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The Playbook for Building a $3.5B Fintech Unicorn | Raghu Kumar (Upstox)
342 Plays2 years ago
"After raising millions of dollars, the first thing we did was shut down our most profitable division." This was the pivotal, contrarian decision that put Upstox on the path to becoming a unicorn. In this episode, co-founder Raghu Kumar reveals why killing their "golden goose"—the proprietary trading desk that funded the company's early days—was the secret to building a trustworthy, scalable fintech empire.
Raghu Kumar is the co-founder of Upstox, one of India's largest stock brokerage firms, valued at over $3.5 billion. A trader at heart, he started his journey by turning a personal stake of just $10,000 into more than $2 million in two years using sophisticated algorithmic trading. He then co-founded and scaled Upstox to over 13 million users before moving on to his next ventures, Rain Platforms and Tylt Money.
In this conversation with host Akshay Datt, Raghu Kumar unpacks the foundational thesis behind Upstox's massive success.
Key Insights from the Conversation:
- Trading to Build: Raghu's first venture was not Upstox, but a proprietary trading firm that turned a small stake into millions. The profits from these trading strategies, first in the US forex markets and later by arbitraging Indian stocks, provided the seed capital for the brokerage.
- Strategic Sacrifice: A critical turning point was shutting down their profitable proprietary trading desk after raising their Series A funding. This eliminated any potential conflict of interest with their clients and forced the entire company to focus on the scalable retail platform.
- Tech-Driven Disruption: Upstox was a pioneer in using technology to solve core friction points. It was the first brokerage in India to offer a completely paperless account opening process using Aadhaar and one of the first to provide a retail API for users to build their own trading algorithms.
- India's Unique Algo-Trading Culture: At the retail level, more individuals are building and deploying their own automated trading algorithms in India than in any other country in the world, including the US.
YouTube Timestamps & Chapters:
00:00 - From a $10,000 bet to a $3.5 Billion Company
01:19 - The Forex "News Trading" Strategy that Made Us Millions
02:56 - Why We Moved to India: The Arbitrage Opportunity
11:41 - The Secret Sauce: How We Traded India's Inefficient Markets
20:58 - Why We Started a Brokerage: The Birth of Upstox (RKSV)
25:39 - Disrupting the Market with Unique Pricing & Growth Hacks
35:25 - The Engine Room: What it Really Takes to Run a Brokerage
40:14 - Building Upstox Pro: From Third-Party Software to In-House Tech
48:18 - India's Unique Edge: The Rise of the Retail Algo Trader
52:57 - The Tiger Global Investment & The Future of Indian Investing
YouTube Hashtags:
#FounderThesis #Upstox #RaghuKumar #IndianStartups #StockMarketIndia #Fintech #AlgorithmicTrading #Entrepreneurship #StartupPodcast #InvestingForBeginners #TradingStrategy #MakeInIndia #Unicorn #StartupStory #AkshayDatt
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Transcript
Founding of Upstocks and Initial Success
00:00:00
Speaker
Hi, I'm Ragu. I founded Upstocks, and after Upstocks, I founded RAIN Platforms.
00:00:18
Speaker
Raghu Kumar is one of the most unique founders we have featured on our show. He and his brother Ravi grew up and got educated in the US and converted a $10,000 investment into $2 million through algorithmic trading in just two years. Then they took the contrarian decision to move to India to trade in the Indian equity markets and this led to the birth of RKSV
00:00:42
Speaker
which today is better known as up stocks. Up stocks became a unicorn in 2021 and is one of the leading trading platforms in India, having raised more than $200 million still date. This is the first part of Akshay Dutt's conversation with Raghu Kumar. And in this episode, they talk about Raghu's journey from making phenomenal wealth through trading and the journey of building up stocks in a highly competitive market.
00:01:07
Speaker
Listen on, and if you like such insightful conversations with disruptive startup founders, then do subscribe to The Founder Thesis Podcast on any audio streaming app.
Early Trading Strategies and Market Entry
00:01:19
Speaker
In college, I basically got introduced to trading. And so one of the first things I did after graduating was I started trading my own money. And then using the money that me and my brother made, we moved to India in 2000. So basically what happened here was in 2006, that's when I started trading with my own money.
00:01:42
Speaker
And I stumbled into some amazing strategies. These were basically strategies involving the foreign exchange markets. And specifically, what we were doing was we were taking advantage of news events. So for example, in the US, every Friday,
00:02:02
Speaker
the US NFP numbers are now. So this is the employment figures. And based on those employment figures, the US dollar goes up or down like immediately within seconds. So if you have access to that information very quickly and you have access to the right brokers, you can place these trades and make a lot of money.
00:02:21
Speaker
So what we did from 2006 through 2008 was we basically just ran this one strategy. It's called news trading. And back then, we were one of the first people to stumble into that whole strategy. So there was an element of luck, obviously, but also we were looking for these types of strategies. So we discovered them. By 2008,
00:02:44
Speaker
the competition caught up to us and it basically became like impossible to make money at the retail level. Like you had to be basically like a Citadel or one of the big hedge funds or prop
Exploiting Market Inefficiencies and Forex Success
00:02:56
Speaker
funds. And so we packed up our bags and we, so during that time in 2008, I started researching India's capital markets. And what I realized was similar types of strategies could actually be run
00:03:10
Speaker
in India. So our first reason to move to India was actually not for up stocks. It was actually to start trading in India. So from 2008 all the way through 2015, we actually actively traded the Indian markets. And in that process, while we were in India, we obtained a brokerage license and we decided to set up a retail shop as well. So trading has always been very close to me basically. Yeah.
00:03:37
Speaker
This strategy which you found in 2006, why did it exist? Was there some sort of market inefficiency, some information asymmetry because of which that strategy existed? Yeah, so the strategy always existed. It's just that the information wasn't available at the retail level.
00:03:57
Speaker
And it's the type of strategy that's not infinitely scalable. So if you think about it, when you trade through a broker, there is a certain amount of liquidity available. And when it comes to foreign exchange, the brokers themselves are the market makers. It's not like
00:04:16
Speaker
when you trade through a regular retail brokerage where the broker is just offloading the liquidity available on the exchange, on a spot for an exchange broker, many of these brokers are the market makers. They're taking the other side. It's like crypto exchange. Most crypto exchanges are also providers of liquidity.
00:04:38
Speaker
Exactly. So when the broker itself takes the other side of the trade, then what happens during these news events is that the broker also has a mandate to provide liquidity, but what they do is they don't provide a lot of liquidity.
00:04:54
Speaker
So during that news event, for example, let's say the Federal Reserve is announcing an interest rate decision, that time, those few seconds before and after the announcement, you'll notice a lot on a lot of these brokers, there's very wide bid-ask spreads and there's very little liquidity. So there wasn't much money to be made, but also what happened during that time was
00:05:21
Speaker
these news announcements were being released to the retail public very quickly. So basically before 2006, you would have to have access to Bloomberg or some crazy high-end terminal to get access to that information.
00:05:36
Speaker
But at the retail level, what was happening was a lot of mom and pop shops and basically people just operating their own businesses, they were releasing this information on the internet. So a lot of the retail public jumped on and it created this massive wave. And then what happened was because so many people were acting upon the news, that in itself led to a lot of price movement.
00:06:01
Speaker
So you're in Japan, right? So in Japan, what happens is when a lot of these news events are released, they're already factored into the prices. So you'll notice that, for example, the yen will not move real time to a lot of these news announcements, right? Because what happens is a lot of these news announcements, unfortunately, are leaked to
00:06:21
Speaker
the journalists or whatnot in advance. But in the US, that was not the case. Long story short, basically, a retail trader was able to make a killing. And those were like crazy years from 2005 through 2008. News trading was this crazy phenomenon. In fact, there's a famous book called Flashcrash by Michael Connolly, where he talks about this phenomenon in that book. So yeah, those are really good years to be an automated algorithmic trader.
00:06:51
Speaker
I'm going to ask what probably sounds like a silly question, but how do you make money in forex trading? What is forex trading? Okay. Yeah. That's actually a really good question. So the forex exchange markets are actually the most liquid market in the world. Okay. So in terms of
00:07:06
Speaker
of transactions done in terms of just a nominal amount of gross turnover, nothing compares to foreign exchange because everyone trades foreign exchange, right? Business is traded to hedge against risk. And then you have retail traders, institutional. So the whole world is trading forex. Now what is forex is nothing more than just the value of the currency, right? So how is the USD, the US dollar calculated? Now the thing about currencies is that
00:07:36
Speaker
everything is relative, right? It's not like the US dollar in itself, it does have value, but we look at the dollar in terms of how it compares to the Euro and the Pound and other currencies. In fact, there's I think six or seven major currencies in the world. So what happens is these currencies are actually traded live and that determines their live price. Now, certain countries, what they do is they control the value of that currency essentially, right?
00:08:07
Speaker
like China. And then you can do that in a hard way or in a soft way. The government can buy back the currency or there are certain ways you can basically ensure that the currency is not depreciating or appreciating too much. So if you're an export-driven economy, then you want to ensure that your currency is not appreciating too much against other currencies. But in the case of the dollar and things like that, yes, the US government definitely has an incentive to
00:08:33
Speaker
ensure that it doesn't get too out of whack, but generally it's a free market. So that's what these markets do. They basically just dictate the value of the currency. So Forex trading would be like, say buying euros today because you feel that dollar will become more valuable against euros. No, that's not bad. It's the other way around. So what happens is, let's assume that I don't even know what the EuroUSD is at right now, but let's assume it's trading at 1.2 or something, right?
00:09:02
Speaker
That means if it's trading at 1.2 and you're looking at the euro USD, that's the number of dollars per euro. And if you think the euro is going to appreciate, then you buy the euro USD.
00:09:18
Speaker
That's all it is. And when you're buying the EuroUSD, you're essentially saying you're bullish on the Euro and you are bearish on the dollar. So the way we would trade, it's really fascinating, is in advance exactly which announcements are coming out
00:09:34
Speaker
for each country. This is obviously public information, there's news trading calendars, and a lot of these US releases are done at 8.30 in the morning EST. A lot of the UK announcements happen at 4.30 EST in the morning. So there would be basically six, seven currencies that you can actually trade and make money on. Now, one thing for me was it was just me and my brother. I was the one who was coming up with all the models.
00:10:01
Speaker
he was the one coding them, we would have to stay up for basically all day. It wasn't all day because you're only really staying up for the 20, 30 minutes before the announcement and after the announcement. But these announcements happen like throughout the day and
00:10:16
Speaker
currencies that would move would be the pound, would be the dollar. Euro wouldn't move, right? Because Euro is not really pegged to one country's activity. It's a Euro, right? So Euro generally wouldn't move to announce this unless it was any sort of indicators that were involving the entire Euro zone. And then you would have the New Zealand, I forget what it's called, New Zealand Corona, I think, and the Australian dollar, and Sweden and Norway, right? Those are the only countries, and Canada, those are the only countries where when certain numbers were released,
00:10:46
Speaker
the currency would move immediately and it would move a massive amount, right? And the great thing about foreign exchange is that you can take on a lot of leverage. So these retail brokers and even prime brokers, they offer sometimes up to a hundred to one leverage, right? Which means if you have a thousand dollars in your account, you could trade a hundred thousand dollars worth of value on that trade. But then you can also lose a lot of money, right? So sometimes we would make
00:11:13
Speaker
hundreds of thousands of dollars in one day and other times would lose $50,000 in one day. So we were able to basically turn something like $10,000 into more than $2 million in the span of two years. And I've talked about this on other podcasts, but basically it was just a crazy time to be news trading. So yeah. Amazing. So what did you identify in India as strategies for trading?
Arbitrage Opportunities in India
00:11:41
Speaker
Yeah. So the secret sauce comes out. So basically what we did, Akshay, was we did the most basic type of trading, which is called arbitrage, right? And speaking about arbitrage, we were talking about SPF earlier. SPF basically... Like SPF is Sam Echlenfried. Sam Echlenfried.
00:12:02
Speaker
of FTX. So they had a sister concern called Alameda Research. And this is all public news now, but Alameda basically a lot of the money that they were trying to make was basically based off of arbitrage as well. And in fact, SPF's background came from basic crypto arbitrage. So arbitrage is nothing more than when something is being sold in one market for a certain price and then
00:12:31
Speaker
another market for a different price, but the same good is being sold. Then you can basically buy on one market and sell on the other market. Pretty simple stuff. Now in India, a lot of these companies are cross-listed between the NSE and the BSE. So if you look at Reliance Industries, it's listed on the NSE and on the BSE. It's the same exact company, except it's a different exchange.
00:12:57
Speaker
Now, one unique thing about India is that you don't have interoperability, which basically means you cannot buy on one exchange and then the same day sell on the other because for whatever reason, the exchanges don't really recognize each other. That's a decision for different matters, but for whatever reason, that's how it is in India. And in the US, it's not like that. In the US, the NYSE and NASDAQ are interoperable.
00:13:24
Speaker
Correct. They recognize each other, which is why you don't even see spreads in the US. Now, keep in mind this was 15 years ago or 14 years ago, but back then, you would notice a massive difference in price between the BSE and NSE. Liquidity, one market was more liquid than the other.
00:13:46
Speaker
Liquidity, but it's not just liquidity. There would actually be not many logical reasons, right? Sometimes symbols would be trading at a discount on the BSE and at other times, other securities would be trading at a discount on the NSE. It happened all the time. And this is something I actually tried to figure out. It's like, why is this happening? It just happened. It's almost like each market is independent, right?
00:14:09
Speaker
So obviously, but there is a dependency obviously, but so that the trick then became how do you find these opportunities and take advantage of them? And then that became like a big puzzle because the two exchanges don't recognize each other. Right. But oftentimes what would happen is the prices would collapse. Right. They wouldn't collapse a hundred percent, but they would collapse enough to make a profit. So for example, you mean the difference between them would collapse?
00:14:40
Speaker
Exactly. But it wouldn't collapse to zero oftentimes. So let's say, for example, a stock is trading at 100 on the BSE and 105 on the NSE. And we see this price difference in the morning. By the afternoon, right before the markets close, that price difference might go to, let's say, 2 rupees versus 5. So you're capturing a 3 rupee profit, and then you have to make sure that 3 rupee profit
00:15:05
Speaker
captures or covers your transaction costs and STT and things like that. So very precise and everything was done algorithmically in a fully automated manner, but we were trading essentially every security on both exchanges right throughout the day. You need to decide which price is the truer reflection and then not
00:15:27
Speaker
Yeah, not really, right? Because you don't necessarily care what's the true price as long as you can make a calculated on the prices collapsing, right? So everything came down to probabilities. You don't really care because I don't know what the true price of, let's say it's the Reliance Industries, I don't know if Reliance should be trading at 100 or 95 or 200 or 1000, right? And that's a totally different matter. But if something is trading at 100 on one exchange, 105 on the other exchange,
00:15:54
Speaker
then chances are the real price is probably somewhere in between. The true market perceived value is probably something in between. And so we would
Transition to Retail and Platform Development
00:16:04
Speaker
start basically employing the strategy. This is the first strategy that we used. And then we basically developed a cash futures strategy, which is very common in India. We have a lot of
00:16:13
Speaker
they're called jobbers, right? Essentially what they do is they, you might've seen them, they basically trade all day in front of a computer terminal. And oftentimes they do it manually, but they're basically trying to capture the price difference between the cash and the future. So cash is basically equity, right? So equity in the future. And what happens is usually the future price is at a premium compared to the equity price, but that also collapses as the month goes through. So that was another strategy. And then we got into commodities trading.
00:16:43
Speaker
Yeah. An instrument which says that I will sell the dine stock to you at 105 rupees after 30 days. That would be a futures. Exactly. Right. So in India, you have a very liquid derivatives market, including futures and options, obviously. And so the future is essentially what is the future price of this product or symbol on a given expiry day. And then you're trading that value essentially. Right.
00:17:12
Speaker
So in India, you have an active liquid futures market as well, and obviously you have NFTY and bank NFTY futures. A future can be either a promise to buy or a promise to sell at a certain price after the X number of days.
00:17:29
Speaker
Yeah, the technical definition, I'm not so certain about, but essentially what it is, you're trading the future value of that product, right? So when I go to a commodities exchange and I'm trading, let's say MCX or crude oil futures, that's essentially what is the price going to be on this given day in the future. And what happens on that day is obviously the live price and the futures price will be the same.
00:17:56
Speaker
at the expiry time. So that's just what you're trading. Yeah. So it was really fascinating. And our advantage actually wasn't really the models. It was actually the technology because what we were doing was we were trading in a fully automated algorithmic manner. So there was no human intervention. And we were one of the first in India actually
00:18:21
Speaker
to employ what's called direct market access. So we got basically access to those prices directly in a fully automated algorithmic manner because the exchanges had just opened it up. So both the BSC and the NSC had opened it up to the retail public. I think looking back, obviously, there's always an element of luck. But those were relatively smooth times and
00:18:44
Speaker
The good thing for us with upstocks, back then upstocks was known as RKSV. The good thing for RKSV was that we had this.
00:18:57
Speaker
Yeah. So RK is basically my initials and my brother's initials. His name is Ravi. So Raghu Kumar, Ravi Kumar. And then the third co-founder is Shrini Vishwanath, RKSV. So one good thing we had going for us was that the prop desk was doing very well. And so the retail
00:19:17
Speaker
offering, which we launched in 2012, we didn't have to get so caught up on being profitable in terms of just the retail offering because we had the prop desk, which was bankrolling a lot of the company's operations. And I was essentially responsible for the prop desk. So that was like my, on a given day, I would say 90% of my work went towards the prop desk and 10% went into operations of the company.
00:19:43
Speaker
Okay. This was only your own money that they're trading on, or did you also take money from clients and trading for them also? No. The evolution was from 2006 through 2008. It was just our collective money, my and my brothers.
00:20:04
Speaker
And then we took that money, we went to India, we obtained a brokerage license and everything basically became company money. And then within the company, we had the retail division and we had the prop division, but it was still one company. And what happened was when we raised external funding,
00:20:21
Speaker
That's when we shut down the prop book because now you don't want to co-mingle different things. Basically you want to avoid what SPF was doing. So we had to foresight. You don't want to co-mingle investor funds and activities that are not true to the core business or the core functions of the company. The core functions of up stocks is it's a retail stock brokerage. The prop desk was still making money when we raised funding, but we shut it down. That was in 2016.
00:20:49
Speaker
Okay. You got a brokerage license in 2008 only? Why did you need a brokerage license? Because you wanted to trade it initially, right? Yeah. So the reason we obtained a brokerage license was for two different reasons. Number one, we knew that we would need a brokerage license eventually because one thing we did want to do was set up shop as a retail stock brokerage because we had a very strong thesis that
00:21:16
Speaker
This was something that was going to do very well in India in terms of discount stock brokerage offering. But the second reason was when you trade through your own brokerage license, then you save on a lot of costs because otherwise you need to trade through another broker's license and they're going to charge a brokerage.
00:21:35
Speaker
So to avoid that, what we did is we obtained our own brokerage license and we basically did away with those unnecessary costs. And if you're doing something like arbitrage trading, you absolutely require your own brokerage license. Otherwise you're not going to make money. Interesting. But it's possible to do algorithmic trading or at least at that time, was it possible to do go trading through another broker? Were there platforms that allowed you to upload your algorithm and trade on it?
00:22:06
Speaker
Yeah, not like it is today. So now in 2022, you can basically code your own algorithm. You can very quickly open up a retail API brokerage or brokerage account and open up the API, code your own algorithm, and no one's going to ask any questions really. Back then, it was very difficult. You essentially had to get your algorithms approved by the exchange, right? For the most part, or you would need to ensure that
00:22:36
Speaker
you were abiding by certain risk management protocols. And we were doing it at the broker level. The retail public could not build their own algos. It basically wasn't open to the retail public, but that changed. So we were actually at the forefront of that. This is something one of my co-founders was very bullish on, which was essentially allowing users to build their own algos and trade off of them.
00:23:00
Speaker
Then other brokers followed suit. Now, most brokers in India have opened up their APIs and that's relatively seamless now. Okay. Tell me the retail journey. I understand the prop desk journey and prop desk for people who don't understand is basically your trading is called the prop desk. Tell me the retail journey.
00:23:21
Speaker
Yeah. So retail journey basically was, again, it's always like an evolution. The idea started because my brother basically was, while we were in Chicago, he was working for a company called Thinkorswim. And you may or may not have heard of Thinkorswim. Thinkorswim is now known as TD Ameritrade, but
00:23:45
Speaker
basically in the late 2000s and for the next 10 years, thinkorswim was the number one options trading brokerage and platform in the US. So all the hardcore traders would go to thinkorswim. And yet my brother had that forth side of knowing that something like a thinkorswim, maybe with more discounted pricing,
00:24:07
Speaker
But with a very good technology driven product offering could do well in India, right? So he basically had that vision, I guess he could say, of saying, hey, in the next, it might take some time, might take five years, might take 10 years, but
00:24:25
Speaker
these types of offerings will do well in the US or in India. And you had other stock brokerages, which were basically doing that in the US. You had Scottrade, you had E-Trade, obviously. You had other discount stock brokerages. This is obviously before Robinhood. And so the concept existed. And that was the idea. And then we moved to India. And one good thing that we did was we didn't rush
00:24:52
Speaker
into just launching something. We spent more than two years in India just sitting on the sidelines.
Retail Platform Launch and Pricing Strategy
00:25:01
Speaker
It also took us a long time to obtain our brokerage licenses. And one reason for that is because we're NRIs and we literally had to go through more hoops, which is fine. That's just how it is. But by the end of 2011 is when we decided, okay, let's do this. Because obviously by then, another brokerage had started.
00:25:21
Speaker
another discount stock brokerage and we saw what they were doing well and maybe some ways to compete with them and that's and we basically launched the retail offering in early 2012. You launched it as app stocks or dealers? As rksv and one decision we had to make back then was pricing right because
00:25:45
Speaker
Again, there was another brokerage which had launched a 20-dupe plan, which I'm sure you're aware of who that is. And because of them, we were like, okay, do we also launch a 20-dupe pricing plan or should we launch something? What is this 20-dupe pricing plan?
00:26:04
Speaker
Yeah. So 22 rupees is basically what all the discount stock workers charge now in India, right? So up stocks, zero. Like 20 rupees for what? For like per trade? Per order, per trade basically. Yeah. And either 20 rupees for that.
00:26:20
Speaker
Exactly. So whether you're trading equities, futures, options, which is a very revolutionary concept because before this concept existed, brokerage basically was very similar to how brokerage happens in the real estate markets, which is it's a percentage of the volume. But when you think about the cost of
00:26:41
Speaker
of doing that business from the business perspective, there is no increased cost because the order goes to the terminal and it doesn't matter whether it's one share or 10,000 shares, the same exact thing is happening. So it's just an archaic way of looking at things.
00:26:59
Speaker
So that got disrupted. So we had to disrupt another way. So what we launched was pretty unique actually. It was a monthly plan where you pay a fixed monthly fee and you can trade as much as you want. So we charged 1947
00:27:17
Speaker
idea being you're free to do as much trading as you want. And in tandem, we also had a per order plan as well. So users could come in and they could pick like the power traders would pick the 1947 plan.
00:27:32
Speaker
I think that's really important. Even for the listeners, I think you have to find something which almost becomes a no-brainer for the customer. So in our case, it was the power traders, people who were trading essentially more than 100 trades per month. That's the math. If you're doing more than 100 trades per month,
00:27:52
Speaker
then 1947. Yeah, it makes sense. And then oftentimes because of that, because you're in that plan, it gives you the liberty of experimenting new strategies and things like that. So that's what's one thing we did. And then we basically had a legacy product which... So essentially our product was a white label solution. It wasn't really
00:28:17
Speaker
something super innovative or anything. From an Indian vendor, there was an Indian vendor who offered something off the sales. Exactly. Right. So that vendor is called Omnisys and they're very well known within the trading community. So we were using a white label solution offered by Omnisys and most brokers back then were doing the same even now, right? A lot of brokers are using some form of Omnisys powered trading platforms and did a fantastic job, right?
00:28:46
Speaker
There's literally a white label solution. You would log in and you would see the RKSP logo, but then from a front-end perspective, there'd be no difference between us and like most other brokers, right? And so in that process, yeah. Take care of the pipes to the exchange and the compliance and all the rules and everything, you take care of it. Like it was a full stack solution.
00:29:09
Speaker
It was a full stack solution and they would offer different types of services. They would also offer back office support. They would handle the order execution, risk management, because what happens with trading is that the exchange has its own RMS.
00:29:27
Speaker
systems, risk management systems. But then the brokers are also tasked with having their own RMS systems. And if you're starting out, you don't have the capability of doing that yourself. And so you basically leverage that through the vendor, which is what we did. And basically around the time we raised our Series A is when we decided to essentially build our own offering. So that's when Upstock's Pro launched. And essentially a lot of the funds that we raised
00:29:57
Speaker
was used towards building the product out. What was your first fundraise like? When did you raise it? Was it a difficult raise? Was it a relatively easy raise? Yeah. First raise was in 2016. You've been running RKS3 for four years by now, the retail offering.
00:30:19
Speaker
The retail offering was running for about four years. What's the right metric to evaluate a brokerage by like trading volume or? Yeah, trading volume. You could look at number of users. You could look at probably those two metrics. What were those metrics for you when you did your first race?
00:30:38
Speaker
So around that time, I believe we're doing something like 100,000 hours per day. Yeah. So those numbers really start to scale up over time. One big reason for that success though, is basically the company's operations are super important, right?
00:30:54
Speaker
But when it comes to stock broking, trust is one of those things that is just paramount and trust takes time to build, right? You can't buy trust. You can try, but you're probably not going to do very well. So it took time. It took time for our users and the market to understand how the company was positioned and things like that. And then we went through the Series A and then using the funds from the Series A, we basically built out and we built it up StocksPro.
00:31:22
Speaker
I want to ask you a couple of questions at this point, like the pre-2016 part of it, and then we'll go from 2016 onwards. What was your go-to market? Like 100,000 orders a day means you must have had a lot of active users. How did you do that user acquisition? What channels work for you?
00:31:42
Speaker
Yeah. So one thing we implemented pretty early on was a very simple referral model where basically whenever anyone referred anybody, a certain percentage of the brokerage fees paid towards the broker would go to the refer. And that became like an inbuilt thing. Like
00:32:04
Speaker
No, for whatever volume that's generated. So let's say I refer you and then you start trading. Whenever you trade, whatever brokerage fees you're paying the company, a percentage of that goes to me.
00:32:20
Speaker
For life, for life. And then we would have different types of partner programs. So partners can include websites, affiliate websites, all different types of authorized persons or influencers, which came up later on. So anyone who has their own referral code and is doing this in a mass, mass way, you basically create a different type of incentive plan for them. And that's one aspect. You would share a percentage of revenue with them.
00:32:47
Speaker
Yes, exactly. You can also sometimes share account opening fees and things like that. And then one thing we did was we experimented a lot. So we actually experimented with paid ads. So for example, Google ads and things like that. We would actually experiment with all those things. And this is something
00:33:07
Speaker
some of our competitors did not do and we actually looked at that as an advantage because everything there comes down to the unit economics and basically recovering that cost of acquiring a customer. It's basically LTV, CSE, you do the math and then you look at the quality of that customer and then you basically just work backwards and
00:33:28
Speaker
you scale that activity if it works, right? So that's something we did. And then a large part of it was actually just word of mouth, right? Because what happens in these types of niche kind of spaces where a company is doing something and there aren't too many other companies doing that same activity is that the company itself starts developing a certain identity.
00:33:52
Speaker
right? So people looked at us a little differently than the way they looked at our competitors. Competitors had certain spokespeople speaking on their behalf and we had us, right? And these things mattered, right? Because people would see us in the news, in the media, and the company develops like
00:34:10
Speaker
like an identity, like a personality, right? You just feel that because whether it's they're seeing one of the co-founders on TV giving an interview or they're reading something about the company or the marketing, right? Let's say I'm sending an email blast.
00:34:26
Speaker
to all the users, they see the way the messaging is coming through and that builds that brand. Certain things come to mind when we think of Tesla. We think of Elon Musk or we think of the way, just the general feel that you have in a Tesla car. Similarly, Facebook, every company, Google, right? Google Apple is actually a good example. If you think of Apple,
00:34:48
Speaker
There's a certain feel that we have with Apple and then Google has this whole thing of, oh, we do good and we always stand by good, doing good. So similarly, these things matter. And one big thing that we always try to cultivate was knowing that voice and then doubling down on it and making sure that all the communication reflected that voice. And even now with rain, this is something that we're now starting to
00:35:14
Speaker
really think about actively. I'm sure we're going to talk about that later, especially in those early stages as you're about to launch a product, developing that voice and then cultivating it over time is really important. What are the components in the business of running a brokerage firm?
Operational Challenges and Innovations
00:35:30
Speaker
Like you spoke about risk management, back office. Can you just spend a minute on each of these, help me understand what they are?
00:35:37
Speaker
Yeah. So before I talk about that, one thing we had going for us was that we had three co-founders and it was never like one person doing everything, right? Sometimes that happens in other companies. So we were fortunate in that sense. So what I would focus on really for the most part was running the prop desk. But apart from that, you have customer support is something I basically
00:36:02
Speaker
spend a lot of time on thinking about and building that up from scratch, going from one agent to hundreds of agents, scaling it, making sure all the agents knew exactly what we stood for. At the same time, making sure that the deliverables were being met. It's very important, so customer service is there. In our case, it was a legacy product, but even there,
00:36:29
Speaker
were certain things that you can do with a white-label product to standard from the competition. Then you have just general risk management. A brokerage is basically dealing with regulators, obviously making sure that you're always compliant and abiding by the regulatory bodies and making sure you're not doing something you're not supposed to be doing. From a compliance standpoint, there's always new compliance
00:36:52
Speaker
issues being released, right? You have to make sure that so whether that means how you onboard a customer or whether you're verifying the customer, how are you verifying them? Because one issue that we faced before we launched IADHR was that it took a lot of time
00:37:10
Speaker
for customers to essentially open up an account. The old school way of opening up an account was that you would need to fill out almost like 20 to 30 pages of paper
00:37:23
Speaker
There's no online account opening form and then you would have to verify yourself and that required basically someone visiting you and verifying you in-person is literally called in-person verification IPV. And then a lot of things can go wrong in that whole process. And then we basically lobbied for allowing IPV to happen over the webcam. So actually
00:37:46
Speaker
RKSV was actually one of the first brokers to do that. And then eventually, I think around 2016-17, Eadhar kind of changed everything because now you can basically just verify yourself through your Eadhar. And then online account opening became much more simple. But yeah, compliance is a big thing. Just regulators. Because Sebi generally does an amazing job. They're actually probably, in my opinion, especially after you see everything's happened with FTX and all that.
00:38:10
Speaker
The regulators in India are probably second to none in the world, but that's a double-edged sword, right? Because now you're also dealing with a lot of regulations all the time. And sometimes you wouldn't know exactly what was actually like a regulation you had to actually abide by versus something which was perhaps being talked about, but not actually passed, right? Things like STT, right? STT was always a big issue and it still is an issue, right? Yeah, capital gain tax.
00:38:37
Speaker
STD. Exactly. Security transaction tax. So you have relatively high STT rates. It has a high STT rate, whether it's on a sell side equity transaction or an options trading. So all these things you're thinking about. So one thing you're doing as a business is you're trying to hire the right people who have experience in those aspects. So they become the experts and you lean on them. So especially with things like compliance and things like that. For the most part,
00:39:07
Speaker
me and the other two co-founders we were not compliance experts right but we basically would make sure that the head of compliance in the company knew exactly what to do for different types of situations. Yeah so other than that it's just like any other business really. And what is the back office here? The customer support is the back office or what's the back office of a road risk firm?
00:39:28
Speaker
No, so back office is basically the ability for the user to see all the trade reports and activity after the trade happens, right? So if I want to basically see my contract notes,
00:39:44
Speaker
which are issued by each exchange every day, how do I do that? If I want to get a detailed history of all my trades done, how do I do that? So one thing we did was we built our own back office systems, which were independent of some of these third party systems that existed. So yeah, so back office is a huge component of running a brokerage. Once you raised funds, then what did you do? Did you go about setting up a tech team to build your own product?
00:40:14
Speaker
Yeah. So this is basically 2016-17. So for me personally, this was the early signs of maybe I should think about doing something else eventually because
00:40:31
Speaker
I was never the kind of person who was super bullish on spending all day running a stock brokerage. It's not something which comes super intuitively to me. I was always the trader. So from 2017 onwards, yeah. You shut down trading as soon as you raise funds.
00:40:49
Speaker
Yeah, we shut it down, or we had to. It was a good decision to make, right? And yeah, one of the major things we did was we built out a tech team, right? So one of my co-founders, he basically led all the tech at Upstocks. So he was responsible for building a team. We basically moved everything in-house, right? We had all the developers report to the office and we built Upstocks Pro from scratch. And that was a fun exercise because one of the things that
00:41:16
Speaker
Upstocks had, which some of these other brokerages didn't have, was a very good web offering. So if you look at Upstocks Pro, essentially, you have the mobile offering and then you have the web offering. Nowadays, most of the activity is done on mobile, but one of the major USPs of Upstocks was the fact that we were able to build a really stunning web interface.
00:41:42
Speaker
Right. And so that actually came to a lot of power users who had, who were probably trading on their, this was like their day job to trade. So they would be trading on a web application instead of like trading on the side along with some other day job.
00:41:58
Speaker
Exactly. And there you are still limited because whenever you're doing something on the web versus downloading an EXE, the web offering is always going to be catching up. I'm not a tech expert here, but I know one of the challenges that we faced during those years was how do you actually get an authentic
00:42:18
Speaker
power user to trade on the web. Because they're so used to these legacy platforms, like we talked about Omnisys, these are downloadable exe files. These are programs that you're running super fast. I guess trading platform was also like a downloadable exe file. It was. Exactly. So one of the actual
00:42:45
Speaker
early frustrations that we had was we launched up stocks and yet a lot of our users were reluctant to leave the third party offering. And I remember it really frustrated one of my co-founders because here's what's going on. But that's the thing because
00:43:02
Speaker
these hardcore traders were so used to dealing with that. It's not, oh, because they don't know better. It's actually because they were getting a lot of things on that offering, which were not available on the web. So that's a trade-off we had to make over time.
00:43:18
Speaker
It's like Excel versus Google Sheets. Exactly. I spend a lot of time in Excel. That being said, over time, I have found myself to spend more and more time on Google Sheets. If I just do that math, if I'm on a desktop, it might be 50-50. Probably skewed towards Google Sheets. But if you ask me, let's say maybe
00:43:42
Speaker
three, four years ago, I think I was spending a lot more time on Excel because Google Sheets keeps getting better and better basically. And we get used to it. That's one of the challenges of launching a product that you think everything is going to do so well. But if you're trying to break a habit or change a habit, you can't predict that outcome, right? Because having that ability to really be empathetic and really put yourself in someone else's shoes is very difficult to do without a sort of bias creeping in.
00:44:10
Speaker
So your product differentiation as opposed to, and I guess there were two other major competitors you had by then would have been that you were focused on people who were trading as a full-time job. So you built your product according to that, like for power users. So, yeah. So one decision we made Akshay was in 2014, yeah, 2014, we stopped the monthly plan.
00:44:39
Speaker
and we only offered the paper trade plan, right? And interestingly, we charged 25 rupees. That was one of the most interesting decisions we've made because it's almost like game theory, right? If you charge the same, then there's a pro to that, but there's a con as well. The pro being you're not really giving a reason for someone to not pick you,
00:45:07
Speaker
the con is you're not really any different. If you charge more, then the pro obviously is slightly higher revenue. But even also from a positioning standpoint, sometimes when you price things a little higher, the perception is that something is better. And we also felt like we were better, right? In a certain way, it's almost like you're going to everyone and saying, hey, I can do this because I can and that's it, right? And another reason to price things higher was otherwise everything becomes a race to the bottom.
00:45:37
Speaker
And to avoid that, or maybe delay that, we charge 25 rupees, right? And it was called the dream plan, right? Even the naming, right? It wasn't just like a pricing plan, it's called the dream plan. Like this is the dream. And obviously one question we would get asked all the time is like, why would I pay 25 when competitors charging 20? But we had very good answers to that. What were those answers?
00:46:00
Speaker
Those answers are basically, we have a better product, we have better customer support, we have a better brand. And this is not a knock on any of the brokerage here. I'm just saying this is actually what we said. We would tell our clients because we believed it. We actually believed that our customer support was better. Because we had certain metrics like
00:46:20
Speaker
certain percentage of all calls were answered within a certain number of seconds. And we were very proud of certain things that we were doing very well. And so everyone bought into that. But in due time, you realize this is not going to really work because at some point in time, especially as
00:46:39
Speaker
companies graduate from startup to not being a startup anymore, then it's, wait, you're not a startup anymore. So you can't use that on me, right? I'm not going to feel sorry for you. I'm not going to, you're just another company. You're trying to take my money. What's really special about you? Nothing is really special about you. And so at a certain point in time, we made a 20 dupes and it's been 20 dupes since then.
00:47:00
Speaker
Yeah. Why did you kill the Netflix plans? The fixed plan we killed because it just, it was just unit economics. We were not really, I think, I'm trying to think about what the reason was. The major reason was probably just the fact that those users were not profitable for us from a business standpoint. Yeah, that address is happening.
00:47:21
Speaker
Now, what we did do was we grandfathered the existing guys in for, I want to say, for a good amount of time. It's not like we just stopped it. But as far as acquiring new customers, nothing that happened actually was from 2012 to 2016, a lot of other brokerages started. And many of them were offering monthly plans and things like that, price cheaper than 1947.
00:47:45
Speaker
So we were like, okay, at a certain point in time, it just becomes easier to have one pricing plan versus throwing two, three different options at the user. So that was a strategic decision that we took. What were the differentiations you built to stand apart from the competitors? When is the first customer service? You also told me about allowing users to upload their own algorithms and stuff like that.
00:48:12
Speaker
How does that work? You write an algorithm using Python or something and then you upload it?
Algo Trading and Market Growth in India
00:48:18
Speaker
Yeah, so definitely the retail API was one divisioning factor. One of the major things that we did was Iyadhar. Upstox was the first company in India to allow for Iyadhar, which really shaved off account opening times. Of course, other brokers followed suit, but that's one of the things that my Upstox co-founder was always super proud of, that the fact that Upstox was number one.
00:48:43
Speaker
So technology does solve a lot of those pain points. If you think about just over a span of a few years,
00:48:51
Speaker
requirement of filling out literally 30 pages of documents. And it's not like just a couple of signatures here and there. It's like almost like 40 lines, everything perfectly submitted. And also there, so you're asking me, what are the different operations that happen in a brokerage? One of the major things that we had was actually, it's called a maker checker, right? So you have one person checking all the, and then another person has to check.
00:49:19
Speaker
first person's work. So it's all manual work, but EADR changed everything because now you can basically just submit an account opening form online. So that's one way we could differentiate it ourselves. Yeah, the retail API was... Upstox was actually, I think, maybe the first or one of the first retail brokers to offer an API. So the idea there is that
00:49:44
Speaker
If you know how to code, then you should be able to build an algorithm which trades using a rules-based process. And then that algo should be able to trade the markets without any sort of third party kind of peeking in and be like, Hey, what's going on here? That's the basic idea.
00:50:04
Speaker
And one of the reasons this was allowed is because it was actually permissible by the exchanges and by SEBI. So certain rule changes came through. You didn't have to get Algos approved. And the reason you didn't have to get Algos approved was because the broker's API was approved.
00:50:21
Speaker
That was the game-changing element. Before, you had to build algos and then go to the exchange because there was no such thing as a retail API. But now, the actual broker's APIs, whether it's up stocks or even zero dollar or other brokers, the APIs themselves are
00:50:38
Speaker
approved by the exchange. So now the broker can offer that to the user and the user can do whatever they want to do. They can code in Python, C+, I'm not exactly sure what languages are supported. And now there's documentation for that. Even that's come a long way. When the API was first launched by upstocks,
00:50:56
Speaker
very few people were using it because it was cumbersome. They didn't really know how to use it. But then that's a bet that the company takes, right? The idea is over time, it'll become easier and easier because one of the major issues with algo trading is that things can go wrong very quickly, right?
00:51:12
Speaker
So you need to make sure that whatever systems you're using are like accurate and they're not going to fail on you. But nowadays you can basically, most brokers in India, including a lot of the full service brokers have actually opened up their APIs. So it's actually really cool. And I talk about this all the time. Sometimes in India, we tend to oftentimes compare to the US in terms of just investor participation rates or even like algo trading, right? If you were to ask the average
00:51:41
Speaker
albatrader in India and be like, hey, how do you think the albatrading community in India compares to the one in the US? Oftentimes they'll say, oh, in the US, it's way more advanced, because it's been around longer, which is true. It has been around longer, but there's actually a lot more retail traders building their own models in India than any country in the world.
00:52:05
Speaker
Wow. Amazing. And this is evidenced on Twitter, on Quora. You'll see a massive amount of traders excitedly talking about building algos. And so that's one of the reasons I actually run the Trading Rooms podcast is because there's so many traders doing this in India, and this does not exist in the US at the same level, at the retail level. Now, in the US, a lot of prop desks and hedge funds do use algos, obviously.
00:52:34
Speaker
But that's at the institutional level. So even at the broker level, I cannot build fully automated algorithms on Robinhood. I cannot do it even on E-Trade, I believe. Like, most of the brokers don't even... So it's really interesting how India is really ahead of the curve over there. Amazing. Okay. I was not aware of this. So people don't... Were you around when the Tiger Global Route happened? 2019?
00:52:57
Speaker
Yeah. So that's like right around that time where basically I had started stepping down from the company's operations, but I was involved. And basically there, the idea was the company was growing very quickly and Tiger was also very involved in the Indian space and they decided to double down on the management, on the company's vision. And it's really the India thesis, the fact that even now,
00:53:25
Speaker
less than 4% of the population has a DMAT account. When you just think about that, it's just mind boggling.
00:53:37
Speaker
Yeah. So in the US it's closer to 40%. Now that's biased because you have a lot of people putting their money into 401ks where they're getting exposure to stocks, right? But even if you discount that, it's still like probably up to between a five to 10X difference. Easy. So a big reason for that is just awareness plus
00:54:03
Speaker
it's not just awareness because awareness is a very lazy term. It's also the actual perception of the markets, seeing things for how they actually are. And so that's changing now in India. People are becoming more and more aware of the fact that stock markets exist and they're getting exposed to it at a younger, younger age. I was exposed to stocks in high school. So I had a teacher
00:54:30
Speaker
who literally, I share this story all the time, she was a microeconomics teacher. This was my sophomore year in high school. On the first day of class, grade 10. So I was 15 years old. On the first day of class, she asks everyone to build a portfolio of stocks.
00:54:53
Speaker
a mock portfolio with the idea being the student with the best performing portfolio at the end of the year gets an A in the class. So everyone pick portfolios consisting of stocks like whatever, Apple, IBM, Microsoft, all the usual suspects.
00:55:09
Speaker
I knew about penny stocks because my brother had traded penny stocks when he was in high school. So I asked the teacher, hey, can I build a portfolio of penny stocks? And she's, sure, why not? And I did that. And of course penny stocks, they can go either way. They're very volatile. But the idea is you have to come in first place to win, right? Otherwise there's nothing to lose. And I ended up winning the competition. So basically that was my introduction to stocks. And that happened in high school.
00:55:38
Speaker
right? So people get introduced to stocks at a younger age. That's also changing now in India. And with trading, that's one of the pain points we're trying to solve with that as well. We hope you enjoyed listening to part one of this two-part episode. Just search for founder thesis on any audio streaming app for part two of this amazing conversation.