Finance Careers in the Age of AI: Who Will Be in Demand Tomorrow? | Timur Turlov | Freedom Broker

De Maragul, director of the analyst department of Freedom Broker, to inaugurate this event. Please, the floor is yours.

Hello, dear colleagues, distinguished guests, distinguished friends. First, I'd like to meet the audience. I think this word, 'the youth,' is appropriate. Could you please raise your hands, the ones who study at the university? Okay. And now, whose graduates over the past five years — the alumni? The alumni. Well, and now the five-year experienced workers. Well, it's all clear now. Well, let's get started. Well, our session is about how the stock market works under the hood in the IT era.

So, I just want to make a small intro. We've recently done research about the introduction of artificial intelligence at the finance market. There are different technological trends that affect financial markets to a greater or lesser extent. The financial markets consist of several blocks, and one of them is artificial intelligence, which is being introduced in the banking sector both in Kazakhstan and in Central Asia in general. The two key findings are the following: the Central Asian countries are less prepared rather than the global countries, and the financial organizations shifted from the use of artificial intelligence in their client experience towards the transformation of internal processes.

For the stock market, I think these are slightly different trends. Blockchain, cryptocurrency, and new markets emerge, and they impact the way the market will look like in 10 to 15 years. And it heavily impacts where we need to go to build our strategy accordingly to improve our businesses and to deploy our business models. So today we have pretty good panelists: brokers, stock exchange, and financial organizations. And we want to talk about where the young experts should look in the future for them not to deal with a certain business but to build their career purposefully and do something beneficial both for the market and the society.

Well, the first question I'd like to forward to Renat. Okay, Renat, tell me please what the broker looks like from inside, and what the financial institution looks like now, or probably we can have a flashback to see what the dynamic was and what's going to be next.

Well, thank you very much for this opportunity to speak, and it's really pleasing that the stock market, you as the young experts, consider the stock market. I want to tell you the obvious thing, but there are not enough experts. I joined Freedom in 2016 as a broker back then. I think the good thing is that we communicate with Olivier and Mikhail, and we've been all together for 10 years working by introducing different tools. Over this past 10 years, I wouldn't say that there are more experts. Now the stock market is considered a technology which is invisible, and we thought like it works itself. It works like the light or the sewage water, the supply water.

But the stock market has the fastest, the coolest technologies, and the fact that they work means that there are many people who stand behind, because the stock market infrastructure is difficult from the business models perspective. There are central depositories, there are some channels, some counterparties, and others. But the applied part of the stock exchange market is very complicated to understand from the first side. So if you press on the buy button and you buy shares, normally it seemingly should work this way, but there are many cases that occur backstage: clearances, clearing transactions, because you buy and sell shares, but there are so many processes that take place behind the operational day.

When the day closes, the central depositories, they clear the difference from every purchase. The same way the banks work. The applicable part of the stock market is also complicated, is also challenging. When I joined the brokerage, I didn't have so much clue about this, but I was very curious. I was wondering the way it works. I remember since 2016, we were introducing the FIX protocol in KASE. We helped others to test their phenomena, because the market's activity is a big factor, and historically it consisted of multiple factors. It was not that high, but over the past 10 years it increased dramatically, and you need to be involved in testing the system.

We used the protocol, we were engaged in the protocol testing. We did that, and a couple of other brokers. Sometimes it's so difficult to detect all the errors, all the mistakes. And even if you check what FIX protocol is, the factor is a standard, and probably you know the way it works. Some other engines check their protocols, but historically the stock market is really technological, and we lack experts because it's really specific. There are no training courses. The universities don't teach the curriculum to train people and to help them know what kind of technologies lie behind this technology.

And our TradeNet platform works with 10 brokers, and we have been developing them since 2010, 10 or 12. It passed through a number of different upgrades and updates, and we are really proud of it. It has turned into a unique system, because this kind of a system has no parallel products. Neither Kazakhstan nor other jurisdictions have something similar. It's unparalleled, and for you to understand, the development of the platform involves more than 150 developers as well as the same number of product developers and managers. As a matter of fact, our trade platform involves more than 500 people who develop them every day.

But you don't only need the developers, you don't only need the business analysts, but also the people who know how the stock market operates, because the applicable part of the business is extremely important. All that can be learned, all that can be accomplished. And the best example is that in 2016, we introduced the post-netting tool. You don't really have to know what it is, but probably there is nothing that gives you an idea what's what. But as a matter of fact, it's a tool that allows clients to shift their positions, to borrow short money, and every day shift their positions without the need of repaying. Just for the sake of example, you buy shares and you see their growth, you can borrow money and prolong specific positions as long as it's necessary.

Probably we've been discussing with MK and Olivier that in a particular university we will launch a curriculum for people to understand what the stock market is and the way it operates technologically. Because of that, there would be more graduates who know the way they work. Because Freedom Broker Kazakhstan's integration with them, there are more than 200 different integrations with stock exchanges, with the depositories, with the KASE. An integration represents not a single service but the access to the section where the shares are traded. There is a currency trading sector where the currencies are traded, and all of them have information gateways, and at every gateway there is the developer's version, the test version, and so on and so forth.

The architecture is really challenging and probably complicated, and we need to have well-trained people. We will train them, and as the practice shows, we have many outstanding specialists who know what the stock markets are, the way they work, and especially when there are large-scale projects, when KASE shifted to some other platform and the market didn't notice that, didn't notice this transition, it was all seamless. As of course there are not enough experts: business analysts, system analysts, developers, all of them are not enough.

I'll tell you why, because the scales of the stock exchange did not allow the owners to pay for such people. But now the reality has changed, and after Freedom, other brokers appeared, that pleases us, because developing the market together is more convenient than having all people working in silos. My answer will be like that.

Thank you, Renat. Very, very brief answer, very short answer.

Yeah, especially when we talk about the stock markets, it's so difficult to answer easily.

How many brokers do you have?

It depends. Two brokers, the major ones, but as I remember, the number of clients was like 300 clients, less than in banking. But the stock exchange nature is different, because the banks' clients face their work every day, because you need to access your mobile app to check how much money you have on your current account or on deposit. But the stock exchange players play in the long run, because you access the market, you access the app and check the way the listing positions change, which makes investors panic, because the market may go up, may go down. And if you check all the listings, small and big ones, Microsoft and Freedom, the market is growing, is consistently growing. And if you think where to invest, probably you need to invest in ITF and of course in Freedom's shares.

And the market shows. I received the news that those clients whose portfolio is more than 50 million, they prefer to invest in the stock exchange market because it's a significant alternative.

How many people work with brokers?

As brokers, like 300 people. Yeah, there is a company, Freedom Technologies, which we transferred to Aana Hub. Distinguished Med is not here. We set it up there, and there are around 300 people. They are engaged in the development and product follow-up in the TradeNet, and they didn't have the divisions out there. And most of them are our distinguished salesforce, the ones that sell our technologies. And now there are 700 people in all. So 300 are technical specialists. Yeah, I mean, they live their own lives because they represent a separate entity. They work independently, and we just use them with different brokers, with different countries, for all brokers, for all markets. Oh, it's better that we work this way.

Okay. 300 people serve 300,000 clients, right?

Well, I mean, if you consider all brokers and all clients from all countries, there will be more than 1 million, because there is also a big market in Europe. And I think that this kind of indicator, probably you need to check it, because the banks serve increasingly more people, because the average receipt is like this and the transactional story is higher, and this is something different. I think that we can calculate how many clients fall to a single broker, but I think we were one of the greatest in Kazakhstan.

Okay, we will come back to you shortly. Our guest from Astana, Olivier. We had a talk yesterday, talked a little bit about how to run this panel session, and the question I want to ask you is almost the same as I asked Renat. How does a modern exchange look like today? How does it look today? And probably it seems like you have a lot of experience, and how it looked back then, like 10 years ago.

Thank you very much for this opportunity. I'll switch to English. That'll be much easier on everyone. I'm sure everybody speaks English here, as you should. I see young people. Yeah. All right. Good. All right. Well, I'm an old-timer here. Okay. I joined the exchange industry 36 years ago, the futures exchange in Paris. Back then there was no electronic trading. It was like a good old open outcry trading pit with people wearing bright-colored jackets, shouting and screaming their lungs off. The only skill that was required back then was basically to shout louder than the guy next to you and make sure nobody steps on your toes. Obviously that's changed a bit.

I was lucky enough that when the futures exchange in Paris decided to move to electronic trading, I was there. So I was at the right place at the right time. Also had one huge advantage. I was probably the only guy at the exchange who could speak some sort of English. So that helped a lot. So they told me, listen, you migrate the operations to screen. And I did that. Little did I know back then that I was the second guy in the world to do that in the futures markets. The first guy was in Sydney a few years before. And then my phone started ringing, obviously, you know, because at the same time many new exchanges were being set up or people were migrating from open outcry to electronic trading.

So one guy called me first, like in Australia, he told me, well, I'm setting up a derivatives exchange. Why don't you come and help me? Just went there, helped them. We set up the exchange. It was during the first internet bubble. The exchange went belly up within three weeks or something like that. It was a great experience. I mean, not for the shareholders, obviously, but for me, I learned, you know, everything you shouldn't make in terms of mistakes when you set up a startup exchange. And I sort of made sure I wouldn't make those same mistakes again.

And then I moved to Boston in the US, where we set up another exchange, the Boston Options Exchange. And every time I could see that the technology was advancing, advancing very fast. Then the third one was Turquoise in London. Turquoise was what was called an MTF, multilateral trading facility. It was basically just a trading venue. Back then, anybody could go and set up their own exchange. You didn't have to be a listing venue with all the regulatory burden and that sort of stuff. Also, it was like the start of high-frequency trading. So it was basically a shooting gallery. It was just trading. So you just put like, you know, 20 algos in a room with like no furniture, no nothing, an empty room, and you let them shoot at each other.

And then I moved to Qatar, and Qatar was good because, like, my first experience in cash products, cash equities, as well as my first experience at frontier markets. And Qatar, the exchange existed already. The reason why they got me there was to clinch what's called an upgrade from frontier to emerging markets with like the main index suppliers, MSCI and FTSE, which we did, which equated in $3 billion getting into the exchange overnight on the day of the upgrade.

So yeah, that's basically, you know, how the exchange world has evolved. And now we're, you know, I was, so obviously my phone rang one day and some bloke in Kazakhstan saying, you know, why don't you come and help us? We're setting up this financial center and we'd love to have you here. So I came up, like, set up my fourth exchange from scratch, and we also set up a depository from scratch, which wasn't the idea initially. So, you know, ultimately, if you lift the hood of this whole thing, what do you see in there? You see software, obviously. You don't see it because it's intangible, but it's software. It's like a, there's a matching engine, which is clearly not, it's the easiest part of the whole thing. You see a settlement engine, which is much like more complicated. At KASE, for example, you'll see a clearing engine as well, which will manage the risk, which is getting more complex. And you'll see surveillance systems, hopefully, that try to detect the baddies, because, you know, when there's money, there's always bad people. There's like the minority, but you need to make sure that...

What language do I want to speak? That's something that's very important. You know, like 30 years ago, like, what language do I want to speak? It's like, well, I speak English. You know, today maybe like if you speak Chinese, actually, you probably don't need to speak English. But now also what you want to know is like what sort of IT language do I want to speak? What sort of IT language is used today and more importantly will still be used in five or 10 years' time? So like, you know, in the old days, like COBOL, Fortran stuff, I'm sure you've never heard about. Now, what you know, what's used today? Python, obviously. C++ is still there, which is surprising. Go and Java of all things. Java, like 20-year-old Java, is still like very much in demand. So, you know, that's something you want to think about, what you want to speak. SQL as well is still like very much in demand.

Also what you see, we don't see actually, is hardware. You don't see hardware anymore. So the hardware, all the software sits on hardware, but the hardware is now virtualized. It's all like virtual machine. So you can't even see like a good old piece of server. And even the data centers now are virtualized, you know, so everybody moves into the cloud. Like AIX was the very first traditional, i.e., the non-crypto exchange in the world to move all its infrastructure in the cloud, in the AWS cloud. And there's something here that's happening right now, and actually a Freedom Group is involved into it. There's a next-generation state-of-the-art data center that's being built outside Astana called Akashi. That's the future.

I can tell you when those guys are live, it's going to be a game-changer for Kazakhstan for another good reason, is that for the first time you'll have all the cloud providers coming into Kazakhstan: AWS, Azure, Kascloud, the local one. And those guys are going to set up a segregated Kazakh domain in the cloud that will most likely host the whole financial infrastructure of Kazakhstan, and that will take care of all the data, the data confidentiality policies that cause problems at the moment.

Then what you see also is telco. Obviously you need telco, like everybody accesses the exchanges via VPNs, secure VPNs, private VPNs. That's the way it is happening today. And when you have all that in place, the last thing you need is IT security. So that's also one area where there's a massive demand for talent, and that will keep growing because, like, you know, especially exchanges are very privileged, if I may say, targets for all the hackers of the world. All the hackers of the world dream of hacking into an exchange system, and we're continuously under attack. I mean, we see throughout the day, every day, we see people trying to hack into our systems. So far we've managed to resist that, but it's a constant priority for us. That's it in a nutshell.

Thank you, Olivier. Pretty interesting experience, and I see two massive trends: that exchanges moved from all paper to all digital in the last 10 to 20 years, and now they are moving into the cloud and getting further in that. But as we talked yesterday, I know you have a law background, but... and I want to ask the audience... I will ask in Russian.

So you see, it's pretty interesting that not a lot of IT guys are here, but exchanges and brokers are moving into IT. And in these terms, what would you recommend? And what to choose, young guys, what to study, what to learn, maybe not only about programming languages, but also probably crypto or something else?

Is that for me?

Yeah.

Learn what you feel like learning at the end of the day. Obviously, you know, try to define what will be in demand in the coming years, in the next 10, 15 years. Make sure you like it as well. Don't get dragged into doing something you don't like. Yeah, crypto is obviously something, I mean, more than crypto, and MK will tell more about that, I'm sure, is tokenization, tokenization of securities, and like the, you know, all this segment of the financial markets moving into tokenized securities, I think will be something very important in the future, not only on the trading side, but in my opinion, more importantly, on the settlement side, because all of a sudden you're going to go from T+2, T+1 settlement, you know, with all that that then entails, to real-time settlement. So yeah, that's something definitely you want to look at, and also, as I said before, IT security. There will always be, you know, jobs for people who are good at IT security. Yeah, thank you.

And probably our next speaker, MK. With MK, we already met before when we worked with MK. I know that KASE... So we did a lot that there should be a tokenization in the Kazakh stock exchange, and we would like to know more about what really is considered the highest trend, the biggest trend. I mean, not specifically when you talk about KASE, about the stock market as such, what is considered to be a greater trend in the area where you work: the artificial intelligence, or blockchain, or crypto?

So, well, I can also tell you how it all works, how we got to know the stock market back then, why I didn't have this part of the story. Well, thank you. Thank you very much for coming. Thank you very much for this question. Well, and by the essence, to the essence, let's go to the essence.

So, in the stock market, so my acquaintance with the stock market started in 2007. And that was my first experience working at KASE back then. And to my luck, I knew all the advantages, and it used to be a very difficult topic. But it was sexy, so to say, all this finance, bankers, brokers. I was on the verge of all these systems where the speed is needed. Yeah. When the speed is needed, I'm always there. And yeah, it's still, it's still a very demanded skill. And yeah, indeed, since then, if you look at what changed, it used to be a very wide, non-regulated market. And despite the fact that KASE stock exchange appeared in 1993, two days after the introducing of the national currency, they had a very huge experience with all that. But despite this fact, since 2007, 8 and 9, they marked the complication that led us to where we are now.

Well, if you talk about the technological system, what's the difference between the systems of the stock exchange from our products is that they are very diverse. You have to have a very hot core that could process the requests very fast, because if you talk about the KASE stock exchange where the currency rate is defined, there are not those who trade with hands there. The requests are generated by algorithms. In one session we can get around 1 billion requests daily, and no one works with them manually, and only if someone insists or in requests.

And the second part relates to our backing and clearing system. And every time when the client submits a request, one needs to decide whether to give a loan or not, to give a chance to process a certain request, and it depends on what will be your security, and all these things must be calculated in a moment, at a time. And a bigger portion represents the facilities: the way we attract and issue, how we rate, if he can trade or not, how we monitor the stock exchange member if he can trade or not, what's his financial state, and so on and so forth.

Given that into consideration, that the greater majority of our audience are financiers, they need to know that the stock exchange is not only about the trading work, but signing a transaction is one part of the story, and the second part is the requirements to the issuers. And if you want to be an issuer, you must comply with certain requirements, and the stock exchange decides if you are in the issue A or issue B category, and if we can give you special terms and conditions, and the investors will take a look at that. So 2002 tools are available in the KASE. You won't be able to check each and every one, and you will have to have certain tools, certain instruments, so to say, that would be really useful.

This is what you tell to the investor: this is the tool that I evaluated by grade A. I put it on top of my listing. The same is applied, the same applies to the stock exchange members. What margin level is allowed? Can you trade with a leverage? Do I trust you, or I need to give you the full deposits? And those things must be available in every stock exchange, and the greatest portion goes to analytics. And what we got, all of them combined over this transaction, some news media aggregate for the stock exchange sells something, the market data goes to Bloomberg operators, the media agencies that process them and trade them and provide them within a certain period of time.

One needs to understand, if you talk about all those technologies, all these stories, you will tell you that you can't do without technologies, and a greater portion where you need to develop a procedure and what's to be done about your client, how to improve it, how to meet his or her demand. And if we proceed to the tokenization, the tokening is kind of a next step, game-changing technology. Yeah, I stand for this word because this year we want to launch a new market, digital finance securities markets. The law was adopted in January that allowed the use of this tool in Kazakh legal field. It allowed us... we have to have the financial markets that we need to change. This is what we have to trade from scratch, and it's a new tool. Luckily, the regulators... so this is how we work, and we decided to regulate this story and didn't want to forbid anything.

And for us, this technology is not a game-changer because we use it somewhere in production, some use some cloud technologies to work with all that faster, and the clearer cases are the data centers and others. But this is not our, this is not our core business. The core business... well, if you talk about all this, if you talk about the idea globally in terms of surveillance, in terms of detecting certain manipulation, what the brokers do for funds and some others, this is the story. This is a big stock exchange segment that takes so much effort and so much resources, and this is where it helps us a lot. This was my short answer from my side. Yeah.

Well, well, but what the answer is, where the specialist should look at, the tokenizing, the cryptocurrency. According to me, this is the area where in the coming time the growth, the boost will take place. But the foundation is still there. You would need to have T+1, T+2, like the way the clearing takes place, T+1, T+2, and let the youth think about it, not we should. But I think this is a question to Renat then. Renat, you have the traditional stock exchanges that deal with financial assets and tokenizing. So how should we, how should the broker move in this regard?

I mean, towards commercializing tokenized assets.

Well, what we didn't mention in here is the market itself from the client's standpoint. The reason why Freedom Broker has grown is because the market of Freedom Finance allowed to do so in 2013 and 2014. The retail market, the frequent clients in the capital market, did not exist. There were so many volumes, so many trades, so small number of clients, and Freedom managed to occupy this market, and it turned out that the stock markets can be used to earn money. That's why many changes took place.

So answering this question in front of the audience, I would tell that the majority of people, the ones who don't know the stock market, will have challenges to understand the concept, because not all people understand what the loans are, what deposits are, what securities are, the way they work, the way they are stored. Do you know where all the dollars are stored? Does anyone know where all USD banknotes are stored? Well, the same matter comes to the transactions. They are somewhere physically in terms of the entries in a ledger. You know, there is a, you clear, there are other brokers where the securities are, they are all in the Federal Reserve Bank. When you transfer to somewhere above, there is a correspondent bank, and the correspondent bank clears the transaction from the Federal Security Service.

So if you have a question, maybe what we, any product that we launch in the financial market, every product must be evaluated from the economic perspective. You can arrange it as a system that no one cares, or the product that no one cares, but you need to understand what is really trendy now and what all people think is the trends, because we see the trend in regulation that it becomes more and more needy, and the young generation understands that better. Bitcoin and crypto, those tools are considered the most demanded among youth. That's why we want to increase the pool of licenses, and in this regard, AIFC provides the financial asset tools.

Thank you for the answer. I think these are two different worlds: the traditional finance, cryptocurrency, decentralized finance. In the first case, I think this is a dual-tier infrastructure, dual-level stock exchange and the client, and in the other case, the crypto can work separately. Do you consider it a challenge? And so the infrastructure will shape, and probably if you can work, the foreign currency stock exchange in Kazakhstan, can we do that or not?

We can't do that. I'll tell you, there is an illusion of confidentiality about the permissiveness and some other matters, and this all works only because of this chaos. And the whole world is looking forward to the cryptocurrency, and the government represented by a regulator. The regulator wants to control everything, and they want to guarantee that the investor's money will not disappear. And if the money is decentralized, sooner or later the new rules will appear for the cryptocurrency, and the same tools may appear at the stock market, and the story will start again.

And I would like to mention the liquidity. You can buy Bitcoin. It doesn't really matter for what price you buy, for a bigger or for a lower price, and the same mechanism is activated. So the key rule model will not change. The stock market is a place where people need to buy and to sell, and we really hope that the broker will provide for an important thing, to protect the client, because the acquaintance with the stock market is a really long journey. People check if they really want it or not, and of course sometimes they don't read in a tiny font that the investments are associated with the risks.

And what Freedom has been dealing with historically long ago allows people to dive into the stock market, and you think how to simplify that. The cashback, that period, there also represents the part of the saving culture and the saving market where you can get access to the stock market really fast. Yeah, not like the shares, but along with that. Because if someone wanted to open a cryptocurrency wallet or not? Well, if you try to do so, a regular person cannot do it himself. It's so difficult to work with all this, because not all people will understand what's what and the way it all works.

Well, I fully agree with you, and yeah, there will be a huge work to do to make it acceptable to the client. I have a very short question to the audience. Does someone know the stock market? Does someone make any transactions? Or please applaud the ones who did. And what about crypto? Did anyone use crypto? Well, in any case, anyway, there are some people who use that, maybe practically on equal footing.

Okay. The question to all speakers I want to ask is that the first one when it comes to the topic of the conference, and the second question is what I always ask in different meetings. The first question is, what undervalued skills would you recommend young people to learn? The first question. The second one, what would you invest in? You can mention it here because there are brokers and stock market people. Where would you invest 1% of your portfolio? Only 1%.

For you, Olivier? It's a question we discussed yesterday. So the first one is, what underestimated skill would you recommend to master for young people? And the second one is about 1% of your portfolio. How would you invest it?

Well, to me, the most valuable skill is soft skills, actually. So it's just like there's too many very bright, brilliant people who are just nerds. They just don't know how to operate in a social environment. So just work on your soft skills. It might look, you know, obvious, but it's something that's very important. And for the rest, again, you know, choose your direction and stick to it. Okay. Make sure you make the right choice at the right time and don't change the, you know, the road every like five minutes. Once you're on a roll, you keep going. Where would I put my money? If I had money, obviously. Well, 1%, I mean, so the 1% is like, it's like you put it on something that's very risky, because assuming that the remaining 99% are like real estate, you know, ETFs, that sort of stuff. So I'd just find a good old hedge fund, the riskiest possible, not like somebody who's like trying to pick off on nanocodes or that sort of stuff. I'd go do some research, find out which hedge funds got like the really brainiac, like in a risky type of strategy, and I'd put my 1% in that, and I'd pray it's only 1%.

Well, I support you in a way that the training is an important point. You need to concentrate on soft skills. It's something that will never harm. I think the soft skills will always help you as long as you live. First and second one is you want to be open-minded. You should show interest, life learning, long learning. You need to try something new. You need to read books. You should not give up doing that every day.

So now the speed of changes that we observe in the world does not allow us, does not give us a chance to stand still, think like I'm a master in this regard and I will always do that. Because four years ago, three years ago, no one knew about, no one would say that that's going to be a thing that will help you in every single task. And even people use AI as a psychoanalysis, as a psychologist. Many people would not believe in that. The same thing happens to Bitcoin. No one would say that in a 10-year perspective the Bitcoin is going to be at the institutional level, at the level of the stock exchange, and the countries may shape fresh crypto reserves as well as the changes to the legislation. The change speed is very fast, and we need to adapt to it and do everything what it takes.

Well, I cannot tell you anything about 1% because the compliance forbids me to do so.

I hoped that at least you would say something. Would you give a suggestion or recommendation?

I think when it comes to the stock exchange, if 1% relates to 10%, then it's going to be like 0.1, or you should invest something risky here. But this is not the institutional recommendation, this is not an investment or institutional recommendation, this is what I wanted to tell you.

But in terms of the skills, probably you will interact with people, and you need to learn how to interact, how to communicate with people, because everything that we do will depend on us. The way you communicate, the way you agree, the way you sell the ideas and the projects, and the way you can perform difficult, challenging things to happen, because you help people, people help you, and this is an ongoing circle. This is what we promote in Freedom.

Thank you very much for this very concise answer. So our time is running out, and I just wanted to summarize a few things: that the big trend for the stock market is tokenization. We realized that the brokerage and stock exchange market is becoming more technological, and it is very rapid rather than 10 years ago, and we know where it's going. And I hope that you have gained some valuable knowledge about where you want to go, what you want to arrange. And associating myself with the speakers, I just also wanted to tell you that there is also an important thing like the reputation, and I think many people on the onset of their career path don't evaluate it, but keep your reputation clean from the youth. And this is my thank you.

Okay, ladies and gentlemen, please don't part. We will have the next session now. The coffee break will be served somewhat later. We will continue the discussion with some other experts, and meanwhile the stage will be modified a little bit, and we will continue our financial summit.

Communication from our side, the people who are not in the financial sector. I took some notes. I made some findings. Many people applauded. Many people had a round of applause who are non-financiers. And just tell me, please, after they speak of such outstanding experts, has someone thought to be the technical guys or not? Well, please have a round of applause who wanted to be the developers. Okay. Okay.

I thought for a while, because you open up an investment app or some other app, banking app, you won't have an idea that after pressing a simple click there are 300 developers behind.

Here we have the next moment. I started from the moment. I started all the story from it 20 years ago. I've just was deep down in the analytics, and many things are being digitalized, and there is a question: what about AI? What about this, that you will stay alive and AI will not overcome? If you think that AI will overcome, raise your hand or clap your hands. Let's discuss it in one year. What about platform? It's being, it's getting ready. Now we have super experts: Vadim Kulf, analytical director, department Freedom Broker. You're welcome to the stage. Alex Maximov, strategic client business management, client broker. You're welcome to the stage. And the moderator will be Ruslan Sultan, economist, expert, and author of the Telegram channel to Economica. The floor is yours.

And good afternoon. Let me continue the previous session. The stock market was several years ago in my life, and Gaspedin Suk, Mr. Suku, worked there, and I wanted to go to a stock market, but when I woke up, I understood it's too early to start to work here. But life brought me to economics matters, including analytics. The most important thing, I try to utter all these things in a simple language, analytics in a human, transparent language. It's very relevant.

The previous session was for experienced people who know what is it. If I understood you correctly, we have a lot of young people. This message is for them mainly, and this session is for you. So you could have comprehension of analytics, because clients don't need dictionaries. They need, we need to persuade them. The more complicated market, the more simpler we need to talk. And AI is being actively developed, and models are being developed more rapidly, and calculation is being developed rapidly. At the same time, the most important thing is that AI cannot make decisions. Human beings need to make decisions. Therefore, a matter of quality of work and how it can deliver their message.

And Vadim and Alex are being actively working. They're not theory people, and they know what is analytics and the future of this area and how to sell it to the business. And the first thing I want to mention, it's a junction of expertise and sales. Some people, some analytics believe that accuracy is the thing, but salesmen believe that the client is the main person, and we have discrepancies or discussions or disagreement here. And Alex, a question to you: when an analyst is too smart for a client, maybe there is a distance because of that. What about your opinion?

Thank you for your question. Many guys started with this matter. We have a certain problem, and academics get people ready for this, and practitioners get ready them. And the first part of people want to explain something. For instance, you have a master's degree in physics or a bachelor's degree, and you see a lot of diagrams, you need to have a lot of diagrams and other demands, a lot of text. And people ask, give me this kind of quotation, a small information. It is another set of skills that an analyst needs to have. Therefore, if I want to say it briefly, it's some clients don't need it. If you want to make a decision for your portfolio, you need to read 30 pages of a text. For instance, you want to buy shares of Apple, and 10% of your portfolio is just... would it be enough to read these 30 pages, or what about quotations or the concentration of the main idea, so it could be comprehensible? The main thing is great when you can preach your message in a plain language.

Can analytics create hindrances for sales? They have a volume of data, and you need to sell it to a client.

Good afternoon. Thank you for your question. When it comes to off-topic, people lost many things because we are discussing it for the future students. When it comes to analytics and the interaction with the clients, I would discuss it for a long time. A function of analytics is not a function of interaction with a client. As a matter of fact, a front office is the business. They have orders, and they ask for observation. Vadim said...

Correctly, practically we see that a client won't read a guide, because when you see the word duration, you just shut the book and the last pages, pi and so forth and so on. The second closing of this guide or manual for the rest of their life. Actually, we have a new generation and we see growth of the new generation. If we look at the numbers, only 8% of our client base is people up to 34 years old. We have 8% of remnants and 35% are people from the client base, roughly saying people who are young and they go to these markets, they would be interested to read it. But people who are older, they are more involved in the informational area. If you want to read 30 pages, you need a strong desire to read it. I don't have, I have a lack of time to read all the 30 pages, and GPT chat can formulate just a short version of these reports. Somebody asked about what about chat GPT chat or analytics in the end, who will stay? I stay for analytics. Alex says, please don't go deeper if there is a double answer. Analytics should formulate a short report, an area where to see, and there is an arbitrage from the other part, and he listens to analytics and he has accounts and he asks questions and says about arbitrage. He wants to just get some part of it. And what about working out of these questions on the basis of this dialogue? What would be the approach of analytics or a salesman who can subdue, and an analytic can go and sell, and what would be a result of these actions?

Sales front office is a business, people who make orders. We work with the clients and we translate from the client's language to analytic language. I have 18 years of expertise in the analyst market. I saw many funny things. There's a quant and algorithmic trade, very smart people, and they express their opinions in quant and digits, numbers and apologies, and clients don't understand them. Therefore we need an interpreter who will explain everything. Analysts are support for front, and the other part is a kind of interpreter. Vadim, conceptually I agree with Alex. In any case, front generates a cash flow for business because of this activity, all the is being generated or developed, and we see the growth of projects and we pay salaries to employees. We need to help the sales department, but we have special features. We need to simplify the analytics. Let's try to see the golden middle in this here, because simplification is not okay from the other side, because you will have poor results and you will see it on the reaction of the clients, and you need to see the balance. You need to analyze a company and to preach your message in a simple language. We have of course GPT chats and they can make the main principles from the big documents, and we can see, okay, people say you used AI. You need to strictly control these things, because when you see that some analytical report was made of AI tools, it brings to refusal, people don't want to use it. It's a refusal from their side. What for do you pay? Where is the expertise? If it has to do with AI, you need to have a concrete understanding, analysts. What kind of tools can I use? Thank you. I want to continue this topic. The equity can be developed with the help of trust. I want to continue our dialogue. We actively use AI and young people, all of them use chat GPT and other tools, because they accelerate the process of work at the same time. Can an analyst be a public speaker? Is he an expert or a technical specialist? Alex, I have a question to you. Can we build an analyst career without public speaking? Probably it's impossible. I don't know, when I started my career, I'm an engineer. I have an education of engineer. I wanted to be an analyst, but the door was wrong, so to say. What about a flamboyant speech on the stage when it comes to user and information, and there is a division on gender of 40% and 60%, and asset division is very differentiating, and people starting from 44 years are holding a lot of assets, and there is a shift when there is an age allocation, it moves to the right. The older we become, the more assets we accumulate. The older a person, he or she would be in the chat less time. The older people tend to do like this, they don't like to type their messages. It would be easier to make a phone call. Likewise, you understand channels, gender and clients you want to deliver the information. It's a very important factor because a person can be very smart, like in Russian Griboyedov's book, and people say, okay, you say wasteless information, you need to understand whom you speak and what is the situation, and that's all from my side. Vadim, I have a question to you. Should an analyst at least interact with the clients? From my point of view, it could happen in different cases. Alex was right. He shouldn't do like that. The analyst has a lot of tasks. When it comes to the previous question, the analyst needs to be an expert on behalf of the company, raising its brand on TV, on online, internet broadcasting. His face is a brand. It's a matter of a reputation. We discussed it. It's worth discussing when it comes to fellowship with the clients. I want to remember Alex's answer. When it comes to retailing, I don't see a spreading. When it comes to institutional clients, it's another matter. An institutional client has a lot of access to data, and he or what about reading of these 30-page reports? The ending client, it's not only retail, and we need to find a balance between them. When it comes to institutional client, it can work properly. There is experience of Wall Street, and there is a monetization and an interaction with the client because they have a direct access to the data. In the context of this dialogue, they don't need mediators because they are professionals, they know this professional language, and they speak to each other on this language. What about penetration of internet? Everything is developing and accelerating. Apologies, I'm talking about AI development. We have young people here in the room. Can AI be a competitor of them? Can it change the position of the analysts, the position of the junior analysts? Let me start. From my point of view, it's impossible in the nearest 10 or 15 years. It's not a relevant case. I can prove it. First of all, you need to create special spare people, so you would have organic growth of a team, at least a defeation of a team. People gain a new expertise as they become professionals, as living people. Of course, they will look around, and there is a churn sometimes. If you don't have a career ladder and opportunities in the team of analytics, at the end of the day, you cannot change a person. Now you need to make a decision. What about GPT chat? We need to save low-quality resources when it comes to workers. It's not unusual. If we have a GPT chat, what else? What about one expert is a foundational guy, just goes away, and all the structure just crashes, and these experts will have a leverage to come to the nearest company, give me more salary, and we will discuss it, and other teams will search for these kind of experts in the market.

Yeah, I would agree with Vadim in this regard, because we can reason in the following way. Whatever you give a request to chat about you, it will always boast you. And when a person graduates from a university and when this person joins your team, and if you want to instruct them how to do all that, and if there is no person who knows how to analyze a company in a proper way, people will give the wrong prompt and people will give the wrong answers because he busts of chity, and there is a good methodology. In Japan, for example, when a beginner comes, first a senior person is given him as an instructor, then the person repeats what the senior person does, and then he should do. That's why I believe that the young analyst should do and repeat, and chat is a good tool to learn, because if I'm in charge of the whole client's business through chat GPT, I will see how the claims from the clients change, the ones who come to us, how the requests to the client support change. Three years ago, some of the requests were so easy to answer, because you could answer any question through the searching engine, and now through chat, the questions follow the extracts from the legislation. So I think chat is a learning tool, learning not of the machine, but learning of a human. It will never replace an analyst. I would agree with Vadim, because there can be a talent gap, because the young analysts are replaced by chat. But what's to be done? What young experts should do? Just to enjoy all the available tools, to be an efficient junior employee, efficient analyst. Well, I think that the most important thing in here is to study. Like people said in the previous sessions, that you should be open-minded, you should be curious, and the piece of advice from my side is that you need to learn how to speak very simply. When I ask people during the job interview, the financial advisors, when I ask certain indicators, they tell that there is a paneer in VB and others, and just I give him the description of IITA. What every letter in IITA means, then there are questions to this person. And when the person fails to answer challenging questions with simple answers of what it means for a regular person who doesn't have a background working at the stock market, this kind of analysts will not be appreciated, will not be demanded. You know, even children should understand us. When we try to get across very simple information, and if the person fails to answer simple questions, then it means that we mistake. For example, the same thing applies to bonds, changing of the interest rate. Well, you can tell us the story of the arrays. But if you fail to explain how the price value, the nominal price from the duration interest rate, why this idea should be there. So the key point is to learn how to speak easily for a person after communication to understand the information. From my experience, I've been working with clients for many years, and if there is a person in front of you and if you lo him with challenging terms, you will never tell that he doesn't understand these terms, because a reputable, distinguished person, a senior person comes and you start telling him this about IITA, he will tell like, I don't understand you, I don't understand what you're saying. He will tell like, it seems like it's okay, but I don't know. So my piece of advice is to make everything as simple as possible, and you need to check the feedback from a person if he understands or not. Probably you should draw something, because the information about the numbers cannot be perceived better by listening. Thank you very much for these pieces of advice, and I think guys should listen to us very carefully. Just to understand the core thing here, what it means to be an excellent employee. What means to be the indicator of your result, the way you did the work or the way the work impacted human results. So how we evaluate that? You can be right hundreds of times, you can make the best analysis, but if you can't convey the final information to your users and if there is no feedback from them, how would you evaluate your work? So one needs to know how to get across the information for the right people properly. So the retail broker represents the people with a very low financial literacy. And this is what you need to keep in mind. We don't mean that we need the skill of simple explaining or in-depth analytics. So the professionals are always talking about the things that are very important. You can tell challenging things with the complicated tech terminology in a simple way. It's a very demanded skill that I can find in the Wall Street Journal. So you can download what other people write. So some people succeed, some people fail to explain. This is not CIS issue. This is not some other countries. I think this problem is very common worldwide. But this is all about people. There is a person who reads and understands the information about the company. If a person starts seeing some challenges, this is not only the matter of understanding, but the text is structured in a wrong way. This skill is very demanded, and I think ChatGPT will not replace it. Within the case, I remember reading some articles about some works, and it turned out that people use the generation, and there are some logical inconsistencies in the text, and meanwhile, chat cannot resolve it. So when it comes to interview, the skills, what skills are needed, what analysts, what skills analysts need, well, I heard it, I heard it that the interviews are very tough, but according to us, they are not so tough indeed. So I think they can give higher bar to the applicants. We allow the candidates to speak up. This is not the matter of the right or wrong answer. If you have some elements of good technical skills, they are all needed, and unless those skills are, you will not be able to build the analysis. So another matter is the matter of logic, if you can express yourself correctly. So the logical chains are up to that. Well, we used to have some cases from the last academy when people could not technically pass the interview. Just a few points needed, but they demonstrated a very high level of motivation, and from our trainee, you know who those people are, we decided to recruit those people who failed a little bit to comply with that, but they had the motivation. So we can find those people because sometimes it's not the matter of technical skills, but sometimes you need to have a well-aligned logic and the skills that can be deployed and developed in the future. Vadim, from your experience, according to you, you recruited many people. I just want to know the percentage of the candidates who have the skills that can lead them to the practical part from day one.

Yes, from day one or there is something to be done. Okay. Well, let's talk frankly today. That's an extremely small percentage. What I want to tell you, Vadim, I have some guys. I see that some of the people are using smartphones out there, and I think this is the gap because if you consider those people as candidates, they will tell their secrets, what they mean, what they pay attention to, and if you want to join the financial sector tomorrow, these things must be heard very carefully, very attentively. And then when you go to the job interview, you can use this knowledge. So be very careful to what you listen today. So we have a very small percentage of those people who we hire, who we recruit. This is my frank answer. I mean, if we would be not so much a break, we would hire thousands of candidates instead of tens or sometimes hundreds. We pass through the screening process of 5,000 people, and if 25% are invited to job interviews. So if we want to talk about the harsh parameters, I'll explain you why. We worked with American market. 95% of all our requests and finding a CIS people for American market is very difficult. We used to have some other cases when CFA certification didn't mean that a candidate knows well the material. So sometimes there is a drillings, people just repeat some words as pirates and they don't know what those research mean. There used to be many cases, that was a surprise for me, that was a revelation, if you find a practitioner on the market ready to work knowing American market. Well, I don't think that there are no people like that. All people were trained from scratch, but okay. Yes, there are some people, but there are not so many of those people. There are a majority of people who you need to train. How to analyze this work? How to train people? How to analyze Kazakh companies? How to analyze American companies, but not enough for our level. This is what we try to find in people from the expertise perspective. We hope that AI tools and motivation will help us to expand your expertise. So when it comes to harsh criteria, there is a chance to work if you show yourself well during the interview or during the test requests. I think that's a very good idea. I think that can be elaborated on the next session, and I think the next request for the next section, Alexia, the question comes to you. I would like to ask you, what do you think, what is needed, what can be improved in the educational program to improve the skills from the practical perspective? So what skills can be improved from the practical side? I think the only option out there can be the following. People should study on the real-life case studies and business cases. I think it is all about that, it depends on this opportunity first. Second, so you can apply some practical sets of trainings and not to the teachers who learn theory, but to people who work with business. We also have our internal academy and brokerage for training people. We hired some specialists, and I can speak frankly that we considered some teachers from the universities, and they passed the job interview, and we required practice for ourselves, people to explain not what GDP is or not just the theory, but in terms of the currency distribution, in terms of the tools distribution, maybe there are some other matters. When the teacher from the university listens, it was really shocking. The teachers could explain well some economic terms that Chat can explain them better. If you want to read about a particular terminology and you want to understand what this term means, you can use Chat, but using a term in practice, this is something different. So you will have to use it in practice and show what can be used in practice and what not. Some analysts cannot use certain indicators which have been in venture investments and so on and so forth. This is what you need to understand. So there should be a practitioner in the real-life business. Thank you. Thank you for that. Well, I will keep my questions here because I really wanted to keep it in the educational sector. I just wanted to ask to give a chance for other people to ask. Well, young people, please don't hesitate because tomorrow we will join in our ranks. Meanwhile, I give you a chance to ask questions. Please go ahead.

So I just wanted to ask a question about the interview. How one can prepare to the job interview in advance? What kind of knowledge is needed? Well, when it comes to knowledge, it depends where you apply. Well, if I talk about my area where I can definitely give you the reason for what we do as the analysts, we evaluate the companies, we need to know what tools are used to evaluate the companies. There are many free-of-charge courses. If you talk about the valuation, you can find them in YouTube or in some other platforms, and English is also needed. When people ask if some public skills are needed, the communication is a very important factor. Communicating and learning in English is very important because this is a very voluminous part, intensive part. Communicating with the US companies, chatting with them, asking them questions that will help them help you during evaluation. I think this is the important part of our work. So English is needed, including the evaluation merits and the well understanding of the finances, CFA, run, English language, kind of those skills are all needed. So if you know how to build a DCF model, if you know English, then everything will be enough for taking the job interview. I think this is the base that can be the foundation that can be given at the university. Well, we are writing the reports. We check if candidates have skills or not. And in our case, championship, we had around 80 companies, more or less, four people for every company. So DCF made some things well. So if you are confident that you have good skills, then welcome. If not, if you have doubts, you need to check the way it all works and know how to pass it at the interview. Oh, by the way, the practice inside our company internally. We check the experience of a certain person and expertise, and if you pass in an interview, while your offer will be the indicator of your job interview. If the interview is failed, you'll not be given a job offer. Well, if we see that there was a mispricing of candidates at the interview level, different things may happen. But we adjust our work as the interview goes. And all in all, it works like that. So what's going to be your piece of advice? Where to go? What things are to be applied? It will never happen easier. No, no. The job interview will never be easy for you. Will never be an easy story. You need to check what kind of resources the company has. Well, look, the analyst onboarding takes the third year in a row. There are important steps and there are some challenges that we set to ourselves. We accept the candidates on and on. We check the interviews, and when you have questions, you need to ask interviews. Probably there was a person to find a proper person, or you have a huge turnover. There are some options that can be studied. You need to write to people in LinkedIn. It will give you entrance in reference company. Find out the data from HR specialists. If you ask questions, if you listen to these requests, you understand your area, your direction, and your target and your goal, it shows you as an interested candidate, and in comparison with other people, you look better. I have about 30 interviews where candidate speaks. I have no questions. We have a lack of time. That's all from our side. In the end of this section, I want to express my gratitude to all the candidates. And dear candidates, I want you to pay attention to this. Vadim and Alex were honest. They expressed the idea that you are not prepared. What about foundational basic knowledge? I just interpret their ideas. Get ready to be developed, to boost your skills in order to sell yourself there. There will be an opportunity to come into a team, and at least young people, you have a chance to raise your skills and analyze your work in order to be on the stage and to sell. It's the only opportunity to compete under the sun. I want to wrap up our session. Thank you very much. From my point of view, very interesting recommendations were delivered both for specialists and for major, apologies, for junior analysts. And I hope some things will be heard by you and implemented. Thank you very much.

So ladies and gentlemen, I want to recap. I'm not a financial expert, but a seller with 20 years of expertise. One young man asked questions and he was memorized. If you were afraid to ask questions, please come up to these people and ask questions of them. Then you will have an opportunity to have a job in 3:55. You should come back because we will have a serious panel session.

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So I think there somewhere here and there, it's okay. 30 seconds left before we go. Then we continue. Okay guys, what was the coolest insight today? The best insight. The skills. I heard about the skills. What kind of skills? Soft skills. Soft skills, as someone told, software coding and soft skills. So you were talking about soft skills, but what's left after one hour talk? What really left about soft skills? What is really important? Open mind. Open mind. Open mind is important. Okay. Excellent. What is higher, the technical capabilities or soft skills? The balancing between the soft skills. So it seems like some people are lagging behind in technical part. So I'm with you. So what other insights did you have? DCF. Someone remembered the abbreviation DCF. So okay. But for me, my core insight is that there are 300 developers behind one broker, and this is not the end, that's the first story. And for me, a certain insight was the following, that one speaker was talking about informational security in the very first discussion, although having hundreds of different events about informational security, informational technology, the core thing is the informational security. One of the most important aspects is the informational security, and what matches here, the technology and the money, and now we remember all those outstanding hackers that want to be integrated. Okay, ladies and gentlemen, I think we can start on that note. Okay, let's talk a little bit more. You understand yourself that today we have highly distinguished guests, the senior experts, and they are never late, but they are somewhat delayed to come. Okay. What I already recommended you, just to approach to someone and seek for the employment. Okay, who tried to seek for the employment, raise your hands. Okay, by the way, next time when you have a chance to ask questions, please stand up when you ask the question, but introduce yourself for people to remember you. For example, my name is... Please remember my name. My name is Larion because I have a rare name. This is the story. Well, people are looking at me so curiously. You know, sometimes it's a well-directed thing when you have to pull the time. There is like, I remember from the story, they were telling the anecdotes waiting until other people to come. Okay, my anecdotes don't finish, and let's wait for others to come. Okay, who's investing now? Please raise your hands who are investing now. Okay, that's a cool thing. And who really loved this 1% story? Did you hear about this 1% of investments in hatching? Who will take this example? Who knew about this before? Raise your hands. Okay, there was this, that's not a new thing for you. Okay, that's not a novelty. Okay, that's not an innovation. Okay. Whose mood changed about the financial market? Whose vibe changed after looking at the changes when Vadim and Alexei were talking, was like snowballing different terms, and did someone realize that this is not mine? Okay. There was a strange question out there because the ones who thought like this already left this room. But luckily, when I check the audience, I see that the room is full and no one left. It all means that we are on the same page and we are on the right track. Well, what else I want to tell you? Just who are the biggest companies globally worldwide? Nvidia. Who else? Google. What else? Who else? Tesla. What else? Pay attention. Everybody names basically technological companies, and their marketing is very driven. And what is the largest of the companies? Microsoft. It was divided for many pieces. It's out of the game. Who else? Nvidia, I agree with it. Nvidia is the largest and the most expensive. Oracle. No, it doesn't reach the standard. Amazon. It doesn't reach the standard too. Who else? You started to think correctly, in spite of the fact we are on the financial forum. Everyone calls social networks and technological companies, but nobody names these kind of organizations. The largest companies are BlackRock, and the largest companies in the world are financial companies who manage all the money. And if you want, you can go up to this level, and the main feature is this. If you want, you can go in there. All the doors are open there, and all the speakers will speak about accessibility of this level. And Kazakhstan is coming into world technological society and circles, and this start is great. Tell me about unicorn kings, and everything happened in your time, unfortunately. It didn't happen in my time, but now I cannot reach because of my age. I can't reach to go to the circles. Now many technological opportunities and startups are being opened up, and among these experts will be some of you, and some of you will be in investment funds, and maybe you will be managers at the top level. What about starting about our this section? No. Okay, that's funny. Let's compose some interesting things like flash mob. What kind of flash mob do you mean? A dance flash mob. We have a lot of students here, that will be funny and interesting. Let's make this kind of flash mob like Vadim does. I have a tradition in the conferences. I create, I take the video off in the end of a conference. The feature is to indicate that interested people goes until it reaches its target. Let me take the video off. Just turn the lights away. I want to see the people, and on the count one to three, you need to make some noise and raise your hands and wave your hands. One, two, three. How many? We have about 400 people here. Thank you very much. The idea with flash mob was successful. That's all from my side. Likewise, I see Timur just came in the room. We can go on, and the next panel session is about education and reality in the year of... Timur Turlov, a main person in the Freedom Hall, CEO of it, Mjang Madiv, general director of Autonomous Cluster Fund, Anakap, you're welcome, the floor is yours. A little bit later, Saitat Norb, Minister of Science and the Higher Education of Ministry of Education of the Republic of Kazakhstan will be with us, and moderator of our session will be Rahimar Akbay, economist and journalist. You're welcome. Take your seats, please.

Dear ladies and gentlemen, it's a huge interest for me to moderate such a session with an audience in a very specific moment when we are not in the middle but at the beginning, just some web of technological revolutions can be felt and we change everything. Then it's not just simply words. What the declarations that we heard from Microsoft and other technological giants, they tell like by year 2027 the majority of workplaces will be replaced with the artificial intelligence, and now we have some agents open floor and some of them are in use now. And for me the latest discovery was the use of, you know, lab that performs our work 10 times better than some other well-known analysts from my sector, and I believe that Saitat Norbback will join us shortly. The most triggering and burning question is, so what's to be done? What junior should do? Because we all see now the effect of Robin Good. On the contrary, this is about the technologies and artificial intelligence that helps those who are really strong, who are really advanced, they empower them with many boundless tools and weaken the who just joined the labor market. In this regard, Timur Turlov, this question goes to you as one of the most prestigious employers, as one of the most prestigious brands. How you perceive juniors? How juniors can beat the market and be very successful? Thank you very much.

In professional circles, bring coffee or tea, be a servant, and then you will be a lord. And what about your professional career? You will be a person with trust. You will have a good reputation. You will have inner wisdom which comes from your professional experts and colleagues.

When it comes to the appearance of AI, what about this situation? We still have this situation. It works properly. These principles work properly, but all the way needs to be going through with the help of the AI. The base of your work is not, or the measure of your work is not your level of tiredness.

You need to find simple solutions to difficult tasks. Why do people want to strive to knowledge? Because they provide an easier way to solve big problems. It would be faster. Therefore, AI could be your faithful friend. And if you are a person who works with pipes, it will help you to make fewer mistakes and to have a large volume of interesting orders.

At the same time, these are people who are burning with interest. You have energy, you have chances and opportunities to manage these technologies. If you're a friend of these technologies, it's a cool situation. Many people who are 50, 60, or 70, it's difficult for them to manage things. Their mentality patterns are different from yours. You're young people, and for the first time in history, you can get some advantage in comparison with these people. But don't be proud.

We in the 1990s and 2000s, we could build financial models on the basis of excellent... I became a CEO of a financial company. I want to brag: according to the rating, I am the youngest manager in our team. And technological philosophy and structure of society could help you to manage services of AI and to build different chatbots of AI. And when you enter a company, it's just the plan of the company. You can bring transformation there, and your career will go up, and you will be a cool manager.

I absolutely agree with you in this sense. There is the same moment. It was never, we didn't have the easiest situation like now. You can learn easy and fast, and if you have a serious task, you can start to accomplish this task, and then I will support you to make this great work. It can be your mentor and teacher, and if you have no way out, it will help you. You have a brain, and it will help you to develop your brain.

And what about desires of AI? You can manage the knowledge much faster than before. It's a good direction. And what about great challenges? Just meet these challenges. Don't be afraid of these challenges. If you have a desire, you delve into details, into all the lines.

One of my colleagues I worked with, he's one of the founders of Freedom. He made a career of a financial expert, a very great expert. When we were beginners, he couldn't manage Excel. He couldn't make programs and software because of Google and a high level of motivation. It was the start of his progress. The first step was a calculator, then Excel, the third thing about writing macros. Then he served Google's and basics for applications, and he started to write more complicated algorithms, then BASIC, then he managed MySQL, then he managed databases which are more complicated. Finally, he became our accounting system architect, and Google answered all his questions even before.

In the past, when it comes to the current world situation, probably you can be very flexible and adaptive. Who could get a meal now? Then you will have bookkeeping, accounting, wisdom. Maybe you don't need to get a special education. It needs to be a foundation to ask questions, and it's a tool. But then understand your goal and don't be afraid to ask your questions.

If you ask questions, it's more important because you will find the answers. Tomorrow just highlighted the main quality: it's high motivation. Now, and I persuaded you, you are in the most unique situation. Nobody was before there when education and these things are affordable and accessible. It's in your mobile phone. What does it worth to spend your time by education in a traditional way?

What about gym? It's a useful thing because you make push-ups not only not to be a professional push-up, and you train your muscles. In the same way, you train your brain. It's useful because in the process of this education you face problems, you manage to solve the problems. What about social disciplines? And you comprehend this world: less magic, more physics in the world after acknowledging the world. If you have this kind of mentality, if you have a great university, that's cool.

The uniqueness of a diploma from formal higher education, it's not so cool. Almost everybody in Kazakhstan has this kind of diplomas. The use of education couldn't be underevaluated. Your diploma without experience is useless. Some people don't have diplomas, but they earn a lot of money and they can go up to a great position. If you studied in an institute or other kind of university, you would boost your skills. That would be great if we compared it with... if you have this school, you will face complicated tasks and you will solve the problems. If you overcame something and you had complicated things, it would be a great advantage for you.

Nevertheless, the actuality of a gap that profile universities... is it sufficient to start your work? What about this gap?

You are not only the head of AIT in the CIS, the largest one in CIS. You always keep connected with very outstanding people. You were in the Silicon Valley. What about trends? And who is nervous that this AI trend will break this technological trend?

It seems like all people know what to do. They know how to create startups, and there are some people who can do that, but hands are not enough. That's a huge shift due to the technologies development, and this can be a unique thing that requires some competences, understanding business processes, agile.

Well, just a few words. So, to what extent this outstanding technological trend dynamics is unchangeable and agile, and it breaks the value of the highest education and diplomas, both here in Kazakhstan and in the US?

But what happens if this candidate has just graduated and he has no working experience?

Okay, Timur, when making a job interview with someone, what qualities, what professional aspects do you consider in the forefront?

But because our session is called 'On the Verge of Education and Technologies in the Era of Artificial Intelligence', we will come to this idea a little bit later. I'm concerned about the labor market in the US as the most complicated, as the most diverse employment market. I was inspired by 1.8 billion USD of students' debts. I wanted to check this number. It turned out that 30% of these debts, people prolong around 20 to 30% of defaults for these debts, and the average payoff of those debts is around 20 years to repay the diploma. So many investments did not pay off itself. So people didn't have enough profits to repay their education. This is what I wanted to tell you.

Guys, let's talk about the challenges the financial regulators face given the emergence of this new technology, the artificial intelligence. I mean, Timur, what are the latest challenges and what are the latest trends that you can see in this regard?

Maran, you mentioned the challenges and related transformation with such an organization as Aana Hub. Now we have a challenge of the transformation of the whole country, all sectors of the economy. So you are involved, right? You are the person who defines the vectors of this transformation. Could you please tell me just in a few words what the transformation will look like? I don't really understand that.

And to conclude, I'd like to ask you a provocative question. So in 2026, if our speakers were the employers, what would you choose: startups or founders, or would you prefer to be a regular person? Maran Makjan, for example, you wanted to replace yourself from the employed person to a startup founder.

Thank you very much for your precious insights. A round of applause to our speakers. As a matter of fact, we have a unique chance, we have a unique opportunity for students to ask questions to the panelists. Okay, I'll take three questions from the audience. There was a young lady over there who raised her hand.

Hello, hello everyone. My name is Akbasa. That was a great pleasure to listen to your session. I work in the controlling department of a bank, and I'm a fourth-year student. You told that AI will not erase some jobs, but the jobs will change. But when it comes to such a position with regulatory institutions like the National Bank, who have compliance and regulation, will there be manual work? Will there be handling hands operations? Will it survive or not?

So a young person over there in the backstage. My name is Sayyat. I'm a fourth-year student of Narxoz University. My major is finance. I have two questions to ask. Well, what should a student do just to close the gap between academic theory and the requirements of the corporate environment? Thank you.

The young man over there. Hello, my name is Raful. I'm 18 years old. I'm a trader and investor. This is how to explain people what this artificial intelligence is. And some people believe that this is cheating. But this is not the purpose to explain. But how to get the confidence? And not all people understand what it is all about, but not all people trust them.

And ladies and gentlemen, please don't fall. Please take your seats. The next session will be completely in English. We have special simultaneous interpretation devices. Please take the devices for those who have some challenges with English.

Now we will proceed to the championship. The stage will be prepared very shortly. Okay. What kind of insights I got from the last session? Not like an insight, but kind of this. Okay, ladies and gentlemen, please don't part. Please don't part. Please don't go.

Also, this is what I mentioned in the first panel session. Please don't lose your chance.

Ladies and gentlemen, please come back to the room because we are about to continue our event. There will be the cases championship.

I'll tell you a small case for the ones who listen to me. I'll tell you a small case. I would tell you what would happen if you returned back to this hall.

Ladies and gentlemen, please proceed to the room. It was unexpected coming from the room. Please proceed to the room, and we will go on, and we will discuss cases of our students.

I see the teams are ready to present their solutions and their products.

In spite of the fact that part of the people went out and tried to catch experts during the coffee break, I see that you have very intensive discussions, but it's a good thing. It indicates that you are interested. So, ladies and gentlemen, please proceed to the room.

Good afternoon. Let's get started. We will have a very special part. As you know, English language, everything will be in English. It will be a transparent and logical example why we did so, because the English language is not a basic one. What for do we need if we have basic languages like Kazakh and Russian languages? We have a lot of fellowship with American companies, that's why we need to understand skills of students. Therefore, we will speak in English, and then we will listen to presentations of guys, how they will defend.

Let's bring our first team. Welcome to the stage. Can I have a blow here? I want to congratulate you guys on becoming in top three and wish you good luck. Let's see how you do.

So, okay, okay, everyone, imagine that your company, one of your largest clients, the client that literally validates your entire business model, suddenly decided to slash the commitment by 47%. What are you going to do? So the thing is, in that industry that is heavily locked in backlogs, it's going to be a problem. So today, with that, we are introducing to you CoreWeave, the company that the market is right now pricing as a growth company, but this company is also having its own downgrades.

And with that saying, we are Team RNC. My name is Big Jean, my colleagues Tuan Ayan, and right now currently we are introducing you to a sell recommendation of CoreWeave stock price. Right now, Core is trading at $80, and with our valuation, it yields $64, which represents like 20% of downside already. But the most important thing here is the bear case scenario and the bull case scenario, because our investors are facing an asymmetric risk profile, because the bear case is giving like a collapse of 60%, while the bull case is implying just a return of 13%.

With that being said, let us continue our thoughts with our colleague Tuan.

So let's look at what happened in that market. OpenAI reduced its commitment by 47%. So which means that before that introduction, our commitment was $22.4 billion, and our visibility, the contract lasted more than five years. But now we have only $11.9 billion of commitment and visibility of three years. What does this imply? It means that our CDS blew out, and now our credit rating may downfall. Our visibility shortened, and it set a precedent to other companies to recall their contracts.

But one optimistic case in that scenario is that we increase our liquidity by gaining a termination fee of $500 million in cash. Now let's move on to the next slide. And so what can be the effects of that news? We decided to consider it in three ways: the impact on revenue, growth outlook, and overall risk profile.

Our revenue visibility consisted of three key points: it's take-or-pay contracts, our collateral value gap, and our backlog. So take-or-pay contracts, before that we were sure that 100% written in the contract would be paid for us. But now it's no longer a fundamental assumption. It opens the room for some flexibility, and other companies can also redesign their contracts and cut their commitment.

Secondly, we are a heavily asset-based finance company, and we use the GPUs from our contracts as collateral to build our infrastructure. However, as this contract price downgrades, we are under the threat of financial instability. And lastly, our main revenue driver was a backlog that consisted of over $55 billion, but now it imposes a 20% reduction, which then turns to a gross decline.

And we are no longer available to meet the more than 100% growth in revenue in 2026, which also imposes the next problem that our GPU capacity increases. So we have free GPUs that need to be utilized in an already established market. We need to find new clients for our systems. And lastly, our overall risk rate increases as our CDS blow out.

Okay. Now let's look at our risks. Our team considered three main risks: market risk, strategic risk, and financial risk. And in our opinion, the financial risk might be the most probable and the most severe one, as it includes our current debt and the future debt.

So some of our debt contracts that currently exist, such as DDTL3 contract, use the contract realization rate as a convenience. So it's a benchmark for our debt performance. But however, when we shrink the cost of the contract, our contract realization rate also declines, meaning that we are no longer available to meet the requirements of the contract. And secondly, we will be higher priced for the future debt, and it will be difficult for us to build another GPUs. Second one is a strategic...

risk, and these two risks are highly interconnected. So first of all, as we said, this cut imposed a domino effect. So our other clients can cut their contracts, and we have a high customer concentration in the face of Microsoft. And if Microsoft follows the OpenAI steps and decides to cut their contract, we can repeat the case of Imagination Technology and Apple. When Imagination Technology was a main GPU supplier of Apple, and when Apple decided to withdraw their contract, Imagination Technology had to be privatized with a Kenyan private equity fund. And the last one is the market risk. So our main customers and our direct competitors are building their GPU capacity. For example, even Microsoft is building their Azure GPU stations. And if the demand falls and competition rises, our market share may decline.

Yeah, in our valuation analysis, we have built a very large-scale DCF model, and all other things being equal, status variables after the drop out of OpenAI, we today need to consider two things: that's the revenue part and the capex part, because other parts like net working capital, days outstanding, or opex will adjust accordingly. So in revenue here, we have two streams of revenue: existing revenue and total revenue from backlogs. Existing revenue is the revenue that are right now on the income statement of the company, and we just increase it by the CAGR of 26%, which is the average of what our analysis gives.

And the most interesting part is the total revenue from backlogs. Total revenue from backlogs we have after OpenAI dropout around 45 billion dollars, and we have divided this by projected periods, and after that we adjusted by CPI US because our model is in nominal terms, and also add retention rate. Here our key assumption is in retention rate because after expiration of the contracts, of the backlog contracts, we assume that companies will continue using our services. So it's a pretty basic assumption actually, because if it was not so, this company is not interesting, because in the terminal period it will be one-off, and we need to exclude it from the terminal value. So yeah, 92% was a base case, that's a historical value for CoreWeave, and bull case is all revenue is recurring, 100%. Base case is 85%, that's industry average. And here, the key note we want to say is that bear case is not actually that bear, that's 85% industry average, and I would say that some valuation analysts would say that in the long term it will merge to the industry average 85%. So bear case is not that bear, but as the price of the bear case we are receiving around... pretty sell. The next slide.

Yeah, capex. We know that around 90% of the capex is spent on the new GPUs. So by backward induction, if we conduct the research and found out how many GPUs are needed, we can conclude how much capex is needed overall. So here's how we calculate new GPUs for the revenue backlog generation. We know GPUs for the end of the period for each period, active power, and active power per GPU. So look at the history, it's pretty stable. And using these vivid stable values, we can go to the projection and calculate GPUs needed in the projection. Active power in megawatts are received from the backlog that we are contracted already. So we know this value, and after adjusting for our retention rate, we have these values for the new GPUs.

For the second table, we calculated 27. 27 is the value of how many GPUs are needed to calculate marginal revenue of $1 million. That's already taken from table one. And overall, we can calculate here the new GPUs that are needed for revenue generation. So next slide. Here you can see our capex in the terminal period. We said the third quartile was a comparable company analysis because we are a neocloud and our customers are mostly AI, and we need to spend more than our customers. That's the results of our DCF. So base case is around $64.

Now let's move to the comparable companies analysis. And I want to say that it is only for indicative benchmarking and for indicative purposes, and was not used as a primary valuation method. As you can observe, we have analyzed three peer groups: the GPU suppliers, hyperscalers, and neocloud and AI infrastructure. Considering the first group, GPU suppliers, as you can observe, the multiples are pretty high, and this is due to their technological advancement of the sector and multiple benefits of the diversification and the lower risk models of the cloud systems in hyperscalers. And the last is our closest peer group, neocloud and AI infrastructure.

Let's start from the cost of equity. The key case here is the beta. We have calculated the beta based on the price sensitivity of our peer groups, cloud and AI infrastructure, against the S&P 500 benchmark on a two-year weekly basis. And then we have used the Blume adjustment to make the beta smooth in the long run. And after we unlevered it by removing the capital structure, and finally we relevered it for the target capital structure of the company, and our cost of equity is nearly 13%.

Let's move to the cost of debt. Considering the cost of debt, instead of relying on the historical borrowing costs or the senior unsecured debt of the company, we analyze the market-implied default risk, which is based on the nominal risk-free rate and the CDS spread. The company now has a CDS spread of five years, and this is nearly 600 basis points. After that, we compared this to the benchmark analysis of the broader industry and made a mapping, and by this mapping we have derived that the issue-specific basis premium is nearly 300. And after that, we analyzed the two scenarios that the credit model, that the implied credit rating of the company will be downgraded to the B or triple C plus scenarios. And after combining the CDS spread with the normal risk rate, their final pre-tax cost of debt is 9% and the 13% in base and the bear cases respectively. Overall, weighted average cost of capital is 12% and 13% respectively.

Okay, let's dive into scenario analysis. So for the, of course, we're going to start from the bull case, and according to our DCF models, for the terminal period, 68.8 billion dollars were projected for a terminal period, and we are also showing you two valuation multiples, EV/Sales and EV/EBITDA. But let's dive into bull rationale because you can see actually these multiples here on the screen. So the first thing is, of course, CoreWeave's partnership with Nvidia, because the thing is they are also getting a lot of very good and high-demand GPUs directly. Second thing is contractual risk mitigation, because 96% of the revenues are coming from long-term contracts, so the revenue visibility of those companies is so much better than usage-based cloud models. And the value chain integration, M&A, exactly, acquisition of these AI-based companies made this business of this company diversified, by basically they can provide the AI-based solutions. So with that being said, for our bull target price, $194 per share is going to be our bull case scenario.

For bear case scenarios, terminal period based on the DCF model is going to be 48.5 billion dollars with these sales and EBITDA multiples. And the thing with bear rationale is erosion of backlog integrity, since 47% cuts means that you cannot just assume that these backlogs are absolute incomes. And but the new things that I'm going to talk about is legal overhang, because right now CoreWeave is on active ongoing court cases with some entities. So with that being said, bear case target price is $32 per share. We also constructed sensitivity analysis, and for your understanding, we created a football field for our visualization. But the main point here is that our scenarios were mainly affected with WACC and the backlog recognition. Here you can see that change in WACC and the LTR, which is the long-term growth rate, and the WACC to backlog retention rate. With that being said, we firmly recommend... our firm recommendation is sell, because the fact that with all the arguments being said here by me and by my colleagues, and the thing is that within one week, the quarterly report will be published. And the thing is, with this court also, March 13th deadline is also going to reveal very many things that's going to make our case legally clear. With that being said, thank you for your attention, and we are ready for your questions.

Can you hear me? Yes. Yes.

Hello.

Hi, I'm Paul. How are you doing?

Great.

First of all, since I'm from the United States, you mean American football, right?

No, but yes, I'm not sure. I'm not sure.

We should do our research, I think.

I'm just kidding. I'm just kidding. So you're absolutely right. In a few days when they announce their quarter, much will be revealed.

And you did mention on your bull case, you know, the relationship with Nvidia.

Right, so Nvidia now owns about 9% of CoreWeave.

And a couple weeks ago, you know, they added $2 billion to their stake.

What do you think about if this nasty situation happens?

Number one, here Nvidia comes in to rescue. Don't you think that they would do that since they have such a, you know, big stake in the company?

Um.

Okay.

We firmly believe that they're not going to help in that situation, since they are also seeing that some contracts have been reconsidered, and $11 billion is a lot of commitment. And also, I want to talk about the case of Apple and Imagination Technology. Yeah, I believe that because of the fact that... I believe that maybe Nvidia is going to help, but not in that much sense. So in the end of the day, it's going to be privatized again. Not again, but privatized.

Okay.

I can go forward.

Yeah, please do.

So my question is, why did you decide not to use multiple models at all in your analysis?

Yes, I have previously stated that it is only for indicative range, because as you can see from the table, we have three peer groups, and the most closest ones are the last group: hyperscalers, neocloud, and AI infrastructure. And there we can see that the only perfect match is Nebius, and others are not the perfect match. And if you are considering the market approach, we have only three very close companies and one perfect match. And we cannot use the multiples of the hyperscalers and the GPU suppliers in the total one, because there is different risk and there is different maturity of the company. And we believe that EV/Sales is not the final one, because today, due to the immaturity of the company, its EBITDA and other profitability metrics are distorted, because we cannot ignore high depreciation cost, we cannot ignore its high leverage, we cannot ignore other risks. So we are now only using the EV/Sales, and we think that based only on EV/Sales, we cannot use it as a primary valuation method, because EV/Sales don't show its effectiveness. We believe that there should be more stabilized earnings in the future to use it as a primary valuation method.

Okay, thank you. Ed, please.

Hi, I'm Ed Maguire. Thank you, team, for your presentation. I wanted to go to the risks slide where you had the matrix. This one. Yes. And could you talk about your thinking, how you prioritize your thinking about the risks, and whether, if we did get, for instance, renegotiation of contracts, could CoreWeave start a price war with some of the competitors and really hurt, you know, and boost their own competitive position by actually, you know, changing the competition in the marketplace?

Thank you for the question. It's a really interesting question. So first of all, about our prioritization, we looked at the short-term impact. For example, the Stargate deal is already signed, and if in the short term this situation happens, our liabilities will be very soon. So we thought that it will be the higher significance, and other ones we put in a lower significance and kind of lower probability because of that. So we refer to the duration of the contracts and maintenance. And about the price war, so if we establish a price war, I think it can hurt our business even more, because currently we are a heavily indebted company and we are operating in a negative way. And if we decrease our prices to attract clients, yes, we can attract clients and fill the gap, however it will hurt our revenue even more.

Hi everyone, my name is Aortal. I'm a senior equity research analyst covering tech companies in Broker. So my question is about your DCF model. When OpenAI decided to reduce their contract volume, do you expect this reduction to affect your short-term revenue, short-term backlog, or did you model for this to reduce your long-term revenue prospects? How did you model it?

Yeah, okay. So before that, initially we had around 56 billion revenue backlog, and we decreased just the base, as a base of 56, to sort of 45, and divided it by the periods. So because the base is decreased now, the terminal value is also decreased. So it goes to terminal value like...

Hey guys, my name is Mikan, and I'm a strategist, an equity strategist. So first, I would like to mention that you did a great job. A lot of parts of your presentation are really great, and I'd like to mention that how it looks like is really great too, meaning that it should be informative and at the same time, visibility is really great. So great job, guys. Could you please tell me why you put such a big emphasis on OpenAI? So I mean, why do you actually expect that OpenAI will leave the company as a customer, not for example Meta or Microsoft? Why OpenAI?

I'm sorry. Can you please repeat the last part of the question?

Yeah, sure. So, you expect that OpenAI...

Mhm.

won't be a customer of CoreWeave, right? As a bear case.

Not exactly. Not exactly. They're going to be customers, but they are going to...

slash, right.

Yeah.

So why do you actually expect that OpenAI would slash?

Not for example Microsoft or Meta?

I believe it's a condition of our case for final stage.

Yeah, yeah, yeah. So because of that, yeah, I would like to consider slash Microsoft.

Got it, thank you.

Okay, thank you guys. Let's start. Yeah, that's it. Thank you very much for your time. Thank you. Let me get there.

It was a great effort from our team here, all the way from ASA, which is very good. But now we go with the Lemon Brothers. Come on, guys. Go on the stage.

Okay. So, good luck, guys.

One, two, three.

So after a period of strong investor optimism, CoreWeave faced a decline which was motivated by OpenAI's reduction of revenue backlog. The motivation behind OpenAI's decision is strategic reallocation of compute resources, not a breakdown in CoreWeave's operations. So the question is, was this breakdown fundamental, or did the market just overreact? We believe that sentiment cracked, but the business didn't. The show must go on. We issue a buy recommendation for CoreWeave. Our valuation, which includes DCF and multiples, gives a target price of $82, which is a 20.7% upside from the price of $68.

There are three reasons behind our recommendation. First of all, CoreWeave is a fundamental neocloud with strong demand amid AI scarcity, and it outperforms its peers technology-wise. Secondly, we believe that spare capacity would resell quickly, and $500 million of termination fee would provide a liquidity buffer for CoreWeave. And third, diversifying revenue streams. In the future, CoreWeave would be able to limit the risk of customer concentration. My name is Akmal.