you want to add something to that?

Yes. You're right. So basically, on the -- so today, whenever they are getting data, it is at the time of acquisition. And there is no way that we can -- we get data for monitoring purposes. Once account aggregation is fully live and all the banks are participating and a lifetime consent framework is also established, then not only at the time of acquisition, but during the life cycle of the loan as well, we would be continuously monitoring this data -- cash flow data, and that would be much more robust.

I can imagine. So it's a real-time data, which allows you to understand very quickly how sensitivity models are to change. Okay. Last question on the proof-of-concept here. The proof-of-concept that we've uploaded so far is for GRO 2.0. Will we have anything out for the newer models? Do you expect it to be better?

The newer model is expected to go live only in December 2022. So we are still about -- it's right now in the development phase. So once we implement that, post that, we will require some time for that -- for some data to get set and established and post that, we will do that. But there is a frame work already of whenever we launch a new model, what kind of testing we want to do in terms of back testing. And once it goes live, then at what rate we should do proof of concept.

Just to add that, the difference between 2.0 and 3.0. The 2.0 predict the default, categorize the customer in 5 bank; 3.0 would be able to predict the default as it is being done in 2.0, but also would be able to predict the ability of the customer, whether -- if the customer can afford INR 100,000 worth of loan or INR 250,000 worth of loan, which is today is estimated through a policy and product program on the front-end. So that's the core difference.

Okay. So your approval rates falls positive, all of that will improve, your early warning systems with real-time data, all of that will improve, [ brilliant way ]. I have one last question from my side, which is, if I look at our sector mix now this quarter, and I compare it to Q1 FY '22, I can see that education and hospitality, which comprised about 15% of our book, is now down to below 5%, for example. I know this is because of restructuring. But my question is, what is our plan for education and hospitality going forward? Are we going to be looking at a different sector? Do you see it returning to giving us the scale that we chose it in the past?

So we are already seeing a lot of encouraging signs in both these sectors, both in terms of our own portfolio, which is a good portfolio, which has been restructured and a lot of demand also seems to now kicking up, especially in education with children coming -- going back to school. So slowly, the plan is to keep building this up.

We have the next question from the line of Anadi from Vivriti.

Anadi, please go ahead. Anadi, just unmute yourself, and please go ahead with your question.

No questions. It was my mistake.

The next question we have from the line of [ Sameer Shah ].

So I just wanted to understand how this OCEN network that is used by the company? And how is it integrated with the Gro ecosystem that you're at?

Okay. I'll answer that. So OCEN, this open credit enablement network, the broad concept of this network is to have data in a marketplace, which is driven -- data storage, which is driven by book per call, which is standardized across. The first used case of OCEN in India is a platform called GeM Sahay were we are the first lender. So the way it works is the GeM government e-marketplace is a marketplace. Sahay is the OCEN network over and above that, where on 1 side, the sellers are SMEs and the buyers are PSUs and the data of their transaction is stored in that marketplace in a format which is universal. That data we have integrated with the GeM Sahay platform. In fact, not only us now, we were the first ones, but there are many more financiers which are doing that. It accesses the movement and SME takes -- gets an order on GeM, then their previous history of that transaction and the SMEs demographic is available for a financier to make use of firm business rules around that data and do an instant approval for that case. So we are already live with that -- in that. More and more OCEN framework-based platforms will keep coming up once more and more people start adopting that. And as far as we are concerned, our business will engines and the API network is ready whenever it need arises to further integrate.

Okay. Okay. Understood. The other question is regarding the expansion model. So would it be more branch-based going forward? Or would the focus be more towards digital penetration? Like any numbers on this?

So in our earlier plan, we did have a large expansion plan this year on the micro piece. Now the micro branches we do micro secured, which is a high yield secured product and is a focused product for us. But today, with 75 branches over the next 2 quarters, we want to make it highly profitable and then focus on further expansion of micro branches. Any expansion further from here will only be on micro branches. On the prime branches where we do the intermediated business, we don't see any large expansion plans. That's number one. Number two, the expansion will be in products of machinery finance, supply chain and direct to customer, which essentially means that to some question that -- to your question that somebody earlier asked, what is our direct distribution, what is our intermediated distribution. Our focus is to keep improving our direct distribution going forward with micro branches and with the businesses where there is direct to ecosystem, and there are no intermediaries. So did I answer your question in terms of what are the plans on distribution and expansion?

So it will be selective in terms of which areas require intermediation, like a personal contact with the customer. So like as you said, in the micro area.

The answer is that, we will continue to expand our micro branches, where there's a direct-to-customer digitally assisted footprint and a direct-to-customer digital acquisition.

All right. All right. And my last question. So just a lot of people would still not know how to go about a loan approval -- loan application process. So is there anything you are doing for improving awareness about how to go about this online loan application procedure?

So 2 things. One, the moment I said that we are going micro branches direct distribution, we have feet on street. So it is a customer assisted model, and so we will assist the customers to run through their customer journeys. On the direct to customers, we will start with very simple small tickets, small tenure of products where the data requirement is very low and eventually take this up to a more complex product where we need -- we need their involvement -- where we need data on their GSTs, where we need data on their securities, their properties or whether it's machinery. So initially, direct-to-consumer will always be a little simple journey, simple data requirements and over a period of time, we'll graduate with the customers to higher-end products.

Okay. And one last question. Could you possibly give me a split between off-book and on-book disbursements for last 2 or 3 years?

Yes. Even if you look at our few of our slides, you can see that as of March '22, 16% of our book was off-book. As of Q1 end, it is 21%. As of -- we are targeting as of FY '23 to be 35%.

So I was talking about the disbursement. That I think is the AUM, correct?

Right. So the disbursements month-on-month will be in the range of between 35% to 40% off-book.

We have the next question from the line of Manish Agarwal.

Am I audible?

Yes.

Congratulations on good set of number, sir. Just a couple of questions I have. Like this time, in presentation, there is no mention about provision coverage ratio or NIMs. So could you help me with that number? What are the NIMs in this quarter?

Yes. So Nirav can take this. But just broadly, I think so some of the conventional metrics which are applied to NBFC, gradually, we are saying, is not relevant to us. Because the net interest margin, which is a function of our blended portfolio yield minus cost of borrowing is actually not relevant for us and not a right barometer to judge us, because we may have a higher cost of borrowing vis-a-vis some of the large related NBFC. But our liability comes from co-lending or off balance sheet because that will be at much lower rate. So our gross income component is our interest income plus the fee income, which comes from our balance sheet, minus our cost of capital. And that's why -- broadly it has not been given, but just to get your sense, our portfolio rate is around 16.5%, cost of borrowing is 10.5%. Nirav, if I'm correct, unless you can clarify.

No. I think that's right. Absolutely.

In fact, that is represented by the net total income that is being given in the -- Shachin, what you said is really represented in the results as well, which is 10.5% for the quarter.

Yes.

That is net total income. Is it the NIM as well, 10.5%?

So Manish, this includes the income from co-lending. So the lending -- the net total income has been calculated as total income minus the interest expense, right? So that's how it is.

And sir, what is the provision coverage ratio? What could -- around?

On the total book, total provisions are about 1.7%. On Stage 3, the provision coverage is around 28%.

28%?

Yes.

Okay. And sir, just one thing I just need to clarify. I heard somewhere that the company is making some kind of fund for the employees where they would be buying the shares from the market. Is it the right information or just -- like news?

Yes. Correct information. So I guess if you look at our exchange disclosure and our results present -- Board meeting. Our Board has approved a fresh ESOP scheme. The ESOP scheme is only for purchase of shares through secondary market. As you know, as per SEBI regulation, we can do that up to 5%. In a particular year, we can do up to 2% of the total market capitalization. So our Board has approved a loan to an employee welfare trust, which is the quantum is roughly around INR 30-odd crores, and this money would be utilized to buy shares from the market, which would be held in this trust for the employees pool. And employees can vest these shares, I think, so in the year '25, if I'm not correct -- if I'm not wrong. So as and when there is a market opportunity, this employee welfare trust independently would buy from the market and hold it. And then it is like an ESOP scheme. These shares would be held in the trust for the benefit of employees.

Okay. So this -- the money would come from the loan given to the employee, exactly?

Loan given to a trust. So SEBI regulation or ESOP allows this that either the ESOP, which is steadily -- directly given by the company or you can implement the ESOP through a trust. So there is a loan which would be given to the trust and that loan money can be utilized to buy share from the secondary market. And the shares would vest in 2025, employees would pay the cost of acquisition to the trust, and trust would then return that money to the company. Our trust can -- and employees can ask the trust to sell the shares and pay the difference to the employee and the principal amount would come back to the company.

We have the next question from the line of [indiscernible].

Congratulations on a good set of numbers, especially in AUM and fee income. I had 4 questions which have accumulated as the contributions went. I'll just start with the most recent conversation we had. So on ESOPs, will this transaction count towards the 8% gap in the article of association?

So we have, sir, 5.88%, which is the ESOP. And I think, so you're right, this will be roughly around 8% in total. I guess we are going for a shareholder approval. So absolute quantum is INR 30 crores. And if this quantum -- because we don't know what real percentage of shareholding we would be able to acquire because it's a function of price. And in a particular year, you cannot do more than 2%. But if it process as cash percentage of 8%, so when we are going for shareholder approval, whatever is the calculation we will request for shareholders for that change.

That's great. Okay. Then the second question was on the competitive landscape in co-lending. So if in co-lending, we say that we are the leading partner for banks, especially PSU banks who have issues with front book growth and front book quality, who's our next competitor? And how far ahead are we in terms of using the data tripod, et cetera?

So sir, it's very difficult to talk about who our next competitor. We can only talk about ourselves. So in terms of this co-lending as a business model, let me give you some perspective. So there are -- if you look at from a large public sector bank's perspective, I think of an SBI or Bank of Baroda [indiscernible], most of them would like to partner within NBFC of subset. NBFC of subset means that they would look at some significant amount of capital. They would look at a profitable track record. They would look at a healthy portfolio quality and some vintage, and then we'd like to partner because this is what banks want. Now if you look at in terms of the market participant, you have 3 types of -- and last but not least, [ OCEN ] for the IT sector. So the asset class, which can go ONDC is either SME, agri or underground markets and nothing beyond that. So fortunately, then you look at the market participant. So there are 3 types of participants. You have AAA to AA diversified large NBFCs. I think for them because not necessarily that most of them are in priority sectors, so there are a lot of assets these large NBFCs do, which is beyond priority sector. And also for them, it is much easier to do -- take a leverage on the balance sheet and continue doing the business as they want because their balance sheet would have a combination of wholesale corporate credit, means business, SMEs, home loans and so on and so forth. And that's why most of those top 10 large NBFCs are today not entering into co-lending, and most of their asset classes are not hitting through the bank. Then we have around 50-plus NBFCs, which are while our segment, but are either well capitalized on the portfolio to [ track record ], wherein they can get accepted by the bank. Let me clarify. Anything between BBB- to a BBB+ companies. And that's why that segment of the market is also getting expensed [Technical Difficulty] degrow with INR 1,000 crores of capital with AA rating and 5-year of vintage with a very mass portfolio quality and focus on digitization are becoming a preferred player for multiple banks to do co-lending with us. I'm not saying that we would only be the one who would be doing it. Over a period of time, there will be a convergence which would happen. The large NBFC would also start doing co-lending and smaller NBFC would become a little larger and co-lending. But we think so that we have a window of -- between market leader in this -- in next 3 years by the time this catch-up happens.

Okay. And in terms of our micro branches, are they like a strong contributor in this co-lending portfolio? And how do we avoid cannibalizing with our partner, PSU banks?

I don't understand the question. Can you repeat your question?

So basically, our micro branches, they don't compete with the likes of Bank of Baroda, Punjab & Sind Bank, right? We've made sure that they don't compete with them.

Sir, our segment of the market don't compete with the banks. Across every segment of the market, I think it is proven by time that the segment of the market, which have integrated NBFC service, while banks have much bigger, larger, massive presence, we cater to do different needs, right? Even if in the same location, a bank branch would be there, their method of underwriting, onboarding a customer and assessing a customer is completely different. If you look at a longer-term time horizon, 10 to 15 years, banks would learn through these NBFC and co-lending partners and adopt our method of underwriting process and technology. But they have many other priorities also, right? So that's why the adoption of this on their own will be slower. So I don't think that there is any cannibalization.

Are these micro branches -- like we are focusing on micro branches in our next phase of growth, like to a limited extent. My question was, are these micro branches a strong contributor in our co-lending portfolio in our GRO?

Yes, micro branches would be a bigger contributor in terms of the overall portfolio yield and profitability. In terms the AUM growth, there may not be a very large contributor as of now, but they are increasing. All of our banking partners are accepting our micro enterprises credit policy as a product for co-lending. And gradually, as the funnel would increase, that could also start going into the co-origination lending. Amit, you want to add something to that?

No. Absolutely. And to answer the question, the micro secured product that we have is a great high-yield product, is behaving extremely well. And so at this point of time, it also makes sense to keep some high-yield secured business on our books. And so it will continue to be on books for a while. At the same point of time, like Mr. Nath said, we have already started doing micro secured co-lending in a couple of banks, and it will continue to slowly move into the co-lending standard.

A follow-up on that. Are we applying stringent collateral checks on this micro secured business?

Absolutely. So there's a clear policy on what we accept as a collateral, and these are very much in line with what are acceptable by the banks. And so that is the essential recent check why even this product is today acceptable in a large PSU bank because [indiscernible]

Great. Yes. I got my answer. SBI and Bank of Baroda are comfortable taking it. So it needs to be one of the 10 -- list of 10 items. Great. Last question was on the QIP or the -- our leverage ratio basically. So right now, we are at a debt to equity of 2.3%. Obviously, with co-lending, it's not going to rise fast. But as and when we reach 3% to 4%, we would need to raise funds to expand. Considering that the stock price is a function of people -- volume as well, we may need to do a QIP near book value. Is this something we've considered? And have you considered options -- I don't need to know the options, but have you considered our options 6 months, 9 months down the line?

Absolutely. So I was right to put on to [ Shah ]. I don't know the same question is speaking or not. I was citing answer to him. But -- so first and foremost, regulatory, we are allowed to do up to 6x of leverage. But as a company in our initial first 5, 7 years, we have said that we would lever our say, only up to 3.5 to 3.8x. But that should also a tool available to us. Coming to -- we have other 2, which is co-lending. We have targeted 35% of our balance sheet to go in co-lending while depending upon market condition we can push federal and increase that 35% to 45%, and our leverage would remain the same what we are targeting. Third, I think so that our peer set, currently the public market is very muted when it comes to the lending. No [indiscernible]. The public market is muted because majority of the public market investors are worried about COVID and its impact on the balance sheets of banks and NBFCs, and what is the adjusted book value, and that's why we are not being able to ascribe the price. And that is muting the interest in the lending as a segment of the market. Now we are completely out of that. We have no correlation because pre-pandemic, post-pandemic, we have demonstrated portfolio quality, but once you are in a mix, you are at a mix and you can't go beyond that. But our view is that, as we continue to improve and show our growth, there are intelligent set of investors who would come dedicated for us, and that should improve our both price and also liquidity. Having said that, our source of capital is not necessarily only public market. Our source of capital is multiple -- in a listed company we raised roughly around INR 950 crores of capital, not going to the public market but from 4 large private equity investors. So source of capital today is available from private equity, DFI, big family offices and multiple others, who will compare -- or who are comparing us to the private market transaction. There are multiple NBFCs or fintech who are raising equity capital, anything from 3x price to book value to 7 or 8x price to book value. And while you get benchmark to your listed price. But I think that's the fair value where we should be. And hopefully, some of the private investors would look at from that eye and angle.

Okay. Sounds good. So I think it's fair to say that my calculation that, 6 to 9 months is that -- can probably be considered that they were too short. The assumption was too short. So we can still sustain quite a few more months or a few more quarters.

We can sustain the full year, and beyond that.

We have the next question from Mr. [ Adith Prakash ].

Yes. Actually, just a thing I wanted to understand. So we have mentioned that, we were at -- INR 7,500 crores is our plan by FY '23 AUM.

INR 7,000 crore.

Fee book from FY '20, the AUM was approximately [ 800 to 900. ] So we are growing our book to 9x in a matter of 3 years. And then there is a GRO Scorecard 1, there is a GRO Scorecard 2, and GRO Scorecard 3.0 is coming up. So how we are very much confident this is also backed by the GNPA numbers. If you see, I think, 2.13%, I think, was a GNPA this time. So if we back tested at FY '20, your GNPA number would be very high. So how we are checking those things?

So I would say 3 things. I think so you're only looking the headline number, but you are not looking the incremental OpEx, which is being incurred to build the base. So we raised our capital in July 2018. ILFS happened in September 2018. We started our business in April '19. Even between the July 2018 to April '19, a base infrastructure for the company was created. But given the liability market was extremely soft, [ most silent ], we decided only to deploy our capital. So out of INR 958 crores of capital we deployed INR 850-odd crores without leveraging our balance sheet. And immediately after that, the pandemic first round hit very hard, and we shut down our business in the first 6 months. But we were confident that we have to increase our infrastructure. So as of FY '20, we were a company of 170 people. As of FY '22, we were a company of 1,111 people. As of FY '20, we are a company of 8 physical locations. As of FY '22, we are a company of 91 physical location. As of FY '20, our technology team infrastructure was consisted of 5 people. As of FY '22, it was 90 people. As of '20 to '22 of our data analytics team were roughly around -- grown 5x. The growth is coming because this company has taken very early big OpEx to build physical and digital infrastructure, and basis that the growth is now coming. So it's a base effect. Number two, in terms of the portfolio quality, I think so the -- you can't back test it basis lower AUM. Because our low -- first year AUM, obviously, suffered from pandemic, but we have demonstrated that during the pandemic, we could control the portfolio quality much better than our peer set. And only business then has to look at gross NPA on the basis of an expanding portfolio and by cohort portfolio quality. And what is the early indicator? So we are showing you an early indicator of how our portfolio quality basis data analytics is building up, and what we think this would be the portfolio quality at future. Anuj, do you want to add something, please go ahead.

So I just want to add for a business model like us, where now 21% of the book is actually off in form of co-lending or co-agitation. And eventually at the end of this year, around 35% and in 2025, 50%. A good perspective, one can get, if one looks at the GNPA by total AUM. In this quarter, actually, our GNPA is 1.7%. If we add a net NPA at 1.2%, if you look at a total AUM, which is much more reflective of how the portfolio is doing. And in relation to what Shachin you said, in a growing portfolio, especially the first year, the denominator being lower, and then facing 2 pandemics. Post that whatever has come out, we are quite confident that directionally, we are stacking up well.

Okay. Just 1 more thing, I wanted to understand on your GRO Scorecard. So basically, there was a presentation where you were mentioning there was A-band, B-band and C-band. And then there were disbursed loan and there was undisbursed loan. So if a loan is getting A-band in your scorecard, then why you are not disbursing the same? And basically, how this scorecard is coming up there?

So the scorecard is primarily to predict probability of default, which is based on the financials and repayment behavior of the customer. But many times, a customer with good financial track record may not have a good collateral. And we have to say no in terms of LTV. He has come for a INR 1 crore loan against property, but his property value is INR 80 lakhs. So many times we have to decline that case. And there could be other reference check reasons as well. Ideally, yes, we should not. But the practical way -- the way it works is that there can be reasons over and above that. Directionally, what we want to establish is that Gro Score stacking works. And eventually, once enough data is there, then we are able to increase our throughput much more in desirable segments were basically Gro Score A&P.

Okay. One more thing. Out of this restructuring portfolio, which you have gone through. So can we just have a figure, what is outstanding as on date -- as on June end? And out of which how this -- how much is in the 0-plus, and 30-plus, 90-plus?

So our total restructured portfolio at the end of June is INR 120 crores, which is approximately 3.3% of the AUM. In that, the -- and out of this, 20% has become MP. The rest of -- 67% is current. And 4% is in 30 to 90.

You can also give color of the restructured portfolio by segment of the market [Technical Difficulty] to do that.

Yes, we can do that. So overall, if you look at the total restructured portfolio by product, then approximately 60% of that portfolio is undersecured, about 25% under unsecured and rest in supply chain. And by sector, about 85% of the portfolio is under education, hospitality or light injury. What we have seen in terms of repayment behavior, we are seeing that education and light engineering is pretty back to normal at pre-pandemic levels. In hospitality, though overall segment is now looking up, but the stressed customers continues to -- continue to be stressed. And we had done an internal analysis in last quarter were we had predicted of how much more NPA can come in from the -- especially from the unsecured hospitality sector from our current restructured portfolio. And we have planned for approximately INR 78 crores more NPA coming from there.

And our current provision is more than sufficient to cover it.

Yes.

Okay. Just 1 more thing I wanted to understand. We are going with such a high growth plan and we are on the track on it. So there will be a capital adequacy ratio that you need to be maintaining. So what are the strategy where we want to fix it on the capital adequacy ratio where we will be maintaining it?

So I think -- so this has been answered multiple times. It is a showcase in our presentation as well. I've said this in our previous answer, and I will try to summarize that. This company -- regulatory, we have to maintain a capital adequacy of 15%, which means a leverage of 6x. But we would like to ideally maintain our leverage of not more than 3.8x or maximum 3.5x. And by virtue of that, with 35% of our business in our balance sheet, we would be looking at raising this capital. Now raising this capital, the timing of it and when and source, we will consider at an appropriate time, but the company has multiple triggers to continue maintaining its growth without raising the capital as well if it wants to. First, we can -- with our targeted leverage of 3.5%, we can go further. Second, our targeted off-balance sheet asset of 35%, can be increased to say, 45% and leverage would remain the same. So I think so we have this completely in our control, and this does not worry us too much.

Okay. One last query. See, the market -- or the news is there, that there will be some inflation will be strucking MSME sector, especially will have some struggle during this period. So -- and we are corely into the MSME. So where we see our business going on that, please?

So sir, I think so SME and MSME is a very generalized term which is being used. I think, MSME should we look by the segment of the market in which one operates. And now in the revised difficile, INR 200 crore company is also -- a manufacturing company is also an SME. We service customers below INR 5 crores of turnover. Large focus of this company is to service the retail trading within our defined segment. And most of our sector are domestic consumption-driven economy. Our view is that domestic consumption-driven economy, the interest rate rise and inflation does -- would not mute the demand. One of the problem of our controlling inflation in our country that you have to increase the supply side, constraining demand doesn't help. So within our customer set, what we have seen till date, neither the credit demand nor the cash flow is getting a stretch because we service very small businesses.

We can take up few questions in the Q&A session. We have a couple of questions from the line of Mr. Ajay Chauhan. They are as follows. What will be cost trading income as a percent of total top line? Example, 3.2% has been taken in the last -- example given on the last slide of the PPT. And the second question is, 18% target ROE by FY '25. Will this revise further if you prioritize co-lending or plain lending?

Nirav, the first one, can you take second one, I'll explain.

Yes. Absolutely. So right now, I think the -- so basically, the 10.5% that we are talking about, infused co-lending -- core origination income that we say, the spread actually will be about 5.6%, and the rest will be the co-lending income -- as in this particular quarter.

On the next question on the ROE target, 18%. Obviously, on a INR 20,000 crores, our current growth -- it is -- first, it is very hard for listed companies to give projection for the year and for next 3 years. Now when you do that, you do most achievable targets and don't make blue sky assumptions. While the ecosystem of co-lending is improving with every passing day, when we made this prediction in 2021, there was a general skepticism about co-lending or lending-as-a-service model in India. However, we are proving our hypothesis right by going from 16% to 21%. And we are taking to 50% by FY '25. We know and understand that if we increase it by another 10 percentage points, our ROE will kick in further. But we believe that pure marketplace model does not go well with when it comes to the lending as a business. All our banks and partners who are on the liability side want to see us as a principal lending partner. So having a skin in the game, having its own balance sheet helps. And that's why we have made an estimate of half and half.

The next question is from the line of Mr. Manan Modi. With the transformation of UGRO to lending-as-a-service model, do you see the partnerships and alliances be slowing down?

Answer is no. Actually, our aspiration is that we create a bridge. So on 1 side -- and partnership alliance is 1 of our channels, a very good question. On 1 side, we have a large ecosystem of small fintech, small NBFCs, who otherwise can't get access to a large bank. So today, on 1 side, we are doing co-lending with them. On the other side, our originated assets, we are doing co-lending with banks. Our constant endeavor is through our experience, our GRO-Xstream platform and our -- we will like to bring some of our large banks to become a direct co-lender to some of our partners wherein we work as a bridge of providing technology, some form of credit enhancement and service that. So actually, once -- one of the such bank become a partner for our larger ecosystem, we think that over a period of time, our P&A partners would benefit from the co-lenders, which they are bringing on our platform.

The next question is from the line of [ Chad ]. Instead of declining customers who have less collateral, can we offer leading best practice to offer them smaller loans or different terms?

So I think so -- I mean Anuj, I can answer. So look, see the -- I think we don't differentiate the customer when we are assessing them. So at that point of time, our Gro Score doesn't differentiate whether the customer is bringing a property as a collateral, machine as a collateral or is an unsecured loan, it says, yes, I know and categorize the customer in 5 different banks. So to that extent, theoretically, we can offer the same customer an unsecured loan. But the issue is about affordability. The customer who want to borrow against a collateral want a much longer tenure loan because that fits in their cash flow, and want a lower yield. So a customer which is coming for a secured loan would not be satisfied with a very small unsecured loan. And also from a risk perspective, we offer up to INR 3 crores in secured, but we offer only up to INR 25 lakhs in unsecured loans. Amit, you want to add something that is about this?

No. You absolutely answered the question, Shachin.

The next question is how many micro branches do we plan to open this year? How is the performance of the branches launched last year in terms of productivity and payback period?

Okay. I'll take this question. So we launched -- we opened about 70-odd branches in Q3 and Q4. As per our projections, we have a 12-month breakeven plan for each of these branches. By about -- by end of this quarter, the first set of branches have broken even. We will see all these branches at a breakeven and delivering high profitability by December. Once proven -- so while the first few branches have proven that they can be profitable in the first 12 months of launching. And so once proven, I think we will look at the next stage of expansion. We -- depending upon how these branches behave and how early they break even. We will look at anywhere between 25 to 50 branches in this -- by this year-end, possibly in quarter 4.

And overall, this if for 2025 plan. In our identified 5 states, Telangana, Tamil Nadu, Karnataka, Rajasthan and Gujarat, we have done massive data analytics of roughly around 3,000-plus pincode, and this is a cluster approach, and we believe that there are 2,080 clusters in these 5 states where we would eventually would like to be present purely from opportunity and credit quality perspective.

The next question is, co-lending is a space where banks have good cash and the co-lender has a good presence in areas where the bank is not present. But with UGRO, we have very few touch points. How can we benefit the most among competitors?

So actually it is not a question of -- it is not necessarily only physical touch point which matters. Over a period of time, our touch point would also increase. But our origination and sourcing engine is multi-force. So while our physical branch footprint, the top 25 locations in what we call prime customer, can -- 40% to 50% of India's MSME credit outstanding is within this 25 locations. So you can get as much volume as you want within that 25 locations. Our current 70 locations, actually, they can -- they are very -- they are the first prominent point of credit origination purely from a cluster -- corresponding cluster perspective, and that would continue to grow. Third, we have a machinery financing business, which actually does not necessarily require every point physical presence because our source of origination is our OEM partners today, they are roughly around 180 OEMs in India, we are live with a large number of them, and which is increasing. And as that increases, your customer origination keep increasing. Our supply chain financing business, again, is as you continue to increase the number of anchors, the distribution channel, the distributor, the retailer, they can be anywhere, but the entire collection engine for that is driven digitally, and that is also will go in co-lending. Our P&A channel service is almost the entire universe of India, and their collection and infrastructure is being serviced by our partner. And whenever merchant financing platform would go live, you can be anywhere, and we would be able to finance it, that would also go into co-lending. I don't think so that physical presence is any constraint. Our digital infrastructure, our partners infrastructure is what drive and propel our co-lending partnership as well as our own balance sheet.

The next question is from the line of Mr. [ Chetan Parkar ]. How soon do we expect to finalize a co-lending partnership with a private bank?

But we have the last week, we have signed our first co-lending partnership with a private bank.

Next question is from the line of Mr. Manan Modi. Regarding geographical expansion, are there any key states that might contribute to growth, especially West Bengal has seen some issues lately. Have you seen any spreads in that state as well?

This is a very interesting question. At least in our last Board meeting, some of our independent director raised this question and we presented the data to this Board. Anuj, do you want to take this?

Yes. So overall, where we are present currently, and as Shachin was eluting, when we had selected sectors and then we launched initially, we have mapped the sector concentration with the geographies where they were prominent. And we are -- from our coverage perspective, we covered about 75% of total available target segment through our distribution network. Today, we are seeing healthy growth across all geographies. In certain sectors, owing to pandemic, we had deliberately slowed down. But for other sectors and across all geographies, we are showing -- seeing a very, very healthy growth. In Kolkata, 2. Although in Kolkata, we are present only in Kolkata City. And in our kind of target segment where with turnovers of businesses up to INR 5 crores, we are not seeing any stress at all.

Ladies and gentlemen, do we have any other questions?

I think that's it.

As there are no further questions from the participants, I would like to hand the conference over to Mr. Shachindra Nath for any closing comments.

Yes. Thank you so much. Our endeavor has been over the last 2 quarters is to explain our business model, the evolving landscape of how data and digitization would transform the SME financing in India. While we know that this -- from an outside, this seems to be a crowded space. People look at multiple number of NBFCs, and I just keep hearing this question, what is the core differentiation. We are trying to explain that differentiation. And we -- I think so we are gradually making the breakout of how multiple platform in the West has benefited and how our customer can benefit from that. From day 1, while we have never done a formal IPO, but we started as a listed company, raised all our capital in that in hope that the broader public market would appreciate the business model. Because one of the thing which is actually -- which is very unique that when we look at our peer set who are not listed, most of the investors who are putting in capital is in a very high threshold -- and eventually, they come to the public market and most of the public market investors are buying them very, very expensive versus we think that we showcase an opportunity to public market investor to benefit like a private equity investor of benefiting from our growth quality of business and huge infrastructure, both digital, technological and also people infrastructure, which we have built. Please feel free to ask any questions if you have. Nirav is here to support. And we will see you next quarter very soon. Thank you.

Thank you, sir, and the entire team for patiently answering all the queries. I would also like to thank the participants for making this an interactive session. Thank you for joining us, and you may now disconnect your lines.

Thank you.

Thank you.

Thanks.