 Next, we have a fireside chat and for this, I would like to invite Mr. Yashish Daya, he's CEO and co-founder PolicyBazaar.com, group of companies on best practices to make the most of customer insights in the era of fast-evolving media and technology landscape with Mr. Satyabrata, CEO of Media Keys India. I request both the gentlemen to please come and join me on stage. Please welcome them to the big round of applause or a small, thank you. Thank you so much. I think sessions after lunch and after tea are quite exciting. After tea is quite exciting. So hope I see some more people coming in. So we just lost our way while coming back from the speaker launch. So sorry for the delay. So, Yashish, you know, I'll keep the questions pretty simple because this particular category is very different from other categories. It's a very challenging category to go to the consumers and the use of technology of late has been very, very good in terms of reaching out to the consumers in this category. How many of you use, how many of you, if I put it this way, if a person calls you from a bank to sell insurance, what is your reaction? So any one of you, how many of you bought an insurance when a banker has called you? Any hands, show of hands? So I mean, it pretty much says, you know, I think how challenging and how difficult it is. So my first question will be, how new innovation technology has disrupted in terms of reaching out to the consumer vis-a-vis the traditional things that were there and in terms of policy bazaar, how have they implemented those new technologies which has come? Sure. I think when you spoke about insurance that is usually sold, it is the investment kind of products which are mostly sold as insurance. Most people don't even want to know they are about insurance. I think the first thing was trying to get products which are important for consumers, which they may not even understand yet, which are more around life insurance and health insurance. So roughly 70% of our sales would be only life insurance and health insurance. Now the moment you talk about life insurance and health insurance, your best case scenario is you never use that policy, because obviously nobody wants to use a life insurance or health insurance policy because if you use it, that means there is a pretty bad thing happening to you anyway. And from a company point of view also the most profitable customer is the one who never uses the policy. So both from a consumer and customer point of view, the best customer is the one who never uses the policy. But in case something bad happens, the claim must be paid out. Now usually the individual themselves has the highest knowledge. So what is the risk in this product from an insurance company's point of view or anybody's point of view? The risk is somebody's paying 10,000 rupees and there's a kind of one crore payout or somebody's paying 5,000 rupees and there's a 5 lakh payout. So the biggest risk in this is somebody who already knows they are about to claim and they somehow buy this product because they know they're going to claim in the next three months, six months, one year, two years. And this is the risk that one has to guard against. So what is the problem with this risk? The problem with this risk is if you allow that to happen, if you allow people to buy it once they know they need the product, the price will go up for everybody. Correct. So how do you keep prices down? And I think that is where we use a huge amount of data in trying to identify customers who may already know they're going to claim. And this is typically true of health and life insurance. We use a lot of voice analytics, we use a lot of deciphering technologies to just make sure that that part of the customer set is somehow kept out of the purchase cycle because that's not what insurance is supposed to be bought for. And I think once you do that, what that lets you do is bring down the price for... So some of you may have noticed that on Policy Bazaar today you can buy a 1 crore rupee health cover for the price of a 5 lakh rupee health cover. Right? There are three such plans there. And those plans are not available anywhere but Policy Bazaar. But the reason that has happened is because those companies are now confident that we are filtering enough. See, roughly nothing bad or good about it but roughly one third of people in India have one or the other chronic disease, mostly hypertension or diabetics related. All one wants is people to declare that. Correct. If people don't declare that, you will basically have a claims mismatch, right? And once people declare that, there's a higher cost but you get a different policy. If you are able to do... So we are operating on health insurance and the claims ratio of 26% whether retail market is at 85%. And that allows companies to become confident over 10 years when they see this data. It allows them to be confident to say, you know what, these guys know what they are doing. So we are able to reduce prices or give a much higher cover at the same price. And that is how we are using data fundamentally to give customers an offering which they cannot get elsewhere because elsewhere the data is not being used. Correct. But I think that's really the use of data that's happening in the biggest possible manner. So you've been quite a successful company in this particular category. I mean almost 50% is what you...in terms of insurance is what... We are 3% of insurance but we are 50% of insurance. Yes, correct, correct. So tell me, it's a very challenging category to... So how have you as a company made yourself relevant? How have you created the trust in people? And how do you generate that latent demand which comes? See, I think nobody is perfect. But what somewhere we've been able to do is do the right thing for the consumer as much as... From a product perspective always, always. Right? And from a service perspective as much as possible. We are in a difficult industry. It's...you know, I'll give you a very simple example. You today go to a clear trip and you buy up a ticket from them and then you want a refund. You just say okay refund and the money comes back to you. We regularly are not allowed to do that. Correct. The money has to go to the insurance company's account and only the insurance company can refund it. Even if I want to refund it out of my own money and I say I don't care what happens. I'm not allowed to do it. It's considered rebating, it's considered. So we are in a highly regulated tough industry. There is no global distribution system. So we have to integrate with all 40 companies. But I think the most important part is while India doesn't have serious social security for middle class. Correct. See, when we talk about social security in Europe versus social security in India, there may potentially be some social security for very, very poor. But for the middle class, there is no social security in India. So if a middle class person falls sick and I have tons and tons of examples, they can basically one health situation can bankrupt them. A death of an earning member can bankrupt the entire family. So the impacts are very severe. Correct. But even with those impacts, 90% of people pay for hospitalization out of pocket. And less than, okay, so there's only one million, less than one million people in this country buy pure life insurance, which is what people should be buying. Correct. So the biggest problem we have as an industry when they talk about fintech and technology, it's not the technology. The biggest issue is the customer even willing to engage. Absolutely. Right? And how do we stay relevant there? I think there are two parts to it. One is we have to distance ourselves from what is typically being sold as these cashback, moneyback, X-back, Y-back plans. Correct. Which are usually not very good for the consumer. So the first campaign if you think about it was Ulumat Bano. Correct. Which was to get customer empathy that look, this huge amount of stuff that happens in this industry, you don't need to do that. Correct. And the second part is what do you really need to do, which is this pure life insurance, pure health insurance kind of area. Let's emphasize on that. Now even on that it gets boring. If I keep telling you these stats of people die, hospitals are full. It's a fact, right? You go to any hospital, you'll see young people, old people, children, they're there. A friend of mine was the chief operating officer of one of the big hospitals. I asked him what is the revenue per bed per day. That guy said 25,000 rupees. So 25,000 rupees per day, per night is the revenue of the hospital. Obviously somebody's paying for it. That's the consumer. So even in that situation, you can't keep giving these facts, it'll get boring. So we have to always keep it funny. Correct, correct. And even our communication has to be such. We have to play on the fact that as one gets older, there are certain age-based events because of which it gets more expensive. We have to play on the fact that if you have genuine data, we can give you a better product. So these are three, four broad themes that one is able to play on over a long period of time. And yeah, if you keep creating that, see, people say we have 50% market share. But besides us, who else is really talking about these products? Right? Basically what people are saying is compare, save. But who is talking about the product shift? Correct, correct. So I think that is the area we've kind of cornered for the last 10, 11 years. And that allows us to somewhere stay relevant for a few customers. Yeah, that's what I'd say. The other big thing which I personally, you know, I was interested to know, and I think the house would like to know is, you know, you've done a 1,500 close equity from SoftBank. So how could you land at the SoftBank captive? I think, see, in the entire e-commerce world, if you would, how do I put it? You need money to build every business. There's no doubt about it. But somewhere over the last five, six years, money seemed to become the only differentiator. Or become, you know, rather than execution, the focus somewhere shifted on who has how much money. And obviously we can also see that, right? So it's no longer that, okay, two players have $100 each and let's see who's more efficient and the one who's more efficient will get more money to the other person. But what's become is, okay, so how much money would it take to do maybe an inefficient thing? So I think having the largest VC on your cap table is very critical for any industry leader. Correct. And hence, I have no qualms about it. We were the ones who chased SoftBank again and again over the last two years to convince them to come on our cap table, right? And the second part is, when you talk about fintech innovation, who would know about it? The person who's investing in companies across the world and SoftBank seems to be that organization that is investing in whether it's Zongan, whether it's, you know, whichever company is financially innovating in a significant way, getting to a billion dollar plus valuation, SoftBank is somewhere involved. They're involved in the insurance world, they're involved in the reinsurance world. So the amount of learnings they have are quite practical. Correct. And they can be applied. For those two reasons, they seem to be the right people to get on board. And just from a clarity perspective, in our case, because we were so keen to get them on board, the valuation they paid was maybe mediocre. So there were quite a few others who wanted to pay a much higher valuation. But we were very, very keen and very clear that they were the only ones we wanted on board. Wow, fantastic. I think which a lot of people want to know that after this fintech revolution, I mean, I understand this AI powered robots, they'll be digital advisors taking over and they're going to advise you on financial matters. How do you think about it? Are you starting using it or something? We certainly use it. See, we have two kinds of products. Okay. One is products which have a buy-by date. Motor insurance, two-wheeler insurance, travel insurance. You need to buy it by, let's say, 19th of December. So what you're going to do is go out there, check out your options, but eventually you know you have to transact. You don't need a push to transact because you're going to do that anyway. So in these products, a lot of automation we have done, so roughly 80% of all transactions in these products, actually 90% plus would never speak to any human being. So basically it's robotic in a way, right? It's all electronic, it's all robotic. Travel and two-wheeler would be 95, 97%. Motor would be 75-ish percent. We would never speak to anybody, you just kind of go through. And then you come to this different set of products. Products which you don't have to buy. Like a health insurance, right? You may buy it today, you may buy it in the next six weeks, you may buy it in the next six years, you may never buy it. It's relevant for you. You think about it once in a while, but you don't have to, right? There is no compunction. And here it's not about... So it's a combination of information and nudge. That needs to happen side by side. So I think in these areas, the information part, a robot, can do much better than any human being. There is zero doubt there. So most of our sellers would essentially be getting instructions on the... They have experience, they do get specific. It is a bit complicated, but I would never say it can't be robotized, right? I think the problem is, what about the nudge? Correct. It's a bit difficult for the robot to start nudging. Correct. You know, when I hear the conversations, they are about people's children's, the weather, the pollution. It's a 90 minute plus conversation that leads to a health insurance sale. Wow. So a relationship has to be built with the buyer at a somewhat different level for somebody to say, you know what, here I take out 15,000 rupees and put it on the table and buy a health insurance product. Why are you? Because I trust you're doing the right thing for me. As I said, two kinds of products, two different approaches. I do believe from an information perspective, if I look at our own system, it's quite robotic. So there is very little left to the individual knowledge, so to say, already. Which is one of the reasons, one and a half, a 45 day old agent can pretty much do the same conversion rates as, you know, one year old agent. So it takes just 45 days of training to kind of get, and that means it's robotized. It's a process, right? But the nudge is still required in the health insurance and life insurance industry. The nudge is still required. There's no doubt about that. And are there regulatory issues in this? Is RBI involved? I mean... IRDA. Okay, yeah. I don't think the regulator has any issue with you. They understand that insurance, remember, there are 3 million agents in this country. What do the agents do? They go to people's houses, knock on their doors and say, so the nudge is very relevant. If the nudge wasn't there, wasn't required, why would you have these, you know, the whole agency force? So they understand a nudge is required. I don't think there's an issue there. I think it's a bit of a surprise. So I'll put this differently. In India, we have one of the highest rates of consumers coming in and asking for health insurance and life insurance anywhere in the world. But that with whatever humility you want to grant me, that I think is largely attributed to Policy Bazaar. Because something like this may not have happened anywhere else in the world. I think this is something... So we have one of the highest rates of people looking for these products, which just can't happen by itself, right? Okay, now I think the clock shows me the time. So maybe the last question. Now that you've reached to that, I think you've done that 100% growth. You've reached that 8 million consumer base. And I think another thing that you should touch upon is how has Amazon Poly helped you in the growth? And secondly, I mean, what's your personal growth that you're looking at Policy Bazaar and now I think that 1,000 crore benchmark that you're talking about. So I'll touch upon Amazon Poly. So we have 2 million minutes of talk time a day, right? And as I said, we have to take all this information and we are responsible largely for selling risk products, so health insurance life risk, where you sell a product for 500 rupees a month and it can give somebody a 5 lakh claim or 1,000 rupees a month, it can give somebody a 1 crore claim. So for us to identify risks across this whole spectrum is very, very critical. And that is where Amazon Poly really comes in because from all my information, we're the first Hindi-based voice-to-text operation that is going on, which in real time identifies risk, identifies opportunities. So in real time, as you speak, we are able to identify that risk, highlight it to the agent and ask him to course correct and whether that means you need to undergo a medical or whether that means further investigation of some sort needs to happen, that happens at the back end. Also, this is used in customer service quite a bit, but that's a far easier use case where a person comes and says soft copy, namely, so you make sure the soft copy goes through. So a lot of that happens, but I think the real use case that we are building on is identifying risk in real time because that is a game changer for the industry. See, this industry works on 85-90% claims ratios. So if you can change the claims ratio, you've changed the industry. Absolutely, absolutely. That was brilliant. Thank you so much. Thank you. And brilliant chatting up with you, Mr. Dayan.