UGRO CAPITAL LIMITED — Call Transcript 2022

Jul 29, 2022

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29[th] July,2022

BSE Limited 25[th] floor, Phiroze Towers, Dalal Street, Fort, Mumbai- 400001 Bandra (E), Mumbai - 400 051 Scrip code: 511742 NSE Symbol: UGROCAP

National Stock Exchange of India Limited Exchange Plaza, 5th Floor, Plot No. C/1, G Block, Bandra - Kurla Complex, Bandra (E), Mumbai - 400 051

Subject: Transcript of the Earnings Call with Analysts/Investors held on 25[th] July, 2022.

Dear Sir/ Madam,

We refer to our intimation dated 25[th] July,2022, informing uploading of the video recording of the earnings call hosted by the Company on the same date to discuss the Financial Results for the quarter ended 30[th] June,2022 on its website.

In this connection, pursuant to Regulation 30 of the SEBI (Listing Obligations & Disclosure Requirements) Regulations, 2015, please find enclosed the transcript of the said earnings call. The said transcript is also being uploaded on the website of the Company.

This is for your information and records.

Thanking You,

Yours faithfully,

For UGRO Capital Limited

NAMRATA Digitally signed by NAMRATA SAJNANI SAJNANI Date: 2022.07.29 16:51:53 +05'30'

Namrata Sajnani Company Secretary and Compliance Officer

UGRO CAPITAL LIMITED

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Registered Office Address : Equinox Business Park, Tower 3, 4th Floor, LBS Road, Kurla (West), Mumbai - 400070 CIN : L67120MH1993PLC070739

Telephone : +91 22 48918686 I E-mail : yougrow@ugrocapital.com I Website : www.ugrocapital.com

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May 25, 2022

May 25, 2022

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Rhave Shah:

Ladies and gentlemen, good afternoon and welcome. Emkay Global Financial Services takes great pleasure in housing the Q1’FY23 results conference call for UGRO Capital Ltd. 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 Office; 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 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 sirs.

Shachindra Nath:

Good evening, everyone, I am Shachindra Nath. Thank you all for joining our Q1 result presentation.

Shachindra Nath:

We started with this in our last quarter. Our belief is that like consumer credit business in India, the small business financing is also rapidly embracing the data driven underwriting. Since start of demonetisation and advent of GST and creation of three layer of India data stack is ensuring that in over next two to three years, the entire SME credit space would move to a data driven underwriting. The identity layer, the payment layer, and the data layer combined with the power of multiple alternative sources of data would move the credit into three different forms of credit which we call embedded credit, flow-based credit, and buy now pay later and this is also massively supported now. Once fully implemented the OCEN Network and the ONDC would make the merchant financing business very permanent. 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 must converge to lending as a service. We have seen the LaaS companies across Europe, UK, and US, but India is now seeing an evolution of lending as a service. What basically 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 becoming business of service. On one side of the spectrum, where we specialize, in 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 or the liquidity which are banks and large financial institutions. The way we design ourself that while we are a principal lender, we have a highly capitalised balance sheet and we borrow on our balance sheet, but our eventual goal is to be 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 we may want to call it. Our next few slides we will explain that how we are evolving from a leverage business to LaaS as a business but over this Q1 we have been able to prove that this is happening. We have been able to cumulatively disburse 6000+ crores over a period of last four years of which roughly around two years were lost. We have an asset under management of 3650 crore which is a growth of almost 700+ crore over a period of one quarter and we have an off-book AUM of 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 we have roughly around 1300 to 1400 people, we have around 1000 plus partners who services our customer base and for our supply chain business, we have very strong base of 75+ OEMs

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and anchors in our ecosystem version. And finally, I think UGRO over period of last five to six quarters have become a company which services the need of an SME or MSME customer right from a small ₹1-lakh loan to ₹5-crores of credit in different format of what we call the product through multiple distribution. So, we have ability to do secured business loan machinery, unsecured business loan, and micro enterprises loan, supply chain financing and merchant financing which is a digital platform which 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 could be doing to the MSME financing ecosystem in India.

Anuj Pandey:

Thank you Shachindra. So, over 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 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 thing first, a very quick review on how we have evolved in last three-four years. How we have been able to apply data analytics in 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 comprehensive data lead insights in early warning systems. We have applied the same approach in our operations and collections team 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 will probably be one of the first large scale NBFCs to do that. At the very heart of what we have done is what we call a GRO Score. When we started in January 2019 with our first loan, 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 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 one and pandemic two. Our portfolio has remained intact and is in much better shape vis-à-vis competition and during that impact we learnt that the banking behaviour 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 analysed 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 standardise and scale an underwriting methodology for across SMEs in India. Our ambition now is to include the GST data as well and internally we called this GRO Score 3.0. The target is to launch it by the end of 3rd 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 and this has been done by our own portfolio generated data, has been very thoroughly tested statistically. We have analysed more than 45,000 bank statements and more than 21,000 applications have been processed post our GRO Score 2.0 application. So, from as far as statistical rigor is concerned, we haven't left any 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 the basis of that of how what we can do is a very extensive library of about 25,000 plus data features which we have been collecting methodologically since day one of launch. So, for all customers, whether we approve them or reject them, we collect last 12 months of banking data in a

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May 25, 2022

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 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 five risk bands and depending on that risk band there is a probability of default which is assigned and now we have already seen 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 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 important step. 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 sector 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 there was enough data available to make use of. So, we had done a very large exercise with CRISIL and we have chosen eight sectors in which our target segments were smaller SMEs where we can give loans up to ₹5-crores and these eight sectors were healthcare, hospitality, light engineering, auto components, education, electrical equipment, chemicals, and food processing. We also, during our journey about one and half years back, introduced a new sector which we called micro enterprises because we realised 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 on very small businesses with loans up to 25-Lakh. So, today we have focused on these nine sectors, eight of our original plus ninth which came about last year. And now I will ask Amit to take over and he can take you through how we have designed in terms of technology, our product structure, and the financial numbers over to you Amit.

Amit Mande:

Thank you Anuj. And like you rightly said this is to all due to our GRO Score, our proprietary GRO Score, we call it the magic sauce, sometimes we call it the Coke formula, remains at the heart of everything that we do. So, around this GRO Score is what we have really built the robust tech platform. There was a need for a strong platform. There was a need for differentiated platforms to harness the power of data. This remains at the heart of our robust technology platform. There was a need to have customised differentiated platforms to harness every ecosystem and what this slide really shows is a different platform. Our GRO+ platforms look at, intermediary distribution in the prime branches. Our GRO Direct is where we go direct to the customer. GRO Chain is an interesting, high end platform that allows us to harness the ecosystems of the anchors and the suppliers on a supply chain business and the most important Mr. Nath did touch upon this as our route to becoming lending as a service entity, our extremely important platform, our GRO Xstream actually connects the fintechs and the NBFCs on one side, the public sector banks on the other side making us a truly lending as a service platform. All these really revolve around this one thing that we are proud of what we have done as a proof of concept, understood the test of times is our GRO Score 2.0.

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May 25, 2022

With this, really what are we doing is, we are servicing every credit need of every MSME. So, we have designed products starting from ₹50 Thousand to ₹5 crores. Products that have tenures from 30 days to around 15 years and all kinds of needs being serviced. What really this GRO Score does is a 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 a productive asset financing, unsecured loans, supply chain and our micro enterprise loans all of these revolve around this one simple concept of GRO Score and is supported by our platform. More importantly on the distribution side, we are now at about 96 locations. So, I was talking that our distribution strength continues to improve quarter-on-quarter. We are now in 96 locations, more than 1000 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 is more than 700 people that work on all these platforms. If we were to look at how our distribution is we have realised that there are multiple customer cohorts that we want to reach to and we have very different distribution models. Our branch lead channel looks at the Prime branches and the micro branches, they service the intermediary distribution, they take to the customers our loan against property, our affordable LAP, our unsecured loans business, our ecosystem business, distribution model actually harnesses the 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. On the GRO Xstream platform, on one side there are large number of partnership and alliances, NBFCs and Fintechs where we do very differentiated products with them to reach to the last mile and most importantly direct to customer digital channel that will now get enhanced 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 divulge 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, one important thing I wanted to talk about the lending as a service platform. As we continue to build this, our partnerships with the PSU Banks and the NBFCs for co-lending and SFCs continue to increase. In last quarter we had about five, we are now increasing this. We have got Punjab and Sind Bank on board, we have signed with Punjab and Sind Bank for all products. By next quarter, we will have another two 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 beautiful 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 Banks and some large leading NBFCs where we do co-lending and co-origination

Amit Mande:

We kept saying that we wanted to do lending as a service. When we spoke last time after our annual results, we said that we wanted to build a 7000 crore AUM by end of the year and this is really where we are saying that we are absolutely on track to deliver. We had a great first quarter, our AUM stands at about 3,656 crores, off book AUM is at 21%. Our net total income remains healthy at 10.5% and importantly our credit cost is very much under control and so it is at about 1.4%. Overall, I think the real message here is that we started this year to get to a 7000 crore AUM or 35% off book out of that and more than 2% ROA and I think

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May 25, 2022

we are completely on track to get to those numbers. The first quarter has been a testimonial of that. With that thank you and I open this floor for discussion.

Nirav Shah: Rhave, I think we will just take up the questions one-by-one. Rhave Shah: Anonymous Attendee Question-What percentage of sourcing is done through the DSA channel?

Amit Mande: At this point of time 55% of our business comes from the Prime branches 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.

Rhave Shah: Okay, we have a question from Mr. Chinmaya Bhargava.

Chinmaya Bhargava: Hi, good afternoon. Nice to see you all and congratulations on the numbers this quarter. I have about three questions on 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. We have 25,000 data points as you have said, right, but the more data points we add to a model, the more complex relationship becomes between the data and more noise and contradictions you will have between different data points. What framework do we use to choose which data amongst that huge set to prioritize and could you tell me for using like a Bayesian Framework, 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 one to GRO three where we are now?

Subrata Das: The first part of question which says there are 25,000 attributes and the method used. So, first of all it is a future library. It is a total universe of parameters which could be potentially used to predict the probability of default and you are right in saying that not all of them could be used without loss of significance. 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 fitting a very powerful model which holds the test of blacklisting. 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 techniques because we are predicting zero or one outcome or a good or bad outcome on a training dataset 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 least correlation with each other; however, in conjunction are most powerful in predicting the default. The exact formula or the system of base which is used to arrive at the probability of default that is the part which we keep as proprietary to ourselves.

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May 25, 2022

Chinmaya Bhargava:	Okay, that makes sense. Could you just tell me a little bit about how our understanding has changed from
	GRO 1 to GRO 3?
Subrata Das:	So, when we did GRO 1, we had very little data of our own and we were working in conjunction with a Large
	Credit Bureau and developing models on something that we call look alike population one that best
	resembles our target segment; however, they were not our datasets. From there, we moved onto 2.0 which
	is currently invoke since July 2021 which has two major components, one that being developed on our own
	incoming data and with all in-house models predicts much more sharply. Second, it combines the Credit
	Bureau history of the borrowers both the commercial entity as well as the individual applicants as well as
	the bank statement into one consolidated scoring model. And 3.0 is going to incorporate the GST records
	of the entity and thereby it is going to be first of its kind a very robust predictive model which captures the
	intensity of business in a real time GST. The financial discipline of the intent to pay through the Bureau
	record and the ability to pay through so let say the current cash situation and the credits and debits visible
	in the bank statement.
Chinmaya Bhargava:	Okay. Two follow ups there, so one the recent push from the RBI to on board the PSU banks to the account
	aggregators, do you think that is a significant data point for us to improve our model?
Shachindra Nath:	Yes.
Subrata Das:	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 aggregator has the participation of the entire banking sector that it can
	change things.
Shachindra Nath:	Currently the problem is a friction. So, today banking which is one of the most important component to
	assess 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 analyse that requires multiple level
	of curing and intervention but when the same dataset would come from account aggregation it becomes
	very efficient and second one of the big constraint for a non-bank 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 periodic basis and update our model and look at the point of lending
	what is the risk associated but it improves our AWS model early warning signals model, Anuj if you want to
	add something to that.
Anuj Pandey:	Yeah right, so basically today whenever they are getting data it is at the time of acquisition and there is no
	way that 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

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May 25, 2022

but during the life cycle of the loan as well, we would be continuously monitoring this cash flow data and that would be much more robust.

Chinmaya Bhargava: I can imagine. So, it is real time data which allows you to understand very quickly how sensitive the models are to change. Okay, last question on the proof of concept here, the proof of concept that we have uploaded so far is for GRO 2.0. Will we have anything out for the newer models like do you expect it to be better? Anuj Pandey: The new model is expected to go live only in December 2022. So, it is right now in the development phase. So, once we implement that we will require some time for some data to get set and established and post that we will do that, but there is a framework 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. Chinmaya Bhargava: Brilliant, thank you.

Shachindra Nath: I think I just want to add that the difference between 2 and 3, the 2 predict the default, categories the customer in five band. 3 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 the customer can afford 100,000 worth of loan or a 250,000 worth of loan which is today is estimated through a policy and product program on the front end so that is the core difference.

Chinmaya Bhargava: Okay. So, your approval rates, false positives all of that will improve, your Early Warning Systems with real time data all of that will improve. I have one last question from my side which is if I look at now our sector mix 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 was 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 choose it in the past months? Anuj Pandey: 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 lot of demand also seems to now getting up especially in education with children coming going back to school. So, slowly the plan is to keep building this up. Chinmaya Bhargava: Okay. Thank you so much and all the best. I will just back in the que.

Right the next question we have from the line of Samyak Shah.

Rhave Shah:

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Samyak Shah: Hi, thanks for the opportunity. 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 have?

Anuj Pandey: Okay, I will answer that. So OCEN, is Open Credit Enablement Network. The broad concept of this network is to have data in a marketplace which is driven data storage which is given by a protocol which is standardised across. The first used case of OCEN in India is a platform called GeM SAHAY where we were the first lender. So, the way it works is that GeM (Government e Marketplace) is a marketplace, SAHAY is the OCEN Network over and above that where on one 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. We were the first ones but there are many more financers which are doing that. It accesses the moment any SME gets an order on GeM, then their previous history of that transaction and SMEs demographic is available for a financer to make use of form business rules around that data and do an instant approval for that case. We are already live 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 rule engines and the API network is ready whenever need arises to further integrate.

Samyak Shah: 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? Amit Mande: 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 focus product for us but today with 75 branches over next two quarters we want to make it highly profitable and then focus on further expansion of micro branches. Any expansions 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 is 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 questions that somebody earlier asked what our direct distribution is and what is our intermediate 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 questions in terms of what are the plans on distribution and expansion?

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

Amit Mande: The answer is that we will continue to expand our micro branches where there is a direct to customer digitally assisted footprint and a direct to customer digital acquisition.

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May 25, 2022

Samyak Shah: Alright, alright. And my last question, so just a lot of people would still not know how to go about a loan approval or loan application process, so is there anything you are doing for improving awareness about how to go about this online loan application procedure?

Amit Mande:	Two things, one the moment I said that we are going micro branches, direct distribution we have feet on
	street. So, it is in customer assisted model and 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 products
	where the data requirement is very low and eventually take this up to a more complex product where we
	need data on their GSTs, where we need data on their securities, their properties or whether its machinery.
	Initially direct to consumer will always be a little simple journey, simple data requirements and over a period
	we will graduate with the customers to a higher end product.
Samyak Shah:	Okay, 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?
Shachindra Nath:	If you look at few of our slides you can see that. As of March-22, 16% of our book was off book, as of Q1
	and it is 21%. As of we are targeting as of FY23 to be 35%.
Samyak Shah:	I was talking about the disbursements that I think is the AUM correct.
Amit Mande:	Right, so the disbursements month-on-month will be at in the range of between 35% to 40% off book.
Samyak Shah:	Alright, thanks a lot. That's all from my side.
Rhave Shah:	We have the next question from the line of Manisha Agarwal.
Manish Agarwal:	Hello Sir, am I audible?
Nirav Shah:	Yes.
Manish Agarwal:	Congratulations on good set of numbers 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.
Shachindra Nath:	Yeah, Nirav can take this but I will just, broadly I think some of the conventional matrix which are applied

to NBFC, gradually we are saying is not relevant to us because the net interest margin which is a function

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May 25, 2022

of our blended portfolio yield minus cost of borrowing is actually not relevant for us and is not a right parameter to judge us because we may have a higher cost of borrowing vis-a-vis some of the large rated NBFC but our liability come from co-lending or off balance sheeting because that may be at much lower rate. Our gross income component is our interest income plus the fee income which comes from off balance sheet minus our cost of capital and that's why broadly it has not been given but just to get you a sense of our portfolio it is around 16.5% and cost of borrowing is 10.5%, Nirav if I'm correct unless you can clarify.

No, I think Shachin is right absolutely.

Nirav Shah: No, I think Shachin is right absolutely. Amit Mande: 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. Manish Agarwal: that is net total income. Is it the NIMs as well, 10.5%? Nirav Shah: So Manish, this includes the income from co-lending, so the net total income has been calculated is total income minus the interest expense right. Manish Agarwal: Okay, okay. Nirav Shah: So that is how it is. Manish Agarwal: And sir what is the provision coverage ratio around. Anuj Pandey: So, on the total book total provisions are about 1.7%, on stage 3 the provision coverage is around 28%. Manish Agarwal: 28%? Okay. And sir just one thing I just need to qualify, I heard somewhere that the company is making fund for the employees where they would be buying the shares from the market. Is it the right information or just news? Shachindra Nath: No, it is a right information sir. So, I think if you look at our exchange disclosure in our result board meeting, our Board has approved and fresh ESOP scheme. This ESOP scheme is only for purchase of shares through secondary market as at per SEBI regulation we can do that up to 5% and 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 30 crore 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 wrong. So as an when there is a market opportunity this employee welfare

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May 25, 2022

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.

Manish Agarwal: Okay. So, the money would come from the loan given to the employee. Shachindra Nath: Loan given to a trust, so SEBI regulation on ESOP allows this that either they have an ESOP which can be directly given by the company, or you can implement in 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. Manish Agarwal: Okay. Thank you so much sir. Shachindra Nath: And the shares would vest till 2025, employees would pay the cost of acquisition to the trust and trust would then return that money to the company. Or employees can ask the trust to sell the shares and pay the difference to the employees and the principal amount would come back to the company. Manish Shah: That’s very good. Thank you so much. That was so all from my side. Rhave Shah: Thank you. We have the next question from the line of Chet. Chet: Hi! congratulations on the good set of numbers especially in AUM and fee income. I had 4 questions which have accumulated. I will just start with the most recent conversation we had. So, on ESOPs, will this transaction count towards the 8% cap in the Articles of Association. Shachindra Nath: So, we have Sir 5.88% which is the ESOP and I think so you are right this will be roughly around 8% in total. I think so we're going for a shareholder approval, so absolute quantum is 30 crores and if this quantum because we don't know what real percentage of shareholding we would be able to acquire because it is a function of price and in a particular year you cannot do more than 2% but if its process that cap percentage of 8% when we are going for shareholder approval whatever is the calculation we will request for shareholders to approve for that change. Chet: That's great, okay. Then the second question was on the competitive landscape in co-lending. So if in colending the fees say that we are the leading partner for banks especially PSU banks who have issues with you know front book growth and front book quality who is our next competitor and you know how far ahead are we you know in terms of using the data tripod etc.

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So, sir it’s very difficult to talk about who is 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, look at from a large public sector banks perspective, think of an SBI or Bank of Baroda, or a Union Bank most of them would like to partner with an NBFC of substance. NBFC of substance means that they would look at some significant amount of capital, they will look at a profitable track record, they will look at healthy portfolio quality and some vintage and then would like to partner. So 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 co-lending is only for priority sector so the asset class which can go in co-lending is either MSME, agri, or you know almost of them and nothing beyond that. So fortunately, then you look at the market participants so there are three types of participants. You have AAA to AA diversified large NBFCs, I think so for them because not necessarily that most of them are in priority sector, so there are 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 they there balance sheet could have a combination of wholesale, corporate credit, wheels business, you know SMEs, gold loans, so on and so forth. So, that is why most of those top 10 are large NBFCs are today not entering into co-lending and most of their asset classes are also not suited for a bank, and we have roughly around 50+ NBFCs, which are wide SME or Agri segment but are neither well capitalized nor the portfolio track record wherein they can get accepted by the bank. Anything between BBB- to a BBB+ companies and that’s why that segment of the market is also getting excluded. We at UGRO with a 1000 crore of capital with A rating and 5-year of vintage with 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 there will be a convergence which would happen. The large NBFC would also start doing co-lending and smaller NBFC would become little, larger and do co-lending but we think so that we have a you know window of becoming market leader in next 3 years by the time this catch up happens.

Shachindra Nath:

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

Shachindra Nath: I don’t understand the question on cannibalization.

Chet: So basically, you know our micro branches they don't compete with you know the likes of Bank of Baroda you know Punjab and Sind Bank right, we make sure that they don't compete with them.

Shachindra Nath: Sir our segment of the market doesn’t compete with the banks. I think across every segment of the market I think it is proven by time that the segment of the market which a fintech or a an NBFC service while banks have much bigger larger massive presence, we cater to different need right. You know even if in a same location a bank’s 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

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and technology, but they have many other priorities also right. So that’s why they have adoption of this on their own would be slower, so I don't think so there is any cannibalization.

Chest: Are these micro branches like we are focusing on micro branches in our next phase of growth like to a limited extend, my question was are these micro branches a strong contributor in our co-lending portfolio? Shachindra Nath: Sir, yeah, micro branches would be bigger contributor in terms of the overall portfolio yield and profitability. In terms AUM growth, they may not be a very large contributor as of now, but they are increasing. All our banking partners are accepting our micro enterprises credit policy as a product for co-lending and gradually as the funnel would increase that would also start going into the co-origination lending. Amit if you want to add something to that. Amit Mande: No absolutely Sachin and to answer the question the micro secured product that we have, is a great high yield product. It's 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 and at the same point of time like Mr. Nath said we have already started doing micro secured co-lending in couple of banks and it will continue to slowly move into the co-lending. Chet: A follow up on that is you know are we are applying stringent collateral checks on this micro secure business? Amit Mande: Absolutely. So, there is a there's a clear policy on what we accept as a collateral, and these are very much in lines with what are acceptable by the banks and so that is essential reason Chet why even this product is today acceptable in a large PSU bank because of these. Chet: Yes, I got my answer. If SBI and Bank of Baroda are comfortable taking it so it needs to be one of list of 10 items. Great. Last question was on the QIP or the you know our leverage ratio basically so right now we are at a debt to equity of 2.3, you know obviously with co-lending it's not going to rise fast but as and when we reach 3 to 4 you know we would need to raise funds to expand considering that the stock price you know is a function of people you know volume as well we may need to do a QIP near book value, is this is something we have considered and have we considered the options. I don't need to know the options, but have you considered our options you know 6 months 9 months down the line. Shachindra Nath: Absolutely, so I was writing an answer to Tushar, I do not know the same person is speaking or not, I was just writing answer to him. So, first and foremost regulatory we are allowed to do up to 6 time of leverage but as a company in our initial first 5-7 years, we have said that we would lever ourselves only up to 3.5 or 3.8 times, but that is also a tool available to us. We have other tools which is co-lending. We have target 35% of our balance sheet to go in co-lending but depending upon market condition we can push pedal and

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increase that 35% to 45% and our leverage would remain the same what we are targeting. Third, I think so that our peers set currently the public market is very muted when it comes to the lending. No faults have occurred. The public market is muted because majority of the public market investors are worried about impact on the balance sheets of banks and NBFC and what is the adjusted book value and that's why they are not being able to ascribe a price and that is you know 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 in a mix and you cannot go beyond that but our view is that in you know as we continue to improve and show our growth there are you know intelligent set of investors who would come dedicated for us in that should improve our both price and also liquidity. Having said that our source of capital is not necessary only public market, our source of capital is multiple you know in a listed company will raise roughly around 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, DFIs, big family offices and multiple others who will compare or who are comparing us to the private market transactions where multiple NBFCs on fintech who are raising equity capital anything from 3 time price to book value to 7 or 8 time price to book value and you know while you get benchmark to you listed price but I think so that is the fair value where we should be and hopefully some of the private investor would look at from that eye and angle.

Chet:

Okay sounds good. So, I think it's fair to say that you know my calculations that 6 to 9 months is that can probably be you know considered that they were too short, the assumption was too short, so we can still sustain you know quite a few more months or few more quarters.

Shachindra Nath: If we can sustain a full year we can sustain even beyond if we want to.

Chet: Sounds good. That's all from my side thank you. Rhave Shah: Thank you. We have the next question from Mr. Atul Prakash. Atul Prakash: Yeah, actually this thing, wanted to understand so we have mentioned that we are at 7,500 crore is our plan by FY23 AUM.

Shachindra Nath: 7,000 crores.

Atul Prakash: Pre-book from FY20 the AUM was approximately 800 to 900 between. So, we're growing a book to 9x in the matter of 3 years and then there is GRO Score card 1, there is GRO card 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 we see, I think 2.13% I think was the GNPA this time. So, if you back test it at FY20 your GNPA number would be very high. So how we are checking these things?

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Shachindra Nath:

So, I would say 3 things, I think so you are only looking the headline number, but you are not looking the incremental Opex which is being incurred to build a 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 post ILFS, we decided only to deploy our capital. So out of 958 crore of capital we deployed 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 first 6 months, but we were confident that we have to increase our infrastructure so as of FY20 were a company of 170 people, as of FY22 we were a company of 1,111 people. As of FY20, we are a company of 8 physical location as of FY22 we are a company of 91 physical location. As of FY 20 you know our technology team infrastructure was consisted of 5 people, as of FY22 it was 90 people, as of 20 to 22 our data analytics team was you know roughly around grown 5x. So, the growth is coming because this company has taken very early big Opex to build physical and digital infrastructure and basis that you know the growth is now coming. So, it's a base effect. Number 2 in terms of the portfolio quality I think so you know you can't back test its basis lower AUM because our first year AUM obviously we suffered from pandemic but we have demonstrated that during the pandemic we can control the portfolio quality much better than our peers set and only business than has to look at you know gross NPA on the basis of an expanding portfolio and you know 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 it would be the portfolio quality at future. Anuj, you want to add something please feel free.

Anuj Pandey:

So, I just want to add for a business model like ours, where now 21% of the book is off in form of co-lending and co-origination and eventually at the end of this year around 35% and in 2025 50%. A good perspective one can get if I look at the GNP by total AUM. So, in this quarter actually our GNPA is 1.7% if we add 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 addition to what Shachin you said in a growing portfolio specially the first year the denominator being lower and then facing two pandemics, post that whatever has come out we are quite confident that directionally we are stacking up well.

Atul Prakash:

Okay just one more thing wanted to understand on your GRO Score card. So basically, there was a presentation where you are mentioning there was A band, B band, C band and then there was disburse loan and there was undisbursed loan. So, if a loan is getting A band in your scorecard, then why you were not disbursing the same and basically how this scorecard is coming up there.

Anuj Pandey:

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 1 crore loan against property, but his property value is 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

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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 basically GRO Score A and B.

Atul Prakash: 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 of June end and out of which how much is in the 0+, 30+ and 90+. Anuj Pandey: So, our total restructured portfolio at the end of June is 120 crores, which is approximately 3.3% of the AUM and out of this 20% has become NPA. Rest 67% is current and 4% is in 30 to 90 bucket. Shachindra Nath: You can also give color of the restructured portfolio by segment of the market, overall. Anuj Pandey: We can do that, so overall if you look at the total restructured portfolio by product then approximately 60% of that portfolio is under secured about 25% under unsecured and rest in supply chain and by sector about 85% of the portfolio is under education, hospitality, or light engineering. What we have seen in terms of repayment behavior. We are seeing that education and light engineering is back to normal at pre-pandemic levels. In hospitality though overall segment is now looking up but the stressed customers continue to be stressed and we had done an internal analysis in last quarter where we had predicted of how much more NPA can come in specially from the unsecured hospitality sector from our current restructured portfolio and we have planned for approximately 7-8 crores more NPA coming from there.

Shachindra Nath: And our current provision is more than sufficient to cover it. Anuj Pandey: Yes. Atul Prakash: Okay, just one more thing I wanted to understand we are going with such a high growth plan, and we are on the on the track to perform it, so there will be a capital adequacy ratio that you need to be maintaining. So, what are the strategies where we want to fix it on the capital adequacy ratio where we will be maintaining it. Shachindra Nath: So, I think so this has been answered multiple time. It is showcased in our presentation as well. I've said this in our previous answer, and I will try to summarize that. Regulatory we know we have to maintain a capital adequacy of 15%, which means at a leverage of 6 but we would like to ideally maintain our leverage of not more than 3.8 times you know maximum 3.5 times and by virtue of that with 35% of our business in off balance sheet we would be looking at raising this capital. Now raising this capital, you know the timing of it and when and source we will you know 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 you know

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with our targeted leverage of 3.5 we can go further. Second our targeted off-balance sheet asset of 35% can be increased to 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.

Atul Prakash: One last query, see the market or the news is there that there will be some inflation will be striking in MSME sector specially will have some struggle during this period and we are corely into the MSME where we see our business going on that place. Shachindra Nath: So, sir, I think so SME and MSME is a very generalized term which is being used. I think so SME and MSME should be looked by you know the segment of the market in which one operate and now in the revised definition even a 200-crore company, a manufacturing company is also an SME. We service customer below 5-crore of turnover. Large focus of this company is to service the retail trade in within our define 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 would not mute the demand. One of the problems of 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. Atul Prakash: Okay thank you so much and all the best for the upcoming results as well and congratulations on the good numbers. Rhave Shah: Thank you. We can take up a few questions in the Q&A session. We have a couple of questions from the line of Mr. Vijay Chauhan. They are as follows what will be co-spreading income as percent of total topline, example 3.2% has been taken in the example given on the last slide of the PPT. And second question is 18% target ROE by FY25. Will this revise further if you prioritize co-lending or plain vanilla lending? Shachindra Nath: Nirav, the first one can you take? Second one I will explain. Nirav Shah: Yeah absolutely, so right now I think so basically the 10.5% that we are we are talking about includes the co-lending or you know the co-origination income that we see, the spread will be about 5.6% and the rest will be co-lending income in this quarter. Shachindra Nath: Next question on the ROE target 18%, obviously on a 20,000 crore or current, you know 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 a 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 you know lending as a service model in India; however, we are proving our hypothesis right by going from 16% to 21% and we are taking it to 50% by FY25 we know and understand that if we

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increase it by another you no 10 percentage point, our ROE will kick in further but we believe that pure marketplace model does not you know 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 in skin in the game having its own balance sheet helps and that's why we have made an estimate of half in half and half.

Rhave Shah: Thank you next question is from the line of Mr. Manan Modi. With the transformation of U GRO to lending as a service model do you see the partnerships and alliances piece going down.

Shachindra Nath: Answer is no. Our aspiration is that we create a bridge so on one side and partnership and alliance is one of our channels, it is a very good question. On one side we have a large ecosystem of small fintech, small NBFCs who otherwise can't get access to a large bank. So today on one side we are doing co-lending with them on the other side our originated asset we are doing co-lending with banks. Our constant endeavor is through our experience, our GRO Xstream platform and our ability, you know we would 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. So, once one of such banks 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 we were bringing on our platform.

Rhave Shah: Thank you. The next question is from the line of Chet. Instead of declining customers who have less collateral can we opt for leading best practice to offer them smaller loans on different terms.

Shachindra Nath: So, Amit and Anuj, I can answer. So, look I think so 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 or machine as a collateral, or it is an unsecured loan it says yes or no and categories the customer in 5 different bands so to that extent theoretically we can offer the same customer an unsecured loan, but the issue is about affordability. The customer who wants 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 who is coming for a secured loan would not be satisfied with a very small unsecured loan and from a risk perspective we offer up to 3 crores in secured but we offer only up to 25,00,000 lakhs in unsecured loan. Amit, you want to add something that.

Amit Mande:

No absolutely, you have answered question Shachin.

Rhave Shah: Thank you. The next question is how many micro branches we plan to open this year. How is the performance of the branches launched last year in terms of productivity and payback period?

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Okay. I'll take this question. So, 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 end of this quarter, the first set of branches have broken even. We will see all these branches at a break even 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, depending upon how these branches behave and how early they breakeven. We will look at anywhere between 25 to 50 branches by this yearend possibly in the quarter 4.

Amit Mande:

Shachindra Nath:

And overall, in our 2025 plan in our identified 5 state Telangana. Tamil Nadu, Karnataka. Rajasthan, and Gujarat. We have done massive data and tricks of roughly around 3000 plus pin code and this is a cluster approach, and we believe that there are 280 clusters in these 5 states where we would eventually like to be present purely from opportunity and credit quality perspective.

Rhave Shah: Thank you. The next question is co-lending is a space for banks who have good cash and co-lender has good presence in areas where the bank is not present, but with U GRO we have very few touchpoints how can we benefit the most among competitors?

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

Rhave Shah: Thank you. The next question is from the line of Mr. Chinmay Bhargava. How soon do we expect to finalize a co-lending partnership with a private bank?

We have signed over first co-lending partnership with a private bank.

Shachindra Nath:

May 25, 2022

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Rhave Shah: Thank you. Next question is from the line Mr. Manan Modi. Regarding geographical expansion are there any key states that might contribute to grow especially West Bengal has seen some issues lately? Have you seen any stress in that state as well. Shachindra Nath: This is very interesting questions. I think so in our last board meeting some of our dependent director raised this question and represented the data to this Board. Anuj, you want to take this. Anuj Pandey: Yeah. So, overall, where we are present currently and as Shachin was eluting to when we had selected sectors and we had launched initially we have mapped the sector concentration with the geographies where they were prominent and we are from our coverage perspective recovered 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 seeing a very-very healthy growth. In Kolkata too, although in Kolkata we are present only in Kolkata city and in our kind of target segment with turnovers of businesses up to 5 crores, we are not seeing any stress at all. Rhave Shah: Thank you. Ladies and gentlemen, do we have any other questions. Thank you, 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. Shachindra Nath: Thank you so much. Our endeavor has been over the last two quarter is to explain our business model, leave the evolving landscape of how data and digitization would transform the SME financing in India, while we know that from an outside this seems to be a crowded space. People look at multiple number of NBFCs, I keep hearing this question what is the co-differentiation. We are trying to explain that differentiation and I think so we are gradually making the breakout of how multiple platforms in the West has benefited and how our customer can benefit from that. From day one, while we have never done 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 things which is very unique that when we look at our peers set who are not listed most of the investors who are putting in capital is in very threshold and eventually they come to the public market in most of the public market investors are buying them veryvery 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 question if you have, Nirav is here to support, and we will see you next quarter very soon. Thank you.

Rhave Shah:

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.

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