How to succeed again and again in a world of Failure – GoIBIBO’s Ashish Kashyap’s Midas Touch with Start-ups
Succeeding again and again in the world of startups – is the key theme of this episode. People who are able to do this as known to have the Midas Touch. A name that is mentioned when one talks of Greek mythology is King Midas who is remembered for his ability to turn everything he touched into gold. King Midas’s gift or some may call it to curse, came to be called the golden touch, or the Midas touch. The start-up sphere has seen its fair share of entrepreneurs with the infamous Midas Touch.
The ability to build and scale a start-up is a huge challenge. When it comes to running a business, about 80% make it through their first year. This percentage tends to gradually reduce as the years go by. Only 70% survive their second year, and by the tenth year, only about 30% remain in business. Over the years many entrepreneurs have carried out the daunting task of scaling multiple times!
A few examples of entrepreneurs with this start-up Midas touch include Elon Musk with Tesla, SpaceX, The Boring Company, Neuralink, and OpenAI.
Vaitheeswaran K – widely known as the father of India’s e-commerce business with Fabmart.com (later rebranded Indiaplaza.com) and “Again” Drinks.
One such entrepreneur, in this list of entrepreneurs with the Midas touch is Ashish Kashyap, who has been succeeding again and again in the world of startups.
Ashish Kashyap’s Dream Resume
The world of start-ups is fraught with failure. It is estimated that only 1% of start-ups succeed which means millions of start-ups fail. Yet, Ashish Kashyap’s story is an interesting one. From being Google India’s first Country Head to growing and selling GoIbibo for a whopping $2 Billion, making it India’s 2nd largest startup exit, Ashish’s resume in the world of start-ups reads like a dream resume.
But here, to build INDwealth, he has again teamed up with Amrita Sirohia which has already notched up several early successes. Ashish knows a lot of secrets about building and scaling startups.
This freewheeling episode includes everything that he has done and how he succeeds again and again in a world of failure. Listen to Ashish from GoIBIBO talk about his start-up Midas touch and how he has been succeeding again and again in the world of startups.
Here are some excerpts from the Episode:
When The Internet Changed.
So that’s what we did with travel as a category. And of course, the world changed after ISIS two times internet the world change GDSs came in Amadeus, Galileo narrative etc. And I think times internet tried to move in a domestic system just like MakeMyTrip or IBIBO. It was not able to leapfrog to that, but that was one of the reasons, you know. We built which was really really amazingly successful. There was no concept of negative unit economic spiral. So there was revenue made on every advocate.Ashish Kashyap 10:02
How Ashish and Amrita Came Together.
So basically, Ashish was one of my clients at HSBC. So most of my career spent spent, like 15 years with the bank. And when he monetized with, with MakeMyTrip, that’s when he’s started discussing the problems that were there in the wealth management space, and how advisory was not really to the true sense how it should be, and how ultra HNIs and HNIs are really struggling. And he’s like, you’ve already been an expert in figuring out the broken pieces in any industry or in any market space.
So that is when we started discussing of bringing INDmoney. And that’s when, in fact, I went to some of my other UHNI and HNI clients to ask them that if we created something like this, and they were all unanimously of the view that this is the need of the hour. So what INDmoney and INDwealth today’s doing is being really appreciated. And I think we created the product that’s really required in the market.Amrita Sirohia 15:03
Key Advice from Ashish for Entrepreneurs.
But long story short, I think the word I would like to use it, it’s quite a lot to do with resonance and thinking thick skin and being being added and not being stupid, right? Okay. If you’re failing, then cut your losses and just fail, right and celebrate that failure. Right, learn from that failure, and then move to the next move to the next right. And there will be lots of there’ll be some large failures. There’ll be many, many, many, many, many failures, right during the journey.Ashish Kashyap 35:30
Watch On Youtube:
Ashish on The Key Role of Machine Learning.
So, machine learning plays a very important role here to ensure that it is intersecting your risk with the learning it’s having for you about you and also the learning that it is having from the markets. Of course, our aim is not to say buy this stock in tomorrow will go up. That’s that’s just that data is not enough for anyone to do that right. But over longer periods, our aim is to ensure that we allocate you properly because that that itself is correctly completely incorrect.Ashish Kashyap 59:28
Getting Advisory at Scale.
Even then, I think the kind of service that you know, blue category or gold categories getting today, right, that is something that is only available to the ultra HNI, you know, the entire family office service.Amrita Sirohia 01:18:39
Ashish on What it Takes to Build a Great Team
And building a team just doesn’t mean hiring, right? building a team means bringing them on board, onboarding them, getting them to believe naturally believe, without indoctrination, naturally believe the core problem with the company solving the product and services, which the company is giving is really solving a core issue, getting them to participate, getting them to get that first small win and participate in impact creation, that cycle, right. So to go through that cycle, right? It’s not just about hiring, but it’s hiring, building the team, getting them passionate about what they do, getting them excited. That’s that’s a task, right? I mean, it’s, it’s not a trivial thing.Ashish Kashyap 01:22:50
Follow Ashish Kashyap on LinkedIn (@ashishkashyap)
Check out INDwealth.in
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system, ashish, consumers, product, building, day, called, company, happening, users, create, problem, market, travel, india, started, ml, fact, fund manager, advisory
Amrita, Krishna Jonnakadla, Ashish, Tania Jadhav
Krishna Jonnakadla 00:01
This is Maharajas of Scale, a podcast where we go behind the scenes and talk to founders who are demolishing the myths around building and scaling a big business in India. These are the stories that have shattered the assumptions around Indian consumers and of changing the game completely. I am Krishna Jonnakadla, serial entrepreneur, co founder of FLIT the fashion located in town and startup mentor, bringing you the stories. Good afternoon, everyone. Thursday afternoon, Sunday afternoon in Bangalore, and then Ashish and Amrita from INDwealth, an amazing company. I've been doing a lot of research about them. I think it's fascinating what they're working with. They are still you know, for some meaningful jargon. They are throwing AI and Ml for HnIs and that kind of stuff. But we'll get to the bottom of it. But I suspect that our session today is going to be very different from the ones that we've had in the past because we have to do justice to what Ashish has done from you know, his steimer times internet and being in Google's first country manager for India and then the GoIbibo group and then GoIbibo travel and the $2 billion exit with MakeMyTrip and then now Indwell, well I Ashish your entire resume, if I may call it that or career reads like a legendary one and a storied one and literally like a juggernaut. So take us take us through that a little bit. And from DPS Mathura to INSEAD looks like you check all the boxes.
Yeah, I mean, look, I saw Firstly, nothing, I let me be honest, nothing, nothing is deliberate out of that. It's all quite evolutionary.
Krishna Jonnakadla 01:41
That's very humble of you to say that you can't get to where you got to Ashish without being deliberate and then focused, isn't it? But I'm sorry to cut you, but go and go.
Yeah look. So you know, I come from a very humble middle class background. Okay. So definitely coming from a background, which is humble, you are definitely more driven. This is, you know, I kind of grew up in the country where the country was just kind of taking off. You know, liberalisation was just beginning to happen, foreign companies were coming in, you know, the world was changing the exposure, the country was getting connected internet was just happening. And all of this combination of exposure, and that desire to create an impact, you know, led me to do many experiments in my life in many aspects of that evolutionary journey that I talked about, which is what I think I mean, I think he hadn't been very deliberate. But listen, I want to go to a college, I want to do an MBA, by the way, after the after the college, I did not do an MBA to management, most of my further education happened only after several years of work. Okay, which is actually the right way to do it. To be honest. I don't know. So again, that was evolutionary, it was not like, Listen, I wanted to do something. And at that time, I said, I don't want to do further education. I remember, even fresh out of school, I got into Delhi College of Engineering, which now is called, I think, DTU, or the IIT, or something of that sort that time, it was called VCE. And I said, Listen, I don't want to do engineering. And here I am running businesses, which are based on computer science. So all says that it was quite evolutionary. During the journey, one very interesting thread across the journey is that I always liked creating building stuff. And I hated being a passenger, for example, you know, when I joined Google, for me, the high was, you know, setting up the flag in India for them. But what I hated is that as an overall scheme of things, I was a small little cog in the wheel, like a passenger sitting here in India, which was like contributing decimal point of revenue to the overall revenue, and not being able to really feel that I'm making a difference to the customers or to the community at large. Because as you know, you know, most companies like Google Facebook products are made out of Silicon Valley. So the common thread for me that, you know, took me through was it I want to do stuff where I can really impact people's lives, where I can really change people's lives. I can better people's lives, whether it is today's date, financial services, or was it travel earlier, or payments, it was all about creating impact, making a difference building stuff from scratch. So that's what got me going. And that that's what keeps me going every day. It's it's the drive to, you know, express by creating impact.
Krishna Jonnakadla 04:39
That's put very succinctly but let's dig in a little bit after DPS. Then you said you got into Delhi College of Engineering, and...
also I didn't do DC I did economics. That's what I'm saying.
Krishna Jonnakadla 04:50
Oh, okay. Okay.
So that's what I mean. I didn't I didn't go to the engineering line. We didn't...
Krishna Jonnakadla 04:54
Okay. Okay. Most
Technology entrepreneurs become they go into they do basically Computer science engineering or any other form of engineering?
Krishna Jonnakadla 05:03
Come from a background of engineering right? And here I am running so many.
Krishna Jonnakadla 05:08
So, so so so so I All I'm saying is that a lot of it was evolutionary during this journey.
Krishna Jonnakadla 05:15
For what I enjoy and what I didn't enjoy.
Krishna Jonnakadla 05:18
So let's talk about that educational career a little bit. So did so Delhi School of Economics was it?
No, no Kirori Mal College.
Krishna Jonnakadla 05:26
Okay. And then. And then what was your first job?
So my first job was with a music channel called MTV.
Krishna Jonnakadla 05:35
That was my first job. And then my then off subsequently, I joined ti l, which is in Your time's right, I exited to do my further education. And I came back. And then after that, I joined Google.
Krishna Jonnakadla 05:51
So you were with MTV, around the same time, Mahesh Murthy was there?
No, no, this is after that. This is after that. This isn't at all for that.
Krishna Jonnakadla 05:59
Okay. And then times internet DVDs were still early days? I, I guess, Times given their size and given their media reach. They still have their hands everywhere. Was it the Was it the case back then as well?
Absolutely. So the so so the internet division was or is or was run by the by Vineet Jain. One of the promoters slash owners of the group, very, very passionate guy. And I got an opportunity to work very closely with him during that journey, and it's not well written about and well documented. During that journey, I worked very closely with a guy called rajasah. Honey, who's the founder of GSF. JSF is an accelerator. And it's very less written about what we actually back in 2001, when there was just really poor internet in the country, when there was actually mostly dial up and there was some bit of DSL stuff happening. We innovated by launching the first travel auctions in the country, we launched the first reverse price auctions, it's just not written about, it's just not documented anywhere, I have attached some documents, which I will one day come bring together and put together and put it but these were the early innovations which we which we thought that you know, we are absolutely up to a very, very exciting game. It's just that I, during that journey, having created that I I kind of temporarily exited for education, and then came back. But by the time I came back that foreign education gave me this global exposure globally, what's happening. And I said, Look, one needs to learn much more. And I then exited and joined Google. And of course, joining Google was exceptional experience, because you get interviewed by like 18 people over over a week in Mountain View, that itself was an amazing experience, and quite a daunting experience. But that's how the whole journey happened till till till Google.
Krishna Jonnakadla 07:56
Very interesting. So anything you want to elaborate on the internet time when this reverse auction in travel? Was that a precursor to what you eventually did? While the GoIbibo was not really reverse auction, but you're not the first person to try reverse auction. It's a fascinating concept. I guess the at scale, the closest that we've seen is really Groupon. And the funny thing is, a lot of people don't know that. Bill Gates co founder, Paul Allen, after he became a billionaire, he actually tried his hand at a reverse auction company. And then they didn't go anywhere. But that was way back in 1999, which was still early days for internet. So was that a precursor?
Also, So first is let me so travel was an auction platform, not a reverse auction. Okay, classic English Dutch auction. I mean, I, this is the time when I really started understanding the concepts of dynamic pricing and inventory. But the travel auction was if you look at if you go back, we in fact, law to travel auction system, and typically became the largest domain tracking system for travel, make my trip didn't even at that time do domestic travel used to do travel for enterprise. And the concept was that we those days, there was no concept of GDS and middle booking systems, right. So we created a pseudo yield management pricing engine for us. There used to be these airlines called Sahara the Sahara, Indian Airlines, right. Indian Airlines was separate from Yeah, so Sahara, Indian Airlines and jack. So we created these systems, which enable consumers to bid for a group of seats, and come eat for those seats. And I remember day one, when we launched, we sold 10 tickets. And in 10 days, we were selling every day, almost 2000 tickets a day. Okay, during that time when the denominator which is the internet penetration is very weak. So it gave a massive, massive, in fact, that reminds me I must collect that documentation because it was really indigenous for We did I mean, there was no parallel of that. So that's what we did with travel as a category. And of course, the world changed after ISIS two times internet the world change GDSs came in Amadeus, Galileo narrative, etc, etc. And I think times internet tried to move in a domestic system just like make my trip or avivo, it was not able to leapfrog to that, but that was one of the reasons, you know, we built which was really really amazingly successful. And there was no concept of negative unit economic spiral. So there was revenue made on every advocate. So I'm very understand negative unit economics at all. That was something quite new to me also in the mid in the in the madness of 2011 2012. The other system that we built was a very interesting system, it was a shop online shopping system, but not with a fixed price with a with a reverse auction system. So it the categories were largely consumer durables, commoditized. consumer durables, and those days mobiles were also largely commoditize. The concept was very simple. It was called tell your price level. I, it was motivated, because I was doing travel. So I was obviously motivated with Priceline, name your price. So obviously, I had understood what Priceline does. But it was called Taylor price. So consumers were supposed to say so we would say Hey, hey, here's a here's an air conditioner, wanna often air conditioner in the market, this condition sells for 22,000 rupees air conditioner used to be very expensive product. So he has a television, flat screen television, in the market, this product is for 24,000 you tell your price. Okay, so you tell your price. And we would say that if is whatever price you've told, we will basically if we price match, we ship the product to you, the consumers have to authenticate the credit cards just like the way you have to do it on a Netflix of so those days Indian entities are allowed to authenticate and pre authenticate and charge in India now it's a pretty big challenge because of 3D secure. So the way it used to work is that consumers would bid for that and the consumers would tell their price for that air conditioners, the manufacturers like LG, Samsung, Whirlpool, they would bid for that demand. And it was just completely amazing. I mean, the amount of traction we got with you know the the the system becoming there was no mobile apps those days there was no mobile web it was all desktop web right. And typically what I mean for me the big learning was you give value to the consumers they will come to the system somehow or the other right they will come you give value give you basically make something valuable they will figure out again that became so that was like our our take at how ecommerce should be done for consumer products and consumer durables. I wonder why no one did that again. I have no answer. Because I never kind of dwelve into it. But again, something which was super interesting. I remember convincing LG and Samsung so when I went to convince them so I didn't say listen come and do a deal with me give me x commission guess what I told them. So when to LG, I met and there's a guy called solid couple. I don't know if you know him. He is a pretty senior guy in the consumer electronics industry. He was previously the CEO of DSTV he's also I shouldn't say I should say this board has also right so I went and met Salyl Kapoor. And I didn't say I want to do a deal with you and I didn't go and educate him what we want to do. I told him listen, we want to buy 5000 air conditioners Tell me what price will you give me so he gave me a price then I did the same thing with Samsung. The same thing with Whirlpool Same thing with Electrolux, I don't know if Electrolux is alive. So same thing with these 1020 consumer durable companies and I realized that these are all there are a lot of inefficiencies and I started challenging them then I started telling them okay what to buy when you customize the product, because all of these guys had a dealer conflict issue give me a give me a unique model. And I think Amazon basics does that now very well Okay, give me a unique model, give me a unique serial number unique model make some change and will you give me a unique value proposition. So they agreed and then back to back I went and collected demand. So I never was the man that collected demand when I started giving giving them purchase orders till the till today till then they didn't know what the scheme is. I'm not getting them to I didn't give them a system where they should start bidding only when I've done two or three cycles and they said you're either Bob Mota buyer and that I started to then ask them this and now you bid for these customers. So it was it was it was pretty massive. I mean, what I learned the two sided system how this gets orchestrated. away, exciting.
Krishna Jonnakadla 14:52
Interesting. Let's get to know Amrita a little bit, as well. Amritha, tell us, tell us a little bit about yourself and how you came to be where you are right now?
So basically, Ashish was one of my clients at HSBC. So most of my career spent spent, like 15 years with the bank. And when he monetized with, with MakeMyTrip, that's when he's started discussing the problems that were there in the wealth management space, and how advisory was not really to the true sense how it should be, and how ultra HNIs and HNIs are really struggling. And he's like, you've already been an expert in figuring out the broken pieces in any industry or in any market space. So that is when we started discussing of bringing INDmoney. And that's when, in fact, I went to some of my other UHNI and HNI clients to ask them that if we created something like this, and they were all unanimously of the view that this is the need of the hour. So what INDmoney and INDwealth today's doing is being really appreciated. And I think we created the product that's really required in the market.
Krishna Jonnakadla 16:08
So the perfect market research situation where so was it always your brainchild? This is something that you had up your in your mind INDwealth.
Well, no. So I think essentially, it again, comes from a problem statement, right? The problem statement of, you know, the broken pieces in the financial services sector, the fact that there is so much hidden, and so much of losses being incurred by consumers and investors in India, you know, the fact that things people's financial lives are broken and strewn away everywhere. So it was a huge problem for me, people around me. And with that problem statement, when I started discussing with Amrita, I said Amrita, Listen, why are the banks not being able to solve it? Right? Why can't you solve it? Or why is why is the private banking non banking setup, also not solving it? What is the reason? And I figured why, you know, there are a lot of Trade Commission's from these kind of investment products, etc. And I realized that this is not an Excel problem. This is a data science problem, because there is so much data, so much of data feeds, consumers, portfolios, market situations, all of that needs to get intersected. And I realized that this is really the need of the hour to build a personal finance app, which will bring people's finances in a single app, and help them to manage day to day their money and do it transparently so that people can create better value for themselves. And that's how I started to work with Amrita and the team and start building it.
Yeah, I think there were multiple issues, right, like transparency being one of the key, like, even today, a lot of customers don't even know the kind of expenses that they are paying for any holdings that they have with the banks need bonds, mutual funds. vmss, if so, that was something that that was, that was a really. And the other thing is the advisory was mostly driven by the Commission's that our distributors getting so while they would call it advisory to say that we are advising you, but and you know, we're all guilty as bankers to do that. Like invariably, if there is a fanboy, who will come and say I'll give you this much more. If you distribute, it's easy for me to go and prove it to a client that this is the right thing to do. Right. But if the moment you become commission free, then your motives are gone. And you're actually doing the right thing and providing the right advice. And that is what I am the money is trying to change.
Krishna Jonnakadla 18:38
So it I'll come to the Ind angle a little bit. It's very fascinating. I'm sure we can talk hours on end about it. We can keep talking about what Mohnish Pabrai says what Warren Buffett says what Charlie Munger says, the transparency of transparency into the fee based system, the missile misalignment of incentives, the lack of data, and given the size of the financial services industry, it is a behemoth of a problem that you've actually taken on, right. But Ashish, I want to you know, go back to the post Google days a little bit. Okay, I will come to the end. Because I I know that you both have a lot to contribute on the end wealth and the end money story. So without before we get sidetracked with, you know, some of your past ventures or other before we I don't want that to be a sidetrack. Let's complete that part. And, you know, Morgan housel, has written this incredible book called The Psychology of money, right? And, and in that book, he discusses how Charlie Munger once said, There is actually a third partner of Warren Buffett and Charlie Munger, who's actually not that widely known at all. And for a certain period of time, he was Warren Buffett's In fact, annual compound growth rate is 22%. And I think Jim Simmons, there is another person who is compounded annual growth rate over a 20 2020 odd period. 20 year old period is actually 66%. Right? But the fact what actually makes Warren Buffett and Berkshire Hathaway's triq so formidable Is that it? It's at around 22% for four to five decades, right? And then Charlie Munger actually has said this, and I'm using this not in the context of investment, but in the context of, you know, the time when Google compounding is a less understood science. And the most important thing that you need to do with compounding is not actually disturb it. Right. So with that, I know when you were at Google, you said, you felt like you were a cog in the wheel. And I know that feeling, you know, I've constantly in my life, I've chased positions in things where I felt I could make an impact if I was one of 150,000 people, no matter what, how senior the position is, unless and until I'm at the top of the pyramid, my ability to make an impact is really limited, right? But having seen what has today become what Google has become today, and not just globally, but even in India? Do you regret that? You left it at a time and maybe you should have stuck around? And maybe the compounding effect that Charlie Munger refers to with investments would have happened here as well?
No, I don't think so. I mean, I I'm so glad that I took that decision. Because I think the the trail of building on your own, and being able to create systems, platforms, applications, and impacting the lives of people around you, that feeling is absolutely different level altogether. I'm not even talking economics out here. Right. Simple. I you know, I think it's an intangible heart. Right. And, you know, I'm glad that I took that decision at the right time. So then from you see, everything is about timing, right? Sure. Everything, everything is about timing, you can't obviously focus us too much of timing. But if I now do a back test on that timing, I it was a it was the right, it was the best call I took, right, I feel so excited to having created such ubiquitous products, like why people pay you and even we acquired red bars. So really, I mean, there are very few people who have get this opportunity to build such ubiquitous brands. It's very hard to build consumer businesses. And, you know, I feel very glad to have take that decision.
Krishna Jonnakadla 22:39
True. True. I'll come to that. The the fact that you've built so many consumer brands, and it's no ordinary feat that you have done that right. So then from Google on to GoIbibo group, which was essentially an incubator way back way back at that time, correct?
Krishna Jonnakadla 22:56
And then how did the evolution to that being a travel portal happen?
Yeah. So essentially, when I saw so when I, when I decided to exit Google, my decision was to start an incubator. Because, you know, during, during my journey, I was always involved in doing multiple products, multiple, multiple categories, multiple products. And one of the things that I saw when I was in the valley, there is so much of innovation and so much of production happening. So many people would sit in cafes and somebody is talking about an idea around making direct to consumer coffee platform, somebody is talking about, you know, health medicines platform, somebody saying let me solve this, this problem of assistance. So so many people are solving so many problems. And if you see back in 2007. In India, most of the most of the most of the Creator economy, which is let's say developers were talking about, Oh, can I get into Infosys? Can I get into TCS so that was a I mean, they they were just no startups in India. At that time. if let's say you wanted to put 100 crore rupees in India, you just had Shadi and Bharat matrimony.com, you had rediff.com. Okay. And you had naukri.com you didn't have any other startups at that time. Right? There was just so so what I at that time decided that let's let's I will create startups, when there are no startups, I'll create startups and that's why the team of incubator and I got the incubation money from naspers that time, and that was the idea. But while building that incubator, I built several little applications. goibibo was one another experiment which took off and it took off beautifully because of many reasons we can discuss as a long story, separate story. And basically we decided to transform the company from an incubator to a proper company, and that we did in 2009 and around 2009 and 2010. And then when I did that I was facing a lot of problems. And it's deja vu because I'm facing the same problems now, which is with payments. So I started wiring up direct integrations with banks to solve the payment problem. And hence built IBibo pay which later we rebranded as PayYou which we started giving it to third party merchants. So that's how the evolution of GoIbibo and PayYou happen. And that's how the whole transformation happened.
Krishna Jonnakadla 25:30
Incredible. So now having exited GoIbibo in 2017. And now with the what's happening with COVID? Again, do you think in hindsight, looking at it, that it was an incredible decision and great timing, although it's not really back to back that COVID? Not exactly happened? Back to back. But do you think that was? That was a well timed decision as well?
Yeah, look, I mean, I think so after, you know, after the exit, which was quite a celebrated exit, and quite a celebrated transaction in the market it you know, for that time, it was the largest transaction. For today, it's the second largest consumer tech transaction, the first one being Flipkart and Walmart. This is the second largest so far. Which is, which, of course, is a very defining moment, because it communicates to the world that there's value to be created in a way. So having exited. And Firstly, the choice of exit, absolutely, I really happy that I took that decision. Because for me, feeling good. And you know, feeling excited about trading impact and building is really important. That's what I do. And that's what I want to do in the future. And I think from a timing perspective, beautiful, because, as I mean COVID has, if at all accelerated our growth. COVID, if at all has actually really significantly helped us to scale our platform without investing because people really want at this stage, personal finance platforms to digitize their financial life. They want digital execution platforms. So I think there is a huge need for people to have their virtual digital family offices in the cloud. So I think COVID has been a pretty interesting trigger for us.
Krishna Jonnakadla 27:16
I meant COVID in the context of travel, what the wreckage they're travel industry.
Okay, okay, okay, no, so Okay, so. So my view is that that's kind of a short lived phenomenon. Because in any case, if you look at it, the use case for travel apps, like goibibo is leisure. and small businesses, the business use cases, in any case, still not moved so fast on to online, or pure play online. So I think the leisure, travel and all of that is going to be back very soon, right? So I saw a lot of people said, Wow, great timing that you exited, right? Because these travel is kind of devastated. But you look @booking.com right, it's back the market cap of booking.com is back with a vengeance, right? MakeMyTrips, stock prices, pulling back, for example. You know, I'm personally going to go up this new year's amortize going also for New Year's somewhere. So we are traveling back, right. So that's just beginning to happen. So I just feel it's kind of shortly. And they would be, you know, the use case of travel for you to go back home for you to do leisure travel is going to be back there's going to be impact for I think, for a period for business travel, for sure. But then the travel companies will also need to reorient themselves and see how do they provide more services to certain consumers, etc, etc.
And I think they'll be made up because of the vengeance next year.
I think people are going to travel a lot more.
Krishna Jonnakadla 28:51
So revenge travel.
Yes. Yeah. But I think but having said that, there would be impact on business travel. Right. You know, I think five stars will be impacted. The use case of conferences and meetings, that's going to be hits. Definitely. And I think it's very clear that now we all realize that something which we can do like this, why do we need to travel so business travel will have an impact.
Yeah, the world has changed.
That world has changed and that that's not coming back in my view.
Krishna Jonnakadla 29:21
So for a humble middle class boy, to go to Times internet, become the first country head of Google and then land 100 crore naspers fund to create an incubator. $2 billion and run it for some time. to $2 billion exit. What's the secret sauce? Ashish? It's not just evolution, there is some there is something. Is it about how you parlay yourself? Is it about how you make the right connections? Is it is it about knowing who to work with? Or is it if you just tell me it's all just about I was just at the right place at the right time. You know that Do I will not believe you for a second?
No, no, I so I won't say that. Right. So, you know, I would. So, you know, in general. So while so what you right now captured where the happy milestones is selected? It's a timeline. Yeah, sure is zero to, let's say 100 Yeah, chronology. Yeah. You have basically cherry picked? Yeah. Okay. So it will not take many, many, many, many milestones, which are horrible in that journey. Right. I'm all yours. Okay, so. So the issue is that, I think so good. So everybody will face bad days every day, right? So typically, like I would see, I would hear seven bad things worse, and three good things. And I would face nine bad things and only experience one really good thing. So I think we're missing a lot of in that, in that timeline. There are really, really, really bad periods. Right?
Krishna Jonnakadla 31:00
Where they talk about it talk about it.
Yeah, look, so no. So where do I start, right? Because the the milestones that you picked up are like six or seven, those will be like, 600 of them right in those in those 3000 days.
Krishna Jonnakadla 31:15
Inverted and actually destroy my hypothesis completely and say, Hey, you, you, you're glossing over all of these that happened and then give 10 of 10-10. Equally, you know, using the Newtonian law of reverse motion, destroy my hypothesis, you know, feel free to do it.
Yeah. Look, let me start with the last right. So firstly, the fact is that everybody, so if you look at the whole, let me start with the goibibo thing, right? So we, we did the we did the exit, but you do the exit? Because you are you don't you have many variables running around you, right? Sure. And this is the time you were like hands on winning, you know, you say that? Listen, I'm seizing the moment. It Right, I could actually typically do a reverse acquisition. Okay. But we didn't go through that because of circumstances. Right. So while it seems really it's, it's great, right? Obviously, the job of an entrepreneur is to give back returns to people, etc. All done. But if you ask me personally, it's an unfinished business, honestly, right. I mean, really, getting consumer brands to become umeko. To us liked and loved in a short span of time is really hard. And then you want to seize the moment, and you're about to seize the moment, but you change the direction. So, so while it sounds too rosy from the outside, people ask me, you know, for me, it's like, okay, it's an unfinished business. Right. So so that's one example I want to give you. So one, when during the when you say unfinished, unfinished business, I think we could have taken this to another crescendo right together. But that's, that's what I'm trying to say. It's not, you know, so do I feel like wow, that, you know, my job was done on citizen. Okay.
Krishna Jonnakadla 33:02
Right. So So then I'm, I'm thinking there, there were certain investors that wanted an out. And...
It's just circumstances, right, like the we had a service tax rates happening, lots of such issues, right. for, you know, that we had, which kind of got us into a circumstance which said that listen, and and, of course, certain investor alignment, and so on, and so forth. So it's complicated, right? There are multiple, multiple things at play, right? It's the game is very, very much like you're playing, and you don't have the time to see 1000 things right to run multiple things happening at the same time. And you need to make your choices, right. So. So that's one example I want to give you, right. The other other thing is that during the whole journey of Ibibo to GoIbibo, which is incubated we saw so much of exciting stuff, but at the end, we learned so much from failures. We saw so much of little, little, little little failures, which I think my learning from that is that you know, I think I'm thick skin. And being thick skin, I don't get scared of failure. I said, Okay, let's move on. Right, let's keep moving on. And some of it is documented, perhaps some of it is not even documented, but we tried many, many things, as part of that incubate not travel was one of many things which took off, it was really law of averages taking off in an industry, which I kind of understood really well. Personally passionate about. Right. So, so yeah, so that's the that's the, you know, that's the second part of the journey. You know, and I mean, again, there could be many such cases. So I so I think, at least people like me, we've seen more failures. We've seen more, we see more bad days, we see more failures, we see worse things and all kinds of situations simultaneously. So I think the secret is to be thick skin, and and just just just just be resonant. Right? You got to you got to just be Agilent you've got to be, you've got to be strong, strong stomach about it right. During during this journey.
I think that's correct very quickly. Yeah, I think something that like he'll he figured out gaps and equals correct quickly, which I think is not something that everybody can do,
Which is the I trade a process, right? And so you because you don't know right and at time you will look at data data, say something but intuition and you'll intersect data and intuition. But long story short, I think the word I would like to use it, it's quite a lot to do with resonance and thinking thick skin and being being added and not being stupid, right? Okay. If you're failing, then cut your losses and just fail, right and celebrate that failure. Right, learn from that failure, and then move to the next move to the next right. And there will be lots of there'll be some large failures. There'll be many, many, many, many, many failures, right during the journey.
Krishna Jonnakadla 35:53
So I, I've started, I'm i right now I'm doing my sixth startup. And I'm, I know that this is going to be the one and this is going to go places. And the funny thing is, in the five that I've done in the past, two have taken off and two, haven't I they haven't really been the kind of exhibits and there is a lot of unfinished business like you talked about. But the funny thing is, when I before I started this sixth one, I started doing something like a hacking of my mind. Right, I started telling myself what if what we are thinking is good is actually bad. And what we the things that we are actually perceiving as bad is really good in there is a very old Indian film called Dave does, which is Dilip Kumar. And so the original version is actually a Telugu version. And one of the lyrics of that when he is there is this character called power. All right, so Dilip Kumar is longing for borrow and one of the lyrics of that song is when he is pining for her, he's drunk, and then he's pining for her. He says, the essence of all the Vedas, and all the spiritual things is this, that you interpret difficulty as comfort the day you understand that equation, life is going to be awesome with you. Right? So what I've done over the last year or so, is everything that an entrepreneur thinks about saying, okay, cucina era, okay, this is awesome. And we tried this, this date, this, this isn't working. This is awesome. So I've started hacking my mind. And I've read resilience. I've heard a lot of entrepreneurs talk about resilience, you know, Adam Grant talks about resilience, Plan B, and stuff like that. The hidden side of it is, you're still thinking that that is that is something bad, and therefore you need to steel yourself for it. Right? And then what I've done is I've inverted it. And I'm trying, telling myself, no, no, no, don't even think about these as being bad. This actually means that this is good. When you're when everything is happening. And then there is hardly any things that are blowing back then you don't you're not being challenged, and therefore there's not much that you're learning. So I've sort of inverted that perhaps you're saying almost the same thing in a in a different language. But what do you know what I find fascinating, Ashish is the reverse auction platform, the group booking platform group bidding auction platform, and then go eyeballed and the law of averages, meaning you tried so many experiments at IBO group before travel took off, and then the pay you Everything looks like in your mind, it looks like it's evolutionary, and you created something for the moment when you had the need for it. But for me, creating this and and you you teach about user acquisition, organic versus paid and stuff like that. It just tells me that innately, you know, a bunch of things about how to create and grow businesses. And we'll come to now I think we'll make a segue into that. So if you could take a few moments and summarize that not a lot of people in India know that. Right. But when you spoke about the negative unit economics in the early 2010s, negative unit economics exists only in a state where you are flush with capital, where you can even incur that negative unit economics, right? When you're actually challenged for capital, there is no way you can even incur negative unit economics, because there's just no capital to incur the negative. So only when you're so excessively funded. Or maybe you know, the reasons it can be excessive or whatever you can dip into that capital funding and then realize that negative. So what this tells me is that you're someone with this understanding. And the beauty of what you're doing in my mind is that you've been there around the.com bubble, you've been there in the early 2000s and early 2010s. Your experience really spans and then you still continue, you still seem to be growing things. So what is it that you You know, that is so different? And how are you? How have you parlayed that into indwells? Because Indwell was what you raised your seed round in 2018. And you got operational in mid 2019, or maybe early 2019. And then you you blazed that trail, although as an outsider, the seed round has helped in your customer acquisition is what I would think. So if you could take those two separate topics and address that, that'd be great.
So So to understand the question, you want to understand, you are asking that how am I synthesizing my decade journey to build these things is that...
Krishna Jonnakadla 40:39
I what I have seen in what I have seen in India is there are a handful of entrepreneurs, not really more than a handful, that understand how to attract large users build large user basis, anybody can burn through a lot of capital and do that. And then there is that that is there is possibly not a lot of other than good connections, and then landing that kind of capital. There isn't too much intelligence involved there, right. But what you have done is phenomenal from those platforms to eyeball you have built user basis from the grounds up into millions of users, that that tells me that you understand the user psyche and the psychology of building user basis rather innately. What is it that you understand about that? And how have you? How are you parlaying that into what you're doing with INDwealth.
Sure. So look, so there are two spaces, right? One space whenever I think about this, so I like to put myself in the shoes of the customer, very first principles. I don't like to go into too much of deep theory. But first is like I put myself into the shoes of the customer. What is the pain with? Now there could be services, which are already there in the market 100 services like they were when we launched travel, there were hundreds of travel sites. But why did I launch travel site what because I as a customer was paying, my friends were paying, they would try to book and when they're checking out, they would get an unreliable experience, the flares phase would fluctuate, they won't get the ticket in their hands, it would just unreliable, a very, very unreliable system. It's just like an e commerce, they will not have e commerce sites before Flipkart. And Amazon, by the way, lots hundreds is just that when I would place an order in those ecommerce sites, those products would never deliver, they would come after 21 days, 30 days, 40 days, again, let's say when I would do cancel a ticket or cancel a product, I would get my refund after two months. So this whole transaction system in the country was broken for a long time. And when when we launched why vivo, we said listen, can we basically do couple of things, which can we decide what not to do, and but to do certain things to do them really well. So that these very big pain areas get solved. People love to make my trip team laughed at us. I know it, the Cleartrip team, everybody laughed at us Ek Aur Company launch karrae hai yeh log. And that was a very weird name called GoIbibo doesn't make any sense. So everybody laughed at us. But to what I said to myself and the team, listen, there is a pain, right? The search results do not load fast enough. Most of the people are in 2009 are still dialing up and calling up the these make my trips to the world to book the tickets. And we said that listen, we would like to only do online booking and we like to do it reliably. So that's the first thing that we did, which helped us to start beginning to get embraced by a few set of users. Same same problem statement with pay you right? Like we had a payment system, we were using a payment system, third party payment system, it had a failure rate of 60% 40%. We said we need to solve this problem. So in all of this, you know the consumer was put right at the center always right? How do we deliver a service which is better, more reliable? How do we deliver a better consumer experience? Right, essentially, how do we improve conversion rates? If you look at in matrix, how do we can improve success rates? So that was the that was the genesis of whatever we do and whatever we are doing now that listen, how do we basically in the in the current business? How do we ensure that consumers get zero commission investing? How do we ensure that the consumers are able to track all their money in a single place without doing any effort automatically, right? So just to deliver a consumer experience, which is disproportionately better than what they get otherwise? So that's the that's the first first principal part of it where I believe that me and the team needs to eat the dog food by doing it and eat it a lot. Right? Even if it's bad, and more you eat the dog food, the more service you make you better the service you make. Of course, in the journey, you have to decide what not to do. Like, for example, we did hundreds of things not to, like we had decided not to do television commercials as an example. On the other hand, we said we will build our own viral loops. So we launched something called bow contacts, we said, Can we make Archons? Can we basically create virality loops between the consumers? So that was the that was always the second part of the theme that I was building that listen, a lot of these systems are one sided, how do we a make them two sided? How do we connect supply and demand? And number number two? How do we create loops between consumers? So that was the other thinking. And again, we are in obviously, translating a lot of bad philosophy and thinking into the current startup also that how do we build those loops? How do we build virality and, and not just need to do normal AdWords or television ads, right? We don't want to do that kind of stuff to increase reach. Because doing all of that is very linear growth, but creating virality and viral loops, just as nonlinear, right? So suddenly, you wake up and you say, well, your registrations have increased by five times and your monthly active users have increased, because you build these viral loops are hard to orchestrate. So in general, what I'm seeing on the second one is this whole understanding of is very important as to how you orchestrate network effects between the two sides. And between consumers. And these are not that strong. They're not like an Instagram type of network effects, or Snapchat kind, they are weak. But building these network effects and loops always helps you to disproportionately deliver value to the consumers and grow. So to an example, today's date, we have a concept of customer acquisition cost. Where does that Costco take that cost goes to third party platforms like Google, Facebook, blah, blah, blah, can I can I move that half of the customer acquisition cost into building these viral loops? So marketing for me is not marketing, it's actually technology and product, essentially. So so that's been the common theme, essentially. Besides Of course, being like, you know, today's date, I personally service customers, I will personally go and, you know, talk to the talk to the customers Amrita talks, we talk to customers, everybody engineers to talk to the customers, that customer madness and obsession, that that that that has to be there, combined with this concept of paranoia, in a positive sense, that Listen, if you don't do this, then it's gonna be it's the heavens are gonna fall. Right. So so these are the things you know, I'm just thinking on the fly. I don't have all of this documented. But these are some of the things that I would typically practice to synthesize my learnings and then translate into whatever you do. Interesting. Have you made your big pot of gold yet? from any of the exits? I wouldn't say I mean, I think is a very, let's say that I'm comfortable.
Krishna Jonnakadla 47:54
Okay, so let's talk about the seed round for Indwell, for what you but before we talk about the seed round, we've had camps, you know, CAMS, right. computer age management systems.
Krishna Jonnakadla 48:07
For reasonably well informed investors. You know, they would know that cams has been doing a reasonably good job of providing a single snapshot of all of their investments. Is it great? I wouldn't possibly say so. Because I've used their services for more than a decade. And in a sea of no zero options. CAMS definitely does a decent job of providing that single window. But does it do what I end? Well, does, you know, I don't think close, but in the on the back of the heels of their successful IPO, right. So that just shows that there is a demand for things like that. So but from travel, to go on to this, and when you started into 2018 Robo advisory for instance, while you're not completely Robo advisory Robo advisory platform had taken off in the US and a lot of Indian firms were aping the same thing. Right. What was the context in which you theorize that something of this was it again a scratch your own age where you had a similar problem and therefore you decided to do INDwealth or what was the what was the hypothesis?
Yeah, it was it was basically problem statement right. It was a first principle problem. Mm hmm. Typically, let's say as a as a user, I had invested through multiple entities, multiple intermediaries, who are charging me a lot of money from the back end, I had multiple typically India has now for example, India now has two crore unique investors only. And and approximately out of that about 1.2 crore our mutual fund investors in about, or let's say half off half on which or they'll be an overlap, but let's say to grow unique investors, right. Most of the stock investors have two or three accounts. The market, nobody has one single exclusive account because typically the person will open an account with a discount broker, the person opens an account with the bank, like me had has four stock broking accounts at an average it's about a two to two and a half. Okay? So you have multiple stock broking accounts, then you also have your pension, a pension or EP f account. So you have all of these multiple accounts and expenses. So you have assets and liabilities. And, you know, I would I would have all of these guys like if and, and all come to me and say, listen, we'll solve this problem for you, we'll create a family office for you will do this. And I will be very excited. That'd be great, right? If you can track my financial life, it was very hard for me to do it on a spreadsheet, because I can't keep updating it. And so with that, I realized nobody solving it. at best. There were a lot of systems out there, which again, asked me to do and others said, How do we automate it? How do we completely automate it right? How we shouldn't need anyone to be doing data entry, unless it's real estate, and we don't have any solution. But for people's financial life, their expenses, their loans, their savings there deposits, we should just automate mutual funds, automate the thing. And so that was the first big problem that we started thinking. If we looked at a lot of companies across the world couldn't really find a single parallel, that there was something called maintain us, there was some similarities. There is, but then I also realized that I don't want to leave it to just saying that, okay, you organize your financial life, and it's done, then we want to also tell the users how can the user improve his financial life? Right, so how should you allocate At what time? What should you What should you so we were the first ones to actually launch in 2019. Last year, the whole concept of rebalancing, right switch from A to B, because we did our whole machine learning system does scoring etc, etc, which has been really valuable. As you you've seen that there has been so many defaults, which have happened in the market, powers engines started alerting users about the Franklin default six months before, and there's just a year one startup, right. And that was just based on very linear machine learning rules, very linear system. And lots of people saved hundreds of crores to execute. And that was, again, not just helping you organize your money, but also helping you take actions to save your money to grow your money. So all of these were like massive problems, which which will not serve. So this is this is a space where it's not that there are several players who's solving it, but may not be solving it well may not be executing. This is a space which is completely empty. Nobody was kind of solving it, unlike travel where there were many people solving, but not solving well enough. Hence that gave me a window to come in. So that's what that's what got me going. And that's what got me to I remember speaking to Amrita and say, listen, how will people trust us to put money with us, right? Because giving people cash back is very easy, or somebody transacting something or two 3000 rupees is very easy, but how does that happen? So a lot of psychological thinking, etc, etc. and and yeah, here we are, with a with a product, which is growing very fast.
Krishna Jonnakadla 53:20
So how is user growth been ever since you've launched?
So look, I mean, you obviously we launched between April and July last year, so the users was zero. And for me to compare is wrong. But all I can say is that from the pandemic, to now we our user base has grown by almost 18 to 20 times. So the growth has been quite overwhelming. Actually.
Krishna Jonnakadla 53:42
Any numbers you can share?
Not at this stage. But let's let's put it this way that. You know, we were just looking at this very interesting data under the finance category of iOS apps. And we're already now one of the top ranked apps. Despite being they're the newest players, but we are already one of the top iOS apps in the finance category, for example, which goes to show because if you look at ranking is done based on engagement and reach. So I heard of many of those robo advisors that you talk about, I think just about very close to pay tm money, which is a mass product, very different product. So we are like, in the finance, overall finance category ranked 3536 ppm is 34, something like that, but ahead of let's say, ad money, which is economic times, by the way, right? And much mass users, right. So that'll be at money ahead of at markets ahead of your Kansas application as an example. Right. So, so yeah, I think you've done fine for now, but and it's early days, but huge ambitions over the next few years.
Krishna Jonnakadla 54:52
Like I wanted to ask you this question about the Times group. I mean, I respect them. They're a terrific group. I think somewhere we need Jain possibly wanted to model times internet on the lines of Barry Diller dealers interactive GOP iaac, right. But outside of MX Player and you know, some of the recent ones, it's been a lot of average. And given the state of below average execution in India, and slightly above average execution just gives you the edge, it's sort of, it's sort of not a great set set of situation, or a great set of great situation to be in. Because we essentially want players to sort of blaze the trail really, really create awesome mesh products. And I want to call if we wanted to categorize a set of things saying White Glove products, I did that, like you talked about in my wife and I often discuss many times, for instance, a lot of budget hotels that exist, right. So the Tata Group has a budget hotel chain called ginger. And ginger has been there for quite some time, and they do business under those hotels are not fancy. But when you take the luxury hotels of the Taj group, they've been consistent. And when you go to the ginger as well, they've been consistent. Now they don't promise, but you get hot water, the room is clean, every switch works, the coffee kettle works, the television turns on the basics work. But when you see the rest of the landscape, it is always a fluctuating, it is always very up and down ish, isn't it? So in one room, something works, something else doesn't work, you have a bad experience today, you have a bad experience, good experience tomorrow. And if the employee or the manager at that point in time decided to take a personal interest, then you have a great outcome. And the standardization of and the lack of systems, or the presence of it doesn't seem to be creating outcomes at all right? So therefore, looks like you've learned or rather you bring that thinking saying no, I want some things, I want the output to be consistent. I want the customer to have a great experience every time and it has to be the same. Every time they do it. It shouldn't be up and down. And therefore you bring you brought all of that thinking to INDwealth. And you provide a great user experience, you provide one one window and one view of all the investments where does AI and Ml come in here? Talk Talk about that a little bit.
Now and also many, many areas, I can give you a few examples. So the first very important area where AI and Ml comes in is on people's allocation. So there is a there is so people's allocation, by the way, that's the crux so if you really look at it, a lot of Indians have been investing since the last eight years. And they typically run a si, right? It runs 100% equity, even though that person may be conservative. And then when there is a crisis or something goes bad, the person redeems. So if you look at many people, if you were to just look at the data, large data, and you would look at people who don't make money, the other is people don't make money in stocks. I mean, that's that's the reality, but they keep going back, they keep going back. So one of the areas where the default area where machine learning is used for us is to help people's risk score, which is driven by lots of data science, and to help people asset allocate. Because typically, we believe that asset allocation and risk scores are not static, stagnant, they are constantly changing over a longer period of time. And machine learning plays a very important role to folks as an example, let's say you have 100 rupees today or 1000 rupees today, and you are a aggressive person, a static model will tell you to put 80 rupees in equity and 20 rupees in debt, whereas our machine learning system will tell you 80 and 20 is your ideal we'll get to that at some point of time. But today, we don't want you to put 80 rupees in equity because of 1000s of 1000s of reasons right and hence to one thing you park 70 rupees actually in cash or cash equivalent, which will give you five 6% keep it ready put 10 rupees in equity as an example. So, machine learning plays a very important role here to ensure that it is intersecting your risk with the learning it's having for you about you and also the learning that it is having from the markets. Of course, our aim is not to say buy this stock in tomorrow will go up. That's that's just that data is not enough for anyone to do that right. But over longer periods, our aim is to ensure that we allocate you properly because that that itself is correctly completely incorrect. So that's one area. The second is idea is that we do a lot of index and fund scoring through machine learning. And that scoring is driven by how is the risk of a particular index or a fund or a product changing, which we call as a risk score? How is what is happening to the type of industries that that particular product is invested in? What is happening in what house? What is the volatility score, what is the momentum score, and what is the fund manager score. So, for example, if there is a mutual fund, which is managed by a fund manager, if that fund manager is spread thin, or if that fund manager exits that he will get a particular score and that system is learning all the time and balancing the scores. So, which is why we are able to help people to do the right kind of rebalancing. Right, so let's say if you are on a duration based fund, or if you are on a fund, which is not performing not just in terms of returns, but in terms of all the scores, the taking into account your exit loads and capital gains, it will switch you to adequate product. So that's the other area where we, you know, use machine learning. The third area is that which we are still kind of building is your entire financial plan, it will be done completely automatically without asking you anything. And that will be completely ml based, which which basically forecasts your future expenses and forecast your income based on your profile without asking you anything. By the way. I mean, one of the key learnings for us is don't ask people too many things, human being is lazy, we need to we need to give things on the platter to the users. So there are several such areas expenses, for example, expense categorization. So several such areas actually a lot of things that we do by default, like, like the way the our system is able to read PDFs at scale, whether it's whether it's a stock statement, mutual fund statement, etc, etc. It's all machine learning based, you know, so that because you can't do that, if it was not if it was just like an OCR based thing, it can't be done at scale. So I think a lot of stuff that we do is, you know, has has an ml intersected in it.
Krishna Jonnakadla 1:02:11
Interesting. So, you know, Nassim Nicholas Taleb talks about two concepts, which is the Black Swan and the anti fragile aspect of models, right? While he's now very skillfully and very rightly so extrapolated that a lot of things if you see in the Indian context of the last five years, we've had multiple, deliberate economic disruptions, right? These are not a natural outgrowth of, you know, like what happens in the US where you have a boom and bust cycle, purely because of the policies of the Fed and the US government, the manner in which, at some point in time Congress or Senate takes a decision that this today we decide that they decide that the American Dream is going to include Medicare for everybody, or 65. Right. Now, that creates a huge dent in the way markets are managed, it creates a whole new set of set of winners on the healthcare space and a whole host of other people. But in the in the Indian context, we've gone down the path of in some sense, not even creative destruction, in some sense, maybe destructive destruction, you know, with de monetization. And for me, GST, I think, is sort of a long term game, a long term game, I don't really see that as an economic disrupter, at some point in time. You need one version of these things. And then eventually, you know, our pretense that we are the largest growing economy in the world, and our foolhardy intervention in last year's budget, saying that, you know, let's just, you know, go these guys seem to be having a privileged life, so let's just go after them. And then this year is, you know, three month long lockdown. So these I personally call these deliberate economic disruptions, because it feels like a handful of people can know and what it has actually done is it has reversed You know, a lot of wealth creation at certain points in time the market is up again, as we speak today, it seems to be rescaling its peak back to what it was in Jan. 2020, early 2020. But in the process, if you look, look at a lot of fund manager, performance as well, these deliberate economic disruptions, in many cases, has wiped out 90-95% of fund managers performances, right. A lot of funds have seen their, you know, five year averages or even 10 year averages dwindled down into second, single digits. And we don't know what else what else is going to come out of the banking sector consolidation. Because when I see the number of NPS, even very smaller, small, tiny banks seem to be sitting On piles of NPS. So the system I don't think has gone through the worst shock of it yet, that's vile. All of these are deliberate shocks. I think the outgrowth of all the hubris that we had in the early 2010s, we are still yet to see that. Now, in that kind of a scenario, where there are a couple of potential Black Swan events that can happen. What can only can an AI or an ML Engine truly anticipate that it's commendable? What you were able to do with the Franklin, you know, crisis, but how do you model for these things? And because ultimately, it many times in Indian investing, it feels like it's the Wild West, right, the nada day passes. Before we see, for instance, a Ferrari, for example, the syntex tank come, you know, family has defaulted and 1000s of crores of loans. And then notwithstanding that they have such a wide franchise. Now, given so many management's are suspect, and given their economic disruptions, how does it feels like humans cannot fathom that this can happen, can AI ml make a difference? If so, is that something that you're building for?
Some of the stuff you wouldn't scan and would love to hear from Amrita? Also some of the stuff actually. So if you really look at it, there's a lot of focus on on people to start keep analyzing equity markets. But actually, what one misses is that one misses the debt side of the market, right? where companies are taking loans, or companies are being given loans, right. And again, right, and one of the things that we obsessively monitor, and we can't do it humanly, our data systems monitor is who's missing payments, right? Missing payments, and we're doing it really fast, ingesting that information, which company is missing the payment? Right? That information comes from multiple sources. I'm giving a little bit of secret sauce. But I mean, this can be done right? At the end of the day, it cannot be rocket science, what we are doing either. So we are actually monitoring a lot of besides the normal fundamentals, what is the key what is the expected how expensive the market growth, momentum, etc, etc, we looking at all of that. But the other thing that we're looking at more obsessively, which we feel at the end of the day is to protect people's money, right with destruction of money is worse, right? Is to see what are the probabilities of default by companies? What is the health? And what is the probability of default? That's what I emailed us. And the minute it breaches, that's the minute we obviously that impacts the equity that impacts that that impacts everything. And bigger, it is bigger the problem, right? So that's really what we really pay a lot of attention on very, very aggressively besides looking at, you know, what are the key technicals of every company, which everybody is doing and, you know, which has the promoter shareholding changing, how is the which mutual fund is selling and buying? So lots of those 1000s of signals we ingest, besides the oval, one of the things that we do very differently is we monitor every company and see that which company is beginning to behave badly, right? Because when when a company is about to do when when the company delays, there is a screw up. That's where so we got a we got a feature on our product called ind protect, it goes only to prime users, right? That's where the user sees red flag. Okay? Now, obviously, when we were newer, six months ago, people didn't believe us. Right? So we had to kind of send them alerts, etc. But now people are beginning to believe us. So I don't think AI and ml can predict Black Swans, right? As such, we can do something, but we can definitely figure out that the systems can definitely figure out that listen, at what point of time even an aggressive user needs to be conservative. For example, our systems will never ask you to get into dynamic duration debt ever right now or short or or or long term debt, right? Because of so much of volatility, right? We will our system will not ask you to for for that 1% extra to go to a single A rated by a single, A rated bond or a debt paper, right? For example. I don't know what the situation is. But if I'm a consumer, our system will also not ask you to go on and into equity right now. It will kind of ask you to just hang in tight. You know, things don't look good, right? That's what the system is saying. Like, hang tight, things don't look good, or they look flaky right now. So so let's let's park your money into safe places. So that you at least in line with inflation. And that's that's what is great about a system like ours because we monetize ourselves from users and not from funds, fund managers and train users, right?
Krishna Jonnakadla 1:09:51
Your incentives are not misaligned. Correct?
And see from where the industry is today, right. This is still a step forward. Right. So You said that there's so much happening, what can I will do, but at the end of the day data is a way stronger basis to take your decision on investments, then someone's gut feeling like you said, the hotel manager decides that the rooms will be all okay. And you're we're using data to bring in consistency in telling you what is cheaper, what is expensive. So depending on banks and pays, for example, right, and where the value of the stock of that bank is, I can still tell you whether it's cheap or expensive, right? And there is, there is a lot of such examples. So even though what we are doing might not be foolproof, but at least it's a big step forward to what is happening currently, in the market. Like when I was a banker, if a customer in this fund is not performing, should I buy or sell? Or what do I do? Should I sell? Or should I buy more? Right? I would typically go back, talk to the fund manager, understand a few more things, understand what the other guys are doing, and go back and tell him a decision. Right. But you're today I don't do the same right? I have a lot of data to back me to say that, listen, this is how it is these are the scoring this is these are the underlying and this is how the overall fee is and this is the fund manager people but it is not. So there is a lot more confidence in the solution, then and it was earlier.
Krishna Jonnakadla 1:11:22
Yeah, I was not obviously the by definition. A black swan is something we can't predict. So any system whether it is AI, or ml obviously cannot predict one a when the next Black Swan is going to be and what is it going to be about right? We tend to think that a black swan can only be an economic disruption event COVID it is an economic disrupter. But in in itself, it is not an economic disrupter, but it is actually a healthcare health crisis. Right. So we don't know if the next conflagration with China is going to be an economic disrupter. But what I was referring to was given the frequency with which they see these seem to be happening. Is there a certain degree of weightage that is given into the modeling? That is because even with corporate debt, you know, last year, we saw a collapse of the debt market, right, a lot of a rated company's debt was all suspect, and the complicit nature of fear and the rating agencies in terms of what had happened behind the scenes was coming out out into the light. And even today, impact of the infrastructure leasing and financial services crisis hasn't been completely failed in the country. Right. So Laxmi Vilas bank, which was recently acquired by DBS is at the long tail of the IMF s crisis. It is not even in the middle of it. And we haven't yet seen the mayhem that has unfolded. So I was speaking more about and funny thing is, you know, truth be told, I was an investor in Lakshmi Vilas bank, from the age I was 16. My mom gave it to me when I was a minor, and I I saw one lakh 32,000 rupees of share capital wiped out last week, because, you know, the RBI RBI and DBS decided that share capital will be written down to zero. That was, so that was there was a lot of speculative interest that was going on in the stock. So, your early warning systems...
Like Laxmi Vilas are engine, like six months ago, it would assign alerting, right, because I would be missing happening and all of that. So that's it. That's, that's actually, where ml is being used as probability, a default key, right? But the fact that even you can, if you are to pull data feeds, even you can figure out that which which, which are the funny actors in the country, right? And that's exactly what we do. We look at every company and see, which are the funny actors and then the ML system because we don't want to, we want that to be learning, right, essentially, right? And essentially, there's a high probability of default. And then when you get an alert, and then there's mayhem in our company, because then customers are calling. And then there's craziness which happens.
Yeah, because the most Indian debt investors, they are not there to trade in bonds, they want the capital safety, and they want these alerts way before the defaults happen. So if if the system can give them these on time, then it's...
Yeah, so so so and it's all connected, right? The bond market is connected. So it's all connected. So the point I was trying to say is that from our point of view, it's the key is that we want to monitor companies, they they could be times where they suddenly or some other kind of a shock comes out because of some huge aspect, which does not come into data feeds, for example, right. But definitely, I think we've seen over the last one and a half years that we've been quite I mean, like Vodafone, etc, right? I mean, it's been quite basic, but
we've got validation
of the model. We got the validation of the model. And yeah, I mean, the only thing is that listen, our engine will never, never give you 9% on dare try to say it take take conservative returns, but it's the Soviet election. education needs to be done Ellison debt, you don't take risk, right? You're not supposed to take risk. What's been the biggest challenge till now growing to where you've grown? So I think for us the Yeah, look, I mean, I think to for us, the challenge has been when we started this business, we thought that this business is for ultra high net worth and high net worth individuals of the country. That's how we kind of orchestrated, and we had this very, which is why we launched our iOS app before the Android app. And, you know, we had throttling, you know, you have to apply for membership. And, but what really, what we learned is that this problem is not just for ultra high net worth families, it is also for the, the, the the the, I would say, the mass affluent of the country. And, and that is what has really happened that, you know, we've attracted a large number of those users who have had to re orchestrate the product, which is why we kind of rebranded and we said, we have a wealth positioning, and we have the in money, the super money app, okay, so that evolution has been obviously challenging. I wouldn't call it a pivot per se, but the fact that it's now more broad based, so we have these Ember membership tiers, so Platinum is for the rich people he is and then we have the gold membership tier, and then the blue, blue is for free usage. So I think that that that orchestration has been obviously challenging, because each customer segment requires very different kind of servicing levels. So I think that's been a that's been a that's been a challenge. Building a team, despite having so much of experience has been a challenge, right? It's not, it's not easy. But building a team getting the right people in the right place. that's taken me time. It's not been done in a month's time. And that's a constant evolution and constant, ongoing process.
Yeah, I think talent, and
Krishna Jonnakadla 1:16:54
I'll come to the talent part in a second. If Ashish Kashyap says he's finding it tough to build a team then Waterworld has to become for the rest of the people in the country. So the founder is right. But six co founders, isn't your your six co founders, aren't you?
Not See, I think No, no, not that. That's that's that's that incorrectly.
Krishna Jonnakadla 1:17:16
That TechCrunch says about you?
Yeah, no, no, that's incorrectly? No. So it's basically, you know, Amrita and me. And then we have set a few founding members in okay. So yeah, that's the that's the way it's position.
Krishna Jonnakadla 1:17:32
Okay. So let's talk about the talent acquisition part. I did not I did want to complete that growth. So on the one part, so then first class, business class coach class. And so that's essentially how I mean, if so.
Yeah, but a good Good, good, cool, good coach class. So yeah.
Krishna Jonnakadla 1:17:54
Yeah, I always say, you know, flying coach is like, flying cattle. Right.
So, yeah, so not a Catholic class at all. I would call it Executive Class, business class and first class, first class, executive business and first class.
Krishna Jonnakadla 1:18:10
Yeah, no, what I was just saying was, given the nature of the mass support class, because consumers are not just big number, you know, servicing them can be a servicing mass, especially in the Indian context, you know, they come in all shapes and sizes that is going possibly is what's proven to be a challenge?
That's a challenge for us. We had to orchestrate that very quickly. Right. And we suddenly grew, and we hadn't, so we had to put that overnight, that whole system.
Even then, I think the kind of service that you know, blue category or gold categories getting today, right, that is something that is only available to the ultra HNI, you know, the entire family office service.
Type technology has made it accessible suddenly, yeah, like knowledge has made it accessible to truly get advisory at scale. Right. Right. Yeah, go ahead. Go on. Go on. No, no, that's, that's.
Krishna Jonnakadla 1:19:09
So let's talk about the talent acquisition part, I find it hard to believe that you're having trouble. You should be given your streak and given the hypothesis that you're you're working on this must be an A, this is an exciting space. And the beauty of it is unlike all the other systems, a lot of what you do in the other sectors are heavily dependent on what I call as the last mile problem in India. Right? We if we were to really look at Indian serb Indian personnel, right, we have a lot of things. So for instance, you could have a world class nuclear reactor, but the last mile delivery is still done, done by you know, local electric supply units, which are still largely pseudo government or maybe completely government where, you know, things are very unreliable right now. A lot of startups actually get bogged down. and rightfully so because the entire ecosystem is like that. Finance is one such sector where technology, there is a good degree of technology intervention that has happened. And therefore you are able to deliver. Now, the only fundamental difference is there exists these systems and frameworks that you can leverage to deliver superior outcomes, which would mean that you're in our league of your own, to be able to not just offer services and products, but also attract good talent for them. So I find it a little surprising. So talk to me about the challenge.
Yeah, I mean, I think the challenge really is that, you know, once we knew earlier this year that the product market fit is there. We decided that time to invest and to build a team. So and as we were building the team, we also have the pandemic strikers, right. So while pandemic is on, we're trying to hire and onboard people get them into the organization, philosophy, culture, engineers, don't engineers don't know finance, right? They need to be they need to get some some context of Finance. I mean, we need to make it simple. So from that point of view, yeah, I think it's not been a piece of cake. And remember, India is right now flooded with private equity capital, just flooded, right? And as a result that there is for FinTech, there is a larger demand than supply of talent, especially engineering, data science, machine learning. So I wouldn't say that it's trivial. is the hardest, right? So just to just to give you a context, today's date, let's say if you are I am hiring software engineer who is who's interviewing or speaking to me as a company, that software engineer who's exiting has five offers in his hand. Sure. So if I give the first offer to him, he will most likely not join. And this is something he took me also on the stand, because he would have another 40 people out bidding my offer. Right. So the market is madness. So if you are a if you work for software services, nobody looks at you, you know, you work for some XYZ arbit software services company. But if you are in a consumer facing fin tech company, what is the recruiter searching for FinTech? In Gurgoan, FinTech in Bangalore, we come off, right. And then our people get attacked, right. So even from a from a retention perspective, and from a talent acquisition perspective. So I think there is a bit of I had actually thought that, you know, there will be some softening during the pandemic, but it the amplitude increased by 10 times. I think everybody thought it's an opportunity to hire everybody thought. So, I would say that it's not been a piece of cake, building a team. And building a team just doesn't mean hiring, right? building a team means bringing them on board, onboarding them, getting them to believe naturally believe, without indoctrination, naturally believe the core problem with the company solving the product and services, which the company is giving is really solving a core issue, getting them to participate, getting them to get that first small win and participate in impact creation, that cycle, right. So to go through that cycle, right? It's not just about hiring, but it's hiring, building the team, getting them passionate about what they do, getting them excited. That's that's a task, right? I mean, it's, it's not a trivial thing.
Krishna Jonnakadla 1:23:32
Sure, absolutely. No mean task, you need, you can never be too prepared for something like that. Right. So while you know, the IC chip, or the computer chip has grown at the speed of Moore's Law, human brains haven't grown at the same speed. So it has grown in speed, but not at that much. You just, you know, sort of in a passing mention, you said early this year, when product market fit was evident. Talk about that moment a little bit where you felt you had achieved product market fit, and why you felt you had achieved product?
I mean, I think simple. So number one is that we saw that over the in the early days of our product, there was a lot of chatter about us on Twitter, lots of chatter, and it was clearly evident that we were delivering something valuable to consumers. And there was also very, very passionate reviews on the app stores on the Play Store and the iOS stores. A lot of chatter on LinkedIn. So a lot of chatter on these media vehicles. And the fact that consume a feed if we were to do something erroneous for consumers would really get annoyed and write to us aggressively. Remember, the top of the funnel of our app is free, right? I mean, tracking your money is a free service right and free service if it's making a little error. Typically consumers should uninstalled runaway, right? But here the people would be like really like passionate about it. Right? gets solved or not. So we learned a lot from the users every day we continue to learn. I mean, my philosophy has been that you what you want, in early days is few people to love you, then lots of people to be indifferent about true. So we had that very, that we had that power user base, without giving any incentives are without any marketing money. They came to us and derive value, and loved us. So amount, the amount of times I actually shared with the team, the word love comes when people talk about as I love this, and I love that, and I love this about this, I love this nudge widget made right. So I think that's the time when we realized that look, what we are delivering to this to this set of consumers is very, very valuable. The use cases easily are being spelled out by the consumers, the future use cases, the current use case, people are seeing a lot of value. And that's the time we decided that listen, let's double down. Right. In fact, we kind of started seeing that pattern right when we got in tigard. back. And restaurant investors, right? So we started seeing that pattern. And we said, Look, consumer internet is going to be a long journey. So there are unknowns, partners are willing to sign up with us. So we should sign them up. We shouldn't waste the money. Still, it shouldn't that it's not that we started doing TV ads after raising capital, we needed to achieve PFM and then then get to the product to the next level and then say how do we scale this to multiples of millions of people.
Despite so many of our features being Wi Fi? There were signups which were happening. We've had some of the very large family offices, come to us, tell us more and give us feedback build with us. So those kinds of validation have a huge say that we're on right track.
Krishna Jonnakadla 1:26:48
So Amrita two years down the line from the hypothesis that Ashish presented initially with you seems like a while two years seems a very short period, it already feels like a wild ride to me, you know, product market fit and this degree of scale. What is it looked from your vantage point or your point of view? Has it already been like a dream run or you think it's still ahead of you?
See, honestly, I think me and Ashish, we discussed this very often, that when we when we were discussing, we didn't imagine the scope to be so big. And you know, so it's turned out to be a much wider and bigger scope for us, and not just well managed. So that is something that that I definitely learned in the last few years. But for us, it's been very, very exciting. Working with Ashish self, you know, is you learn so much. And like I said, I think my confidence was the fact that, you know, even if we fail in doing something, I knew that we will go back, because, you know, it's at least we know what's happening. Where are the problems? Where is it fragmented? And what is required? In fact, a lot of my clients really liked the platform so much also, because it's built from the perspective of a client issues, right, which is Ashish. So, you know, from my point of view, I think we did a lot of things which other users were not even thinking.
Krishna Jonnakadla 1:28:15
So it looks like between the two of you, you figured out a phenomenal working equation. You I see a great deal of mutual respect for each other. And how did that happen? Was that have you? Did you both know each other prior to ind wealth? or How did this come about?
So I've known Amrita for 12 years. So I basically started Ibibo, and she was the banker at HSBC. So I've known of since that day. So obviously, and she's the one who kind of encouraged me to get into wealth tech, right, that listen, there's a problem. The other thing that we do is we divide and conquer. So I focus on product tech, she focuses on the customer side of the business, the servicing side of the business, the advisory side of the business, the acquisition of the large enterprise side of the business. So that's what Amrita focuses on, I focus on ensuring that I produce a good product, good system for how to be able to market it.
Let's see, one of our biggest apprehensions was that will consumer pay a separate check for advisory? Right, because most of the users today are so used to in charges that they don't even know even if they're paying very steep charges. So that was another thing I think, is very easy, because customer at the end of the day understands that, you know, this is the expenses including and this is the value is driving. So
Krishna Jonnakadla 1:29:43
I think a lot of that is education as well right? Amrita for instance, in the US, you know john Bogle started Vanguard, because he was so fed up with the amount of money that was just being charged with fund managers. I remember way back in 2012 I went to a chase, Chase Bank just to deposit a check. And there was this lady at that point in time, I had about $100,000 in my bank account, because we were just contemplating purchase to making a down payment on a home. And this lady told me, you know, we could do, you should do some investing. I said, Great. What do you think we should we should do? Oh, you'll have to come down for a session for that. I said, Okay, no, give me an inkling of what you're going to do. She said, this is not a very large amount of money. You should just put it in tables. Okay. And then I'll tell you how you should structure it. I said, Okay, what's, what's your commission going to be? He said, 3%. I said, You got to be kidding me.
on it, he will
Krishna Jonnakadla 1:30:45
you you're going to charge me 3%. And you're going to tell me I have to invest in a table. And you're actually charging me for that advice. Right. So now, that is doubled, damaging, right. But but in the Indian context. So the last few years, I've what I've seen is a lot of bad advisory. Right? Especially banks, in the pressure to actually make margins have done have recommended you lip products extensively, which have a loaded wealth in the first three years, these are so front loaded for agent commission, that there is no transparency in the information that is actually presented, even the 15 day free look period that the IRA mandatorily offers doesn't really do justice, because there is nothing there is no, like the cigarette packet comes with a cautionary advice. There is no piece of cautionary advice that actually comes on any of these products. Right. Right. So so looks like you're you're what you're alluding to is that, you know, a lot of that information that you're providing is actually valuable. And I'm sure you know, the Indian market is not that wide, compared to other markets out there. But it's still healthy. You know, the great a great degree of participation. But what I think somewhere, it's just a personal gripe of mine at some point in time. In cop, company, management's today, still, accounting is opaque. A lot of our current accounting is opaque. And given the lack of quality amongst Indian companies, and the degree of money that is there in the system, there is a there is a lot of overvaluation that is in the market. As you know, I tend to take somewhere between an aggressive and conservative stance, if it is all good, quality, clean, management's I can understand. I know, you know, again, we are going into the equity side of things. I'm sure at some point in time, I've always fantasized about this product, which would, let's say let's say for discussion sake, havells. We take havells and using AI and ml, this product here and read through all the press releases and all the interviews of the founders and various officers. And then somewhere you know, points a gap, saying that you know, Dal Mai kuch kala hai. So therefore, you know, be be be wary of, you know, having stock, you know, it's a great company, and I've read their story and all of that, but I'm just using that as a as an example. When that kind of information can happen, I think, two things will happen. deepening of the market, per se, you know, a lot of cleaner management, there'll be incentive to be a clean management. And second, there'll be much more diverse companies. I think, you know, maybe you'll ride that wave looks like you're just at the beginning of it. So what's in store for the next three, four years? Amritha, if I may ask you.
I think we definitely want to scale. Now, you know, in a big way, or like Ashish was saying that we have product validation, we have a lot of customer validation, or, you know, typically any customer will like to delete, but the fact that they come back, give us feedback for us to solve it. And, you know, so that that is something that we would definitely do in the next few years, we are launching many more features on the application. So So yeah, I think it will be that is.
Yeah, I think I think one as I totally agree with Amrita ski. That's the first now focus for us, because scale brings with us with it, lots of benefits. And interestingly, I think we are well poised to scale. You know, I one metric that I shared with you was like the kind of app usage and app ranking we have. The second is also simplicity. The one thing that you know, the the one thing as we go into the mass affluent. We already have HSI as a new Asian eyes as we get that audience making the system's super simple, trivial, with clear, easy communication and education. That's one thing which we want to do. And a product like ours can do that. Like you see something else and somebody else sees something else, right? It's already very personalized, but even more personalized, for example, you should see perhaps, you know, millennial won't have a is as an example as an exposure class or somewhat somebody within somebody who's 22 year old shouldn't see retirement, but you should see retirement right. So those are things which we want to definitely do make it super, super personalized. I think the good news is that we build a very good foundation. I'm very excited in terms of technology complexity, it's 10 acts of goibibo. I can say this in public, but we are very happy with the foundation that we set up. Will you go international at some point in time? I would love to write I took the red bus business as one of my unfinished businesses, right. I took the red bus business to multiple markets.
Yeah. I told you the scope is weird. Yeah. And,
and you know, we've been looking at it right, what resembles our strike. So there's a main we're just tracking but has gone to the advisory. There's somebody who does advisory but not the tracking of financial life.
We already have customers from all over the globe.
As a non resident, non resident.
Krishna Jonnakadla 1:36:00
Awesome. They're terrific, terrific, Ashish Amrita, it was a little bit of an eclectic conversation, not with a chronology that we usually follow. But I'm glad we've covered and touched upon multiple topics. I know you guys are going to scale new topics in the days to come in the years to come. mirages of scale, we'll come back and talk to you when you are at a new peak and a new summit to see what that vantage point looks like. Any closing comments before we sign off?
No, I we've I've enjoyed this conversation. It's helped me to actually reflect ever. You don't do these things. I'll back to them like I actually reflected and thought about it. Just I think I should do some memoirs.
Krishna Jonnakadla 1:36:43
We should come back and still do have specific GoIbibo episode. Maybe you said that's a good story we should talk about?
No, I mean, that's very exciting. Yeah, absolutely.
Krishna Jonnakadla 1:36:52
Yeah. Awesome. We wish you the very best and we'll see you soon.
Tania Jadhav 1:36:57
We hope you enjoyed this story. If this story made a difference to you, tell us by leaving a comment on the website, or our social media channels. Help us spread the love by subscribing, liking and sharing our show. We welcome speaker suggestions and collaboration. Write to me at email@example.com